Journal articles: 'Energy efficiency, traffic engineering, wired networks'

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Fondo-Ferreiro, Pablo, Miguel Rodríguez-Pérez, Manuel Fernández-Veiga, and Sergio Herrería-Alonso. "Matching SDN and Legacy Networking Hardware for Energy Efficiency and Bounded Delay." Sensors 18, no. 11 (November 13, 2018): 3915. http://dx.doi.org/10.3390/s18113915.

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Both economic and environmental costs are driving much research in the area of the energy efficiency of networking equipment. This research has produced a great amount of proposals. However, the majority of them remain unimplemented due to the lack of flexibility of current hardware devices and a certain lack of enthusiasm from commercial vendors. At the same time, Software-Defined Networking (SDN) has allowed customers to control switching decisions with a flexibility and precision previously unheard of. This paper explores the potential convergence between the two aforementioned trends and presents a promising power saving algorithm that can be implemented using standard SDN capabilities of current switches, reducing operation costs on both data centers and wired access networks. In particular, we focus on minimizing the energy consumption in bundles of energy-efficient Ethernet links leveraging SDN. For this, we build on an existing theoretical algorithm and adapt it for implementing with an SDN solution. We study several approaches and compare the resulting algorithms not only according to their energy efficiency, but also taking into account additional QoS metrics. The results show that the resulting algorithm is able to closely match the theoretical results, even when taking into account the requirements of delay-sensitive traffic.

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Kumar V., Shiva, Rajashree V. Biradar, and V. C. Patil. "Design and Performance Analysis of Hybrid Energy Harvesting and WSN Application for More Life Time and High Throughput." International Journal of Circuits, Systems and Signal Processing 16 (January 17, 2022): 686–98. http://dx.doi.org/10.46300/9106.2022.16.85.

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the technology of wireless sensor-actuator networks (WSANs) is widely employed in the applications of IoT due to its wireless nature and it does not involve any wired structure. The wireless systems that are battery-driven can easily reconfigure the existing devices and sensors efficiently in the manufacturing units without employing any cable for power operation as well as for communication. The wireless sensor-actuator networks that are based on IEEE 802.15.4 consumes significantly less power. These networks are designed and built cost-effectively by considering the capacity of battery and expense so that they can be employed for many applications. The application of a typical wireless Autonomous Scheduling and Distributed Graph Routing (DDSR) has illustrated the reliability of employing its basic approaches for almost ten years and it consists of the accurate plot for routing and time-slotted channel hopping therefore ensuring accurate low-power wireless communication in the processing site. Officially declared by the controversial statements associated with the government of Greek experiences fourth industrialization. There is a huge requirement for sensor nodes link via WSAN in the industrial site. Also, reduced computational complexity is one of the drawbacks faced by the existing standards of WSAN which is caused because of their highly centralized traffic management systems and thereby significantly improves the consistency and accessibility of network operations at the expense of optimization. This research work enables the study of efficient Wireless DGR network management and also introduces an alternative for DDSR by enabling the sensor nodes to determine their data traffic routes for the transmission of data. When compared to the above two physical routing protocols, the proposed technique can drastically improve the performance of a network, throughput, and energy consumption under various aspects. Energy harvesting (EH) plays a significant role in the implementation of large IoT devices. The requirement for subsequent employment of power sources is eliminated by The efficient approach of Energy Harvesting and thereby providing a relatively close- perpetual working environment for the network. The structural concept of routing protocols that are designed for the IoT applications which are based on the wireless sensor has been transformed into "energy-harvesting-aware" from the concept of "energy-aware" because of the development in the Energy harvesting techniques. The main objective of the research work is to propose a routing protocol that is energy-harvesting-aware for the various network of IoT in case of acoustic sources of energy. A novel algorithm for routing called Autonomous Scheduling and Distributed Graph Routing (DDSR) has been developed and significantly improved by incorporating a new “energy back-off” factor. The proposed algorithm when integrated with various techniques of energy harvesting enhances the longevity of nodes, quality of service of a network under increased differential traffic, and factors influencing the accessibility of energy. The research work analyses the performance of the system for various constraints of energy harvesting. When compared to previous routing protocols the proposed algorithm achieves very good energy efficiency in the network of distributed IoT by fulfilling the requirements of QoS.

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Fu, Shu, Hong Wen, Jinsong Wu, and Bin Wu. "Cross-Networks Energy Efficiency Tradeoff: From Wired Networks to Wireless Networks." IEEE Access 5 (2017): 15–26. http://dx.doi.org/10.1109/access.2016.2585221.

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Pavlovs, D., V. Bobrovs, M. Parfjonovs, A. Alsevska, and G. Ivanovs. "Evaluation of Signal Regeneration Impact on the Power Efficiency of Long-Haul DWDM Systems." Latvian Journal of Physics and Technical Sciences 54, no. 5 (October 26, 2017): 68–77. http://dx.doi.org/10.1515/lpts-2017-0035.

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Abstract Due to potential economic benefits and expected environmental impact, the power consumption issue in wired networks has become a major challenge. Furthermore, continuously increasing global Internet traffic demands high spectral efficiency values. As a result, the relationship between spectral efficiency and energy consumption of telecommunication networks has become a popular topic of academic research over the past years, where a critical parameter is power efficiency. The present research contains calculation results that can be used by optical network designers and operators as guidance for developing more power efficient communication networks if the planned system falls within the scope of this paper. The research results are presented as average aggregated traffic curves that provide more flexible data for the systems with different spectrum availability. Further investigations could be needed in order to evaluate the parameters under consideration taking into account particular spectral parameters, e.g., the entire C-band.

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Hussein, Mohammed, Wisam Alabbasi, and Ahmad Alsadeh. "Green distributed algorithm for energy saving in IP wired networks using sleep scheduling." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 5160. http://dx.doi.org/10.11591/ijece.v11i6.pp5160-5169.

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Energy saving has become a critical issue and a great challenge in the past few decades, and a great effort as well is being made to reduce consumed energy. The Internet forms a major source for energy consumption. Therefore, in this work we propose an algorithm for energy saving in distributed backbone networks, the reduced energy consumption (RedCon) algorithm. In this paper, we introduce a new version for saving energy on the Internet by switching off underutilized links and switching on idle links when the network is overloaded in a distributed manner over the network nodes based on LSA messages and without any knowledge of the traffic matrix. Our algorithm is more accurate and outperforms other algorithms with its time checks and advanced learning algorithm.

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Kumar, Manish, Rajeev Tripathi, and Sudarshan Tiwari. "A Weighted Routing Scheme for Industrial Wireless Sensor Networks." International Journal of Wireless Networks and Broadband Technologies 4, no. 2 (April 2015): 1–14. http://dx.doi.org/10.4018/ijwnbt.2015040101.

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The WSNs replace the medium of communication from wired to wireless in industrial environment. This offer several advantages that includes easy and fast installation, low-cost maintenance and energy saving. In industrial monitoring and control application, the sensory measures should be delivered to control center in predefined deadline time, so the necessary actions may timely initiated. The geographical routing as reactive routing protocol plays a massive role for real-time packet delivery. The proposed routing protocol follows path discovery on demand basis to reduce the path discovery overhead. Moreover, the routing protocol follows weighted forwarding node selection process. This selects the shorter path over speedy reliable links for smaller deadline time and distributes the traffic over energy efficient node for larger deadline time. Through simulation, the authors demonstrate, compared to existing routing protocol the proposed routing protocol improves the packet delivery ratio along with enhanced network life while maintaining the high energy efficiency and low delivery latency.

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Puype, Bart, Willem Vereecken, Didier Colle, Mario Pickavet, and Piet Demeester. "Multilayer traffic engineering for energy efficiency." Photonic Network Communications 21, no. 2 (September 10, 2010): 127–40. http://dx.doi.org/10.1007/s11107-010-0287-6.

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Cherbal, Sarra, Abdellah Boukerram, and Abdelhak Boubetra. "Locality-Awareness and Replication for an Adaptive CHORD to MANet." International Journal of Distributed Systems and Technologies 8, no. 3 (July 2017): 1–24. http://dx.doi.org/10.4018/ijdst.2017070101.

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Structured peer-to-peer (P2P) systems have shown over time a high performance to P2P users. They are typically applied on Internet and wired networks. On the other hand, the evolution of mobile devices and the popularity of infrastructure-less wireless networks as mobile ad-hoc networks (MANET), make of them an interesting underlay for P2P overlays. However, their energy consumption stills a critical element with limited-energy batteries, and the most principal cause of energy consumption is the immense overhead. The aim of this work is to apply the Chord protocol on MANET underlay, in order to benefit from the efficient content-sharing process and the infrastructure-less mobility. At the same time, this work aims to conserve a good level of energy consumption and network lifetime. Therefore, it proposes a novel mechanism of locality awareness and replication of data that attempts to improve the lookup efficiency and reduce the traffic overhead.

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Jiang, Ding De, Wen Juan Wang, Wei Han Zhang, Peng Zhang, and Ya Li. "Qos Constraints-Based Energy-Efficient Model for IP Networks." Advanced Materials Research 765-767 (September 2013): 1747–51. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1747.

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This paper proposes an energy-efficient model to overcome the energy-efficient problem in large-scale IP networks, based on QoS constraints. To characterize network energy consumption, we present a link energy consumption model based on the sleep and speed scaling mechanisms. If there is no traffic on a link, let it sleep, or activate it and divide its energy consumption into base energy consumption and traffic energy consumption. And then according to the link energy consumption model, we can build our energy-efficient model to improve the network energy efficiency. Finally, simulation results show that our model can significantly improve the network energy efficiency.

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Zhang, Di, Zhenyu Zhou, Zhengyu Zhu, and Shahid Mumtaz. "Energy Efficiency Analysis of ICN Assisted 5G IoT System." Wireless Communications and Mobile Computing 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/6579467.

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Other than separately investing the energy efficiency (EE) merits of information-centric networking’s (ICN’s) caching and sharing (CS) mechanism in wireless communications, here we comprehensively compare the EE performances of ICN’s CS mechanism in different scenarios. A modified system model is first proposed while introducing the CS mechanism into the in-network router, base station (BS), and neighboring user sides. Afterwards, the system achievable sum rate as well as the power consumptions in wireless and wired sections is investigated. The EE performances of different scenarios are finally obtained by dividing the achievable sum rate by the consumed power. While comparing the three scenarios, numerical results demonstrate that the optimal place to cache the content is mainly determined by the distance and hub number of the core routers that passed.

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Ray, Shweta. "Intelligent-Driven Green Resource Allocation for Industrial Internet of Things In 5g Heterogeneous Network." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 55–67. http://dx.doi.org/10.22214/ijraset.2022.45161.

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Abstract: Mobile networks' energy consumption is rising in tandem with the volume of traffic and the number of people utilising mobile technology. To maintain the long-term survival of the next generation of mobile networks, there must be an emphasis on energy efficiency. By minimising the network's power consumption and proposing an energy-efficient network architecture, this thesis addresses the issue of increasing 5G and beyond network efficiency. The first component of this thesis focuses on base stations (BSs), the most energy-intensive part of mobile networks. Mobile network providers offer us with a data set that contains information on the amount of traffic on their system. The poor temporal granularity of mobile network traffic data makes it difficult to train ML systems for sleep mode management choices. Bursty arrivals are taken into consideration while generating mobile network traffic statistics.

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Wang, Weiguang, Hui Li, Wenjie Zhang, and Shanlin Wei. "Energy Efficiency for Data Offloading in D2D Cooperative Caching Networks." Wireless Communications and Mobile Computing 2020 (June 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/2730478.

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D2D communication improves the cellular network performance by using proximity-based services between adjacent devices, which considered is an effective way to solve the problem of spectrum scarcity caused by tremendous mobile data traffic. If the cache-enabled users are willing to send the cached file to the requesters, the content delivery traffic can be offloaded through the D2D link. In this paper, we strive to find the maximum energy efficiency of the D2D caching network through the joint optimization of cache policy and content transmit power. Specifically, based on stochastic geometry-aided modeling of the network, we derive the data offloading rate in closed form, which jointly considers the effects of success sensing probability and success transmission probability. According to the data offloading rate, we formulate a joint optimization problem integrating cache policy and transmit power to maximize the system energy efficiency. To solve this problem, we propose two optimization algorithms that the cache policy optimization algorithm based on gradient update and the joint optimization algorithm. The simulation results demonstrate that the joint optimization has twice the superiority in improving the energy efficiency of the D2D caching network compared with other schemes.

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Xiang, Lanhua, Hongbin Chen, and Feng Zhao. "Area Spectral Efficiency and Energy Efficiency Tradeoff in Ultradense Heterogeneous Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/4390197.

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In order to meet the demand of explosive data traffic, ultradense base station (BS) deployment in heterogeneous networks (HetNets) as a key technique in 5G has been proposed. However, with the increment of BSs, the total energy consumption will also increase. So, the energy efficiency (EE) has become a focal point in ultradense HetNets. In this paper, we take the area spectral efficiency (ASE) into consideration and focus on the tradeoff between the ASE and EE in an ultradense HetNet. The distributions of BSs in the two-tier ultradense HetNet are modeled by two independent Poisson point processes (PPPs) and the expressions of ASE and EE are derived by using the stochastic geometry tool. The tradeoff between the ASE and EE is formulated as a constrained optimization problem in which the EE is maximized under the ASE constraint, through optimizing the BS densities. It is difficult to solve the optimization problem analytically, because the closed-form expressions of ASE and EE are not easily obtained. Therefore, simulations are conducted to find optimal BS densities.

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Bou Dargham, Nadine, Abdallah Makhoul, Jacques Bou Abdo, Jacques Demerjian, and Christophe Guyeux. "Efficient Hybrid Emergency Aware MAC Protocol for Wireless Body Sensor Networks." Sensors 18, no. 10 (October 22, 2018): 3572. http://dx.doi.org/10.3390/s18103572.

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In Body Sensor Networks (BSNs), two types of events should be addressed: periodic and emergency events. Traffic rate is usually low during periodic observation, and becomes very high upon emergency. One of the main and challenging requirements of BSNs is to design Medium Access Control (MAC) protocols that guarantee immediate and reliable transmission of data in emergency situations, while maintaining high energy efficiency in non-emergency conditions. In this paper, we propose a new emergency aware hybrid DTDMA/DS-CDMA protocol that can accommodate BSN traffic variations by addressing emergency and periodic traffic requirements. It takes advantage of the high delay efficiency of DS-CDMA in traffic burst, and the high energy efficiency of DTDMA in periodic traffic. The proposed scheme is evaluated in terms of delay, packet drop percentage, and energy consumption. Different OPNET simulations are performed for various number of nodes carrying emergency data, and for various payload sizes. The protocol performance is compared to other existing hybrid protocols. Results show that the proposed scheme outperforms the others in terms of delay and packet drop percentage for different number of nodes carrying emergency data, as well as for different payload sizes. It also offers the highest energy efficiency during periodic observation, while adjusting the energy consumption during emergency by assigning spreading codes only to nodes holding emergency data.

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Sun, Hongguang, Min Sheng, Matthias Wildemeersch, Tony Q. S. Quek, and Jiandong Li. "Traffic Adaptation and Energy Efficiency for Small Cell Networks With Dynamic TDD." IEEE Journal on Selected Areas in Communications 34, no. 12 (December 2016): 3234–51. http://dx.doi.org/10.1109/jsac.2016.2600442.

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Bansal, Sorav, Rajeev Shorey, Rajeev Gupta, and Archan Misra. "Energy Efficiency and Capacity for TCP Traffic in Multi-Hop Wireless Networks." Wireless Networks 12, no. 1 (February 2006): 5–21. http://dx.doi.org/10.1007/s11276-006-6146-9.

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Han, Longzhe, Jia Zhao, Xuecai Bao, Guangming Liu, Yan Liu, and Taras Maksymyuk. "An Adaptive Video Transmission Mechanism over MEC-Based Content-Centric Networks." Wireless Communications and Mobile Computing 2021 (July 16, 2021): 1–10. http://dx.doi.org/10.1155/2021/9968550.

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The rapid growth of video traffic poses serious challenges to the current Internet. Content-Centric Networking (CCN) as a promising candidate has been proposed to reengineer the Internet architecture. The in-network caching and named content communication model of CCN can enhance the video streaming applications and reduce the network workload. Due to the bandwidth-consuming characteristic of video streaming, the aggressive transmission of video data will cause a reduction of overall network efficiency. In this paper, we present an adaptive video transmission mechanism over Mobile Edge Computing- (MEC-) based CCN. The computation and storage resources of the MEC server are utilized to facilitate the video delivery. Our mechanism adopts a scalable video coding scheme to adaptively control transmission rate to cope with the network condition variation. To analyse the equilibrium property of the proposed mechanism, an analytical model is deduced by using network utility function and convex programming. We also take into account the packet loss in wired and wireless links and present a MEC assistant loss recovery algorithm. The experiment results demonstrate the performance improvement of our proposed mechanism.

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Abdullah, Radhwan M., Ayad H. Abdulqader, Dia M. Ali, Ali A. Alwan, and Abedallah Z. Abualkishik. "An improved approach for managing energy efficiency in mobile networks." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (May 1, 2022): 955. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp955-964.

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It is highly expected that soon there will be environmental and economic negative implications from the amount of energy consumed by wireless network devices. Therefore, many researchers have paid attention toward addressing these challenges to investigate the impact of these wireless networks on both environment and the economy. This paper proposes an approach for alternating work among the fifth generation (5G) with Long-Term Evolution (LTE) wireless networks. The idea of the proposed approach relies on turning off specific base stations (BSs) and antennas for the users based on the required quality of service (QoS). Some BSs like 5G networks aim to provide high-speed communications with significant savings in energy consumption during high traffic periods. On the other hand, there is a slow speed with the high consumption of energy in other BSs like LTE networks. Our proposed solution employs the idea of activating some of the BSs networks and changing the number of active antennas that achieves optimal results for the entire area. Doing so lead to a significant reduction in energy consumption when the traffic load is low. The experimental results illustrate that our proposed solution outperforms the most recent approaches by saving a significant amount in power consumption while maintaining a stable service awareness during switching situations.

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Li, Jian, Kaiping Xue, David S. L. Wei, Jianqing Liu, and Yongdong Zhang. "Energy Efficiency and Traffic Offloading Optimization in Integrated Satellite/Terrestrial Radio Access Networks." IEEE Transactions on Wireless Communications 19, no. 4 (April 2020): 2367–81. http://dx.doi.org/10.1109/twc.2020.2964236.

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Habelalmateen, Mohammed I., Ahmed Jamal Ahmed, Ali Hashim Abbas, and Sami Abduljabbar Rashid. "TACRP: Traffic-Aware Clustering-Based Routing Protocol for Vehicular Ad-Hoc Networks." Designs 6, no. 5 (October 2, 2022): 89. http://dx.doi.org/10.3390/designs6050089.

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On account of the highly dynamic topology of vehicular networks, network congestion and energy utilization are greatly increased, which directly affects the performance of VANETs. So, managing traffic and reducing energy consumption in the network becomes a challenging task in such huge mobility-based VANET networks. Thus, in this paper a new traffic and cluster-based network method is introduced, namely, Traffic-Aware Clustering based Routing Protocol (TACRP). The main aim of the approach is to improve traffic management in the network as well as to reduce energy consumption in it. In the constructed network, a Traffic Management Unit (TMU) is introduced to control the entire network traffic with the help of RSUs. Vehicles with similar speed and direction are grouped into a cluster to increase the network stability and help to reduce the energy consumption of the network. The clustering model provides principles associated with vehicles leaving the clusters, joining the clusters, cluster updates and inter-cluster communication, which makes the network more stable and reliable. For instance, in the proposed work the CH selection is based on centralization, weight, distance, and energy calculation. Such network settings facilitate successfully clustering of vehicles on the road. Simulation experimental analysis showed that the proposed TACRP routing protocol achieved better results in terms of energy efficiency, throughput, packet delivery ratio, and end to end delay of the network when compared with earlier methods, such as ECHS and NRHCS.

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Yu, Jie, Fachao Jiang, Weiwei Kong, and Yugong Luo. "A Distributed and Hierarchical Optimal Control Method for Intelligent Connected Vehicles in Multi-Intersection Road Networks." World Electric Vehicle Journal 13, no. 2 (February 4, 2022): 34. http://dx.doi.org/10.3390/wevj13020034.

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Intelligent connected vehicles (ICVs) technologies will bring significant changes to future transportation, and urban intersections will be an important scenario for the application of ICVs. There exists one significant challenge to address for the control of ICVs in unsignalized, multi-intersection road networks, that is, how to realize the comprehensive optimization of traffic efficiency and energy saving. To solve this problem, the distributed and hierarchical optimal control architecture is first established in this paper, consisting of a cloud decision layer and a vehicle control layer. For the cloud decision layer, the distributed model predictive control (DMPC) method is utilized for distributed optimization control of multi-intersection road network systems, to achieve optimization in terms of traffic efficiency. For the vehicle control layer, based on the reference speed optimized from the cloud decision layer, the DMPC method is further utilized for distributed optimal control of each vehicle platoon, to achieve optimization in terms of energy saving. Finally, the comparative simulation tests are carried out based on MATLAB and SUMO. The feasibility and effectiveness of the proposed method were verified, and the improvement of traffic efficiency and energy saving was achieved.

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Dong, Yuan, Lina Pu, Yu Luo, Zheng Peng, Haining Mo, Yun Meng, Yi Zhao, and Yuzhi Zhang. "Receiver-Initiated Handshaking MAC Based on Traffic Estimation for Underwater Sensor Networks ‡." Sensors 18, no. 11 (November 12, 2018): 3895. http://dx.doi.org/10.3390/s18113895.

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In underwater sensor networks (UWSNs), the unique characteristics of acoustic channels have posed great challenges for the design of medium access control (MAC) protocols. The long propagation delay problem has been widely explored in recent literature. However, the long preamble problem with acoustic modems revealed in real experiments brings new challenges to underwater MAC design. The overhead of control messages in handshaking-based protocols becomes significant due to the long preamble in underwater acoustic modems. To address this problem, we advocate the receiver-initiated handshaking method with parallel reservation to improve the handshaking efficiency. Despite some existing works along this direction, the data polling problem is still an open issue. Without knowing the status of senders, the receiver faces two challenges for efficient data polling: when to poll data from the sender and how much data to request. In this paper, we propose a traffic estimation-based receiver-initiated MAC (TERI-MAC) to solve this problem with an adaptive approach. Data polling in TERI-MAC depends on an online approximation of traffic distribution. It estimates the energy efficiency and network latency and starts the data request only when the preferred performance can be achieved. TERI-MAC can achieve a stable energy efficiency with arbitrary network traffic patterns. For traffic estimation, we employ a resampling technique to keep a small computation and memory overhead. The performance of TERI-MAC in terms of energy efficiency, channel utilization, and communication latency is verified in simulations. Our results show that, compared with existing receiver-initiated-based underwater MAC protocols, TERI-MAC can achieve higher energy efficiency at the price of a delay penalty. This confirms the strength of TERI-MAC for delay-tolerant applications.

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Gueguen, Cédric, and Malo Manini. "Dynamic Tradeoff between Energy and Throughput in Wireless 5G Networks." Wireless Communications and Mobile Computing 2018 (September 4, 2018): 1–12. http://dx.doi.org/10.1155/2018/7484786.

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Even though system energy and spectral efficiency are major issues in wireless network, reaching these objectives conjointly seems very difficult and requires the usage of tradeoffs. Moreover, depending on the context, the importance of either varies. In underloaded context, guaranteeing high Quality of Service (QoS) is easily achievable due to large surplus of available radio resources and focus should be put on energy rather than system throughput. On the contrary, in an overloaded context, the lack of available radio resources required that resources allocation algorithms focus on system capacity in order to preserve QoS. Since the major issue of the network is to satisfy users, in this specific case, energy consumption must become lesser important. Many specialized solutions have been proposed that focus either on energy saving or on throughput maximization. They provide high performances, respectively, on their specific network traffic load context, previously described, but are not optimized outside. Other solutions that proposed static tradeoffs provide average performances but can not be fully efficient in all scenarios. In this paper, we propose a Dynamic Tradeoff between energy and throughput efficiency that adapts the scheduler priorities to the network context and particularly to the traffic load. Considering the context, the scheduler is able to adjust its behavior in order to maintain high QoS while reducing as much energy as possible. Performance evaluation will show that the proposed solution succeeds to minimize energy consumption better than energy focused scheduler in underloaded context while being able to reach the same spectral efficiency as throughput oriented scheduler in highly loaded context.

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Pradeep, S., Yogesh Kumar Sharma, Chaman Verma, Surjeet Dalal, and Cvpr Prasad. "Energy Efficient Routing Protocol in Novel Schemes for Performance Evaluation." Applied System Innovation 5, no. 5 (October 13, 2022): 101. http://dx.doi.org/10.3390/asi5050101.

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Wireless sensor networks (WSNs) are a comparatively new revolutionary technology that has the potential to revolutionize how we live together with the present system. To enhance data archiving, WSNs are frequently used in scientific studies. Many applications have proved the value of wired sensors; however, they are prone to wire cutting or damage. While preventing wire tangles and damage, wireless sensor networks provide autonomous monitoring. The WS network suffers from a number of fundamental restrictions, including insufficient processing power, storage space, available bandwidth, and information exchange. Consequently, energy-efficient strategies are necessary for maximizing the performance and lifespan of WSNs. As a result, the special cluster head relay node and energy balancing techniques will be applied to deal with WSN energy consumptions. This extends the life of the network. In wireless sensor networks, clustering is a smart approach to reduce energy consumption. Energy scarcity and consumption are serious issues that must be addressed with effective and dependable solutions. The proposed MGSA considers the distance between each node and its corresponding CHs, as well as the residual energy and delay, as important factors in the relay node selection. The proposed approach outperforms the current methods, such as low-energy adaptive clustering hierarchy, LEACH (in terms of data delivery rate), energy efficiency, and network longevity. The next level, which will boost the efficiency of wireless sensor networks, with two fitness functions, is proposed. The cluster head (CH) is in charge of collecting and transmitting data from all other cluster nodes. The flow of the consistency of the cluster head selection process will beat the improved data delivery rate, energy efficiency, recommended fuzzy clustering performance experiments, and assessments. As a result, energy-efficient operations are necessary to maximize the WSN performance and lifespan.

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Wang, Weiguang, Hui Li, Yang Liu, Wei Cheng, and Haoyang Qin. "Caching deployment based on energy efficiency in device-to-device cooperative networks." International Journal of Distributed Sensor Networks 16, no. 12 (December 2020): 155014772098465. http://dx.doi.org/10.1177/1550147720984659.

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The rapid growth of mobile data traffic demand will cause congestion to the future communication network. The cache-enabled device-to-device communication has been proven to effectively enhance the performance of wireless communication networks. This article investigates the caching deployment problem from the energy efficiency in the cache-enabled device-to-device networks. According to the random geometry theory modeling, the closed form expression of energy efficiency is derived, which measures the average number of successful transmitted file bits per unit time and per unit power consumption. And then we establish an optimization problem to maximize energy efficiency. As the formulated optimization problem is a multiple-ratio fractional programming problem that cannot be solved conveniently, we propose a quadratic transformation method to nest in the energy efficiency maximization problem. To tackle this problem, an iterative optimization algorithm is proposed to optimize the caching policy and network energy efficiency. The simulation results demonstrate that the proposed policy can achieve higher energy efficiency and hit probability in the cache-enabled device-to-device network.

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Kim, Kyung Tae, and Hee Yong Youn. "An Energy-Efficient MAC Protocol Employing Dynamic Threshold for Wireless Sensor Networks." International Journal of Distributed Sensor Networks 8, no. 10 (October 1, 2012): 304329. http://dx.doi.org/10.1155/2012/304329.

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Energy efficiency is a critical issue for sensor network since the network lifetime depends on efficient management of the energy resource of sensor nodes. Particularly, designing energy efficient MAC protocol has a significant influence on the performance of wireless sensor network with regards to the energy. The existing MAC protocols developed for sensor network try to avoid energy waste during idle listening time by controlling the duty cycle of the transmission period. Since the traffic conditions are diverse, they may not always display improvements in energy consumption. In this paper we propose a new energy efficient MAC protocol called dynamic threshold MAC (DT-MAC), which employs a dynamic threshold for the buffer of each sensor node to maximize the energy efficiency regardless of specific network traffic condition. Here the packets are stored in the buffer, and then transmitted when the number of packets in the buffer exceeds the threshold dynamically decided according to the number of hops of the node from the source in the path of packet forwarding. The simulation results using OMNnet++ show that DT-MAC enables significant improvement in energy consumption compared to the existing MAC protocols. The proposed DT-MAC protocol also reduces the number of transmissions of control packets.

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Musovic, Jasmin, Vlatko Lipovac, and Adriana Lipovac. "Stochastic Geometry-Based Analysis of Heterogeneous Wireless Network Spectral, Energy and Deployment Efficiency." Electronics 10, no. 7 (March 26, 2021): 786. http://dx.doi.org/10.3390/electronics10070786.

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For quite a while, it has been evident that homogeneous network architectures, based on cells with a uniform radiation pattern, cannot fulfill the ever increasing demand of mobile users for capacity and service quality while still preserving spectrum and energy. However, only with the introduction of the Fourth Generation mobile communication networks to deal with the surging data traffic of multimedia applications, have smaller cells been widely used to break down service zone areas of macro base stations into multiple tiers, thus improving network performance, reducing traffic congestion, and enabling better management of spectrum and energy consumption in a macro network. In this paper, we present an analytical model for assessing the efficiency of bandwidth and energy usage, as well as of network deployment, taking into account overall network investment and maintenance costs. This paves the way to the improved planning of network coverage, and its capacity and reliability, thus preserving its spectrum and energy, as well as the environment. The analysis considers the downlink of an arbitrary heterogeneous cellular network by using tools of stochastic geometry that adopt the distribution of base stations in the form of a Poisson Point Process. The proposed analytical model is verified by the according software simulations using the ns-3 network simulator. The obtained results closely match the theoretically predicted values and boundaries, clearly indicating that, in all three analyzed aspects: spectral, energy, and deploymental, the efficiency of small-cell networks was higher with respect to traditional large-cell networks and increased even further for heterogeneous (two-tier in our tests) networks.

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Lee, Sangwoo, and Sunwoo Kim. "Guest Editorial: Special Issue on Designs and Algorithms of Localization in Vehicular Networks." Energies 15, no. 6 (March 18, 2022): 2223. http://dx.doi.org/10.3390/en15062223.

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We have been witnessing a paradigm shift in road transport systems over the last few years with the advent of autonomous vehicles and emerging road applications for road safety and traffic efficiency [...]

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Buzura, Sorin, Bogdan Iancu, Vasile Dadarlat, Adrian Peculea, and Emil Cebuc. "Optimizations for Energy Efficiency in Software-Defined Wireless Sensor Networks." Sensors 20, no. 17 (August 24, 2020): 4779. http://dx.doi.org/10.3390/s20174779.

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Software-defined wireless sensor networking (SDWSN) is an emerging networking architecture which is envisioned to become the main enabler for the internet of things (IoT). In this architecture, the sensors plane is managed by a control plane. With this separation, the network management is facilitated, and performance is improved in dynamic environments. One of the main issues a sensor environment is facing is the limited lifetime of network devices influenced by high levels of energy consumption. The current work proposes a system design which aims to improve the energy efficiency in an SDWSN by combining the concepts of content awareness and adaptive data broadcast. The purpose is to increase the sensors’ lifespan by reducing the number of generated data packets in the resource-constrained sensors plane of the network. The system has a distributed management approach, with content awareness being implemented at the individual programmable sensor level and the adaptive data broadcast being performed in the control plane. Several simulations were run on historical weather and the results show a significant decrease in network traffic. Compared to similar work in this area which focuses on improving energy efficiency with complex algorithms for routing, clustering, or caching, the current proposal employs simple computing procedures on each network device with a high impact on the overall network performance.

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Majeed, Uzma, Aqdas Naveed Malik, Nasim Abbas, and Waseem Abbass. "An Energy-Efficient Distributed Congestion Control Protocol for Wireless Multimedia Sensor Networks." Electronics 11, no. 20 (October 11, 2022): 3265. http://dx.doi.org/10.3390/electronics11203265.

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Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network surpasses the available capacity. This article presents an energy-efficient distributed congestion control protocol (DCCP) to mitigate congestion and improve end-to-end delay. Compared to the other protocols, the DCCP protocol proposed in this article can alleviate congestion by intelligently selecting the best path. First, congestion is detected by using two congestion indicators. Second, each node aggregates the received data and builds a traffic congestion map. The traffic congestion map is used to calculate the best path. Therefore, the traffic is balanced on different routes, which reduces the end-to-end delay. Finally, a rate controller is designed to prevent congestion in the network by sending a congestion notification message to a source node. After receiving a congestion notification message, the source node immediately adjusts its transmission rate. Experimental results based on raspberry pi sensor nodes show that the proposed DCCP protocol significantly improves network performance and is superior to existing modern congestion control protocols.

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Min, Haitao, Xiaoyong Xiong, Fang Yang, Weiyi Sun, Yuanbin Yu, and Pengyu Wang. "An Energy-Efficient Driving Method for Connected and Automated Vehicles Based on Reinforcement Learning." Machines 11, no. 2 (January 26, 2023): 168. http://dx.doi.org/10.3390/machines11020168.

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The development of connected and automated vehicles (CAV) technology not only helps to reduce traffic accidents and improve traffic efficiency, but also has significant potential for energy saving and emission reduction. Using the dynamic traffic flow information around the vehicle to optimize the vehicle trajectory is conducive to improving the energy efficiency of the vehicle. Therefore, an energy-efficient driving method for CAVs based on reinforcement learning is proposed in this paper. Firstly, a set of vehicle trajectory prediction models based on long and short-term memory (LSTM) neural networks are developed, which integrate driving intention prediction and lane change time prediction to improve the prediction accuracy of surrounding vehicle trajectories. Secondly, an energy-efficient driving model is built based on Proximity Policy Optimization (PPO) reinforcement learning. The model takes the current states and predicted trajectories of surrounding vehicles as input information, and outputs energy-saving control variables while taking into account various constraints, such as safety, comfort, and travel efficiency. Finally, the method is tested by simulation on the NGSIM dataset, and the results show that the proposed method can save energy consumption by 9–22%.

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Śmieszek, Miroslaw, Nataliia Kostian, Vasyl Mateichyk, Jakub Mościszewski, and Liudmyla Tarandushka. "Determination of the Model Basis for Assessing the Vehicle Energy Efficiency in Urban Traffic." Energies 14, no. 24 (December 17, 2021): 8538. http://dx.doi.org/10.3390/en14248538.

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The paper studies the problem of assessing the vehicle energy efficiency on the streets of urban road network. As a result of morphological analysis of the system “Vehicle—Traffic flow—Road—Traffic Environment” 18 significant morphological attributes of its functional elements, that affect the energy efficiency of vehicles, were identified. Each attribute is characterized by 3–6 implementation variants, which are evaluated by the relevant quantitative or qualitative parameters. The energy efficiency of vehicles is determined by the criteria of their energy consumption considering the vehicle category, type of energy unit, mode of vehicle movement and adjustment factors—road, climatic and others. The input parameters values of the system in the process of traffic flow on the linear fragments of streets and road networks of the cities of Ukraine and Poland were measured. The set of independent system parameters is determined by applying the Farrar-Glober method based on statistical estimates. The specified set is the basis of the studied system and is formed of 10 independent input parameters. The presence in the basis of parameters that correspond to the morphological features of all four functional elements, confirmed the importance of these elements of the system. The mathematical dependence of the impact of vehicle characteristics, traffic flow, road and environment on vehicle energy efficiency is built. The standard deviation of the model values from the tabular ones equals σ´=0.0091. Relative standard deviation equals S´r=1.5%. The results of the study could be used in the development of new and optimization of existing intelligent traffic control systems of urban transport.

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Więcek, Dariusz, Igor Michalski, Krzysztof Rzeźniczak, and Dariusz Wypiór. "Multi-RAT Orchestration Method for Heterogeneous Wireless Networks." Applied Sciences 11, no. 18 (September 7, 2021): 8281. http://dx.doi.org/10.3390/app11188281.

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Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces network indicators, it is possible to decrease the user mobile terminal energy consumption, keeping traffic speed at an adequate level. The solution discussed was implemented in an experimental testbed with Software Defined Radio transmission systems. Downlink and uplink data links were toggled among different RATs according to the decisions that were taken by the end-to-end multi-RAT orchestrator based on the received proper network traffic-related indicators. The authors focused on finding an adequate algorithm that allowed for reduced power usage in the user terminal and made the attempt to verify how to reach the power reduction without introducing RAT-specific rules. The results showed that the proposed orchestration EE reduction was observed (from 11% to 42% for two different scenarios) in relation to the single LTE network deployment. The orchestration compared to the Wi-Fi network does not provide EE gain (−7% and 0%, respectively), but allows the user to achieve a higher data rate (23% and 39% gain, respectively), thus keeping the energy efficiency at almost the same level.

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Chen, Xianfu, Jinsong Wu, Yueming Cai, Honggang Zhang, and Tao Chen. "Energy-Efficiency Oriented Traffic Offloading in Wireless Networks: A Brief Survey and a Learning Approach for Heterogeneous Cellular Networks." IEEE Journal on Selected Areas in Communications 33, no. 4 (April 2015): 627–40. http://dx.doi.org/10.1109/jsac.2015.2393496.

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Gu, Rentao, Gang Wang, Zhekang Li, and Yuefeng Ji. "Energy and Transmission Efficiency Enhancement in Passive Optical Network Enabled Reconfigurable Fronthaul Supporting Smart Homes." Sensors 20, no. 21 (November 2, 2020): 6245. http://dx.doi.org/10.3390/s20216245.

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Smart home technologies are growing actively all around the world. As a result, great pressures are imposed on internet of things networks by dynamic traffic and plenty of devices. The passive optical network is considered one of the most promising fronthaul technologies. In particular, the time and wavelength division multiplexing passive optical network has shown the advantage of high capacity and received attention recently. In support of internet of things networks, the energy and transmission efficiency has emerged as an important issue on the time and wavelength division multiplexing passive optical network enabled fronthaul networks. In this paper, we try to enhance the energy and transmission efficiency of the time and wavelength division multiplexing passive optical network enabled reconfigurable fronthaul. Fronthaul links’ load balancing is also taken into consideration. An integer non-linear programming model is employed to formulate the joint optimization problem. We also provide an adaptive genetic algorithm-based approach with fast convergence. The simulation results show that the active units of fronthaul can be dynamically switched on/off with the traffic variation and a significant energy saving is achieved. In addition, the maximum transmission efficiency increases by 87% with integer non-linear programming method in off-peak periods.

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Zeng, Jun, Hao Wang, and Wei Luo. "Self-Optimizing Traffic Steering for 5G mmWave Heterogeneous Networks." Sensors 22, no. 19 (September 20, 2022): 7112. http://dx.doi.org/10.3390/s22197112.

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Driven by growing mobile traffic, millimeter wave (mmWave) communications have recently been developed to enhance wireless network capacity. Due to insufficient coverage and the lack of support for mobility, mmWave is often deployed in the ultra-dense small cells of the 5G heterogeneous network. In this article, we first summarize the characteristics of the 5G heterogeneous network from the viewpoints of devices, spectra, and networks. We then propose a triple-band network structure which incorporates licensed bands, sub-6GHz unlicensed bands, and mmWave bands to support various types of mobile users. Based on the novel network structure, we further propose a self-optimizing traffic steering strategy which can intelligently steer traffic to specific networks and spectra according to the dynamic network and traffic environments. Several use cases are also discussed to facilitate the implementation of our proposals. Finally, we present numerical results to demonstrate that the proposed network structure and strategy can effectively enhance the system throughput and energy efficiency.

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Park, Hyebin, and Yujin Lim. "Deep Reinforcement Learning Based Resource Allocation with Radio Remote Head Grouping and Vehicle Clustering in 5G Vehicular Networks." Electronics 10, no. 23 (December 2, 2021): 3015. http://dx.doi.org/10.3390/electronics10233015.

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With increasing data traffic requirements in vehicular networks, vehicle-to-everything (V2X) communication has become imperative in improving road safety to guarantee reliable and low latency services. However, V2X communication is highly affected by interference when changing channel states in a high mobility environment in vehicular networks. For optimal interference management in high mobility environments, it is necessary to apply deep reinforcement learning (DRL) to allocate communication resources. In addition, to improve system capacity and reduce system energy consumption from the traffic overheads of periodic messages, a vehicle clustering technique is required. In this paper, a DRL based resource allocation method is proposed with remote radio head grouping and vehicle clustering to maximize system energy efficiency while considering quality of service and reliability. The proposed algorithm is compared with three existing algorithms in terms of performance through simulations, in each case outperforming the existing algorithms in terms of average signal to interference noise ratio, achievable data rate, and system energy efficiency.

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Oborkhale, L. I., C. C. Nwaogu, and O. A. Amadi. "Achieving energy efficiency for 5G at base stations level." Scientia Africana 20, no. 3 (January 26, 2022): 1–10. http://dx.doi.org/10.4314/sa.v20i3.1.

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As the era of 5th Generation (5G) networks is dawning, several pertinent issues associated with the improvements that have to be achieved in future communications are attracting increasing research attention. This work, considered achieving energy efficiency for 5G at base stations level. Energy efficiency simply means using less energy to perform the same task thereby, eliminating energy waste. The objective of this paper is to examine the ways of deploying energy efficient hardware at the base stations in order to make the base stations more green energy based. Considering the current energy concerns, base stations in emerging wireless networks range from low-energy BSS to high-energy BSS with entirely different constraints in either case. In view of these extremes, this paper examines the major components behind energy-efficient wireless communication network design during the peak and off-peak traffic periods. It was discovered that the Power amplifier consumes up to 59% of the energy at the base stations. Improving a Power amplifier by bringing linearity could improve the efficiency of the BS and hence reduce the energy crunch at the BS level from 59% to 51%.

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Chochliouros, Ioannis P., Michail-Alexandros Kourtis, Anastasia S. Spiliopoulou, Pavlos Lazaridis, Zaharias Zaharis, Charilaos Zarakovitis, and Anastasios Kourtis. "Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures." Energies 14, no. 17 (August 30, 2021): 5392. http://dx.doi.org/10.3390/en14175392.

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Energy efficiency is a huge opportunity for both the developed and the developing world, and ICT will be the key enabler towards realising this challenge, in a huge variety of ways across the full range of industries. In the telecommunications space in particular, power consumption and the resulting energy-related pollution are becoming major operational and economical concerns. The exponential increases in network traffic and the number of connected devices both make energy efficiency an increasingly important concern for the mobile networks of the (near) future. More specifically, as 5G is being deployed at a time when energy efficiency appears as a significant matter for the network ability to take into account and to serve societal and environmental issues, this can play a major role in helping industries to achieve sustainability goals. Within this scope, energy efficiency has recently gained its own role as a performance measure and design constraint for 5G communication networks and this has identified new challenges for the future. In particular, the inclusion of AI/ML techniques will further enhance 5G’s capabilities to achieve lower power consumption and, most importantly, dynamic adaption of the network elements to any sort of energy requirements, to ensure effective functioning.

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Shweta, Patil, Leena Bojaraj, Pallavi Biradar, Mohammed Bakhar, and Alazar Yeshitla. "A Power Efficiency Wireless Communication Networks by Early Detection of Wrong Decision Probability in Handover Traffic." Wireless Communications and Mobile Computing 2022 (February 18, 2022): 1–7. http://dx.doi.org/10.1155/2022/4612604.

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This paper highlights the energy consumption due to handovers in wireless communication system. Ever-increasing demand for higher data rate for users of cellular networks and the energy consumption that results from the effective satisfaction of these demands leads to greater consumption of energy from such energy sources that depend on burning of greenhouse gas emitting fossil fuels for energy production. An evolved Node B or e-NB inside, as in equipment handling the radio frequencies, can be divided into two large categories (1) BaseBand Unit (2) Remote Radio Head or RRH. For the purpose of our current work, we will focus on mainly the Remote Radio Head part. A simple picturization of the evolved Node B and the User Equipment (UE) that are included in the power model has been discussed. The proposed framework for mobility management/security gateway protocol including wrong decision probability of handover evaluation following measurements’ procedure has been designed successfully. We have compared to other UL/UE power consumption. The lowest ISD has the largest power usage in resultant output.

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Awan, Khalid M., Nadeem Ashraf, Muhammad Qaiser Saleem, Osama E. Sheta, Kashif Naseer Qureshi, Asim Zeb, Khalid Haseeb, and Ali Safaa Sadiq. "A priority-based congestion-avoidance routing protocol using IoT-based heterogeneous medical sensors for energy efficiency in healthcare wireless body area networks." International Journal of Distributed Sensor Networks 15, no. 6 (June 2019): 155014771985398. http://dx.doi.org/10.1177/1550147719853980.

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A wireless body area network is a collection of Internet of Things–based wearable heterogeneous computing devices primarily used in healthcare monitoring applications. A lot of research is in process to reduce the cost and increase efficiency in medical industry. Low power sensor nodes are often attached to high-risk patients for real-time remote monitoring. These sensors have limited resources such as storage capacity, battery life, computational power, and channel bandwidth. The current work proposes a multi-hop Priority-based Congestion-avoidance Routing Protocol using IoT based heterogeneous sensors for energy efficiency in wireless body area networks. The objective is to devise a routing protocol among sensor nodes such that it has minimum delay and higher throughput for emergency packets using IoT based sensor nodes, optimal energy consumption for longer network lifetime, and efficient scarce resource utilization. In our proposed work, data traffic is categorized into normal and emergency or life-critical data. For normal data traffic, next-hop selection will be selected based upon three parameters; residual energy, congestion on forwarder node, and signal-to-noise ratio of the path between source and forwarder node. We use the data aggregation and filtration technique to reduce the network traffic load and energy consumption. A priority-based routing scheme is also proposed for life-critical data to have less delay and greater throughput in emergency situations. Performance of the proposed protocol is evaluated with two cutting-edge routing techniques iM-SIMPLE and Optimized Cost Effective and Energy Efficient Routing. The proposed model outperforms in terms of network throughput, traffic load, energy consumption, and lifespan.

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Amirgholy, Mahyar, and H. Oliver Gao. "Optimal traffic operation for maximum energy efficiency in signal-free urban networks: A macroscopic analytical approach." Applied Energy 329 (January 2023): 120128. http://dx.doi.org/10.1016/j.apenergy.2022.120128.

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Vu, Quy Khanh, and Ngoc Anh Le. "An Energy-Efficient Routing Protocol for MANET in Internet of Things Environment." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 07 (July 2, 2021): 88. http://dx.doi.org/10.3991/ijoe.v17i07.23273.

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MANET-IoT networks are currently being focus developed and expected to become popular in next-generation mobile networks due to their simplicity and efficiency in solving real problems in a wide range of areas such as smart agriculture, smart health care, intelligent traffic, military, entertainment, and smart cities. Because of the nature of mobile network nodes, saving energy for MANET is always a complicated problem. In this paper, we proposed a saving energy routing protocol that uses an integrated routing metric from hops number and remaining energy metrics for decision-making to selects a fit route. Besides, we evaluate the performance of the proposed protocol on NS2 simulation software. Simulation results demonstrated the proposed protocol improves the network lifetime and network performance parameters compared to traditional protocols.

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Wu, Liangshun, and Hengjin Cai. "Energy-Efficient Adaptive Sensing Scheduling in Wireless Sensor Networks Using Fibonacci Tree Optimization Algorithm." Sensors 21, no. 15 (July 23, 2021): 5002. http://dx.doi.org/10.3390/s21155002.

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Wireless sensor networks are appealing, largely because they do not need wired infrastructure, but it is precisely this feature that renders them energy-constrained. The duty cycle scheduling is perceived as a contributor to the energy efficiency of sensing. This paper developed a novel paradigm for modeling wireless sensor networks; in this context, an adaptive sensing scheduling strategy is proposed depending on event occurrence behavior, and the scheduling problem is framed as an optimization problem. The optimization objectives include reducing energy depletion and optimizing detection accuracy. We determine the explicit form of the objective function by numerical fitting and found that the objective function aggregated by the fitting functions is a bivariate multimodal function that favors the Fibonacci tree optimization algorithm. Then, with the optimal parameters optimized by the Fibonacci tree optimization algorithm, the scheduling scheme can be easily deployed, and it behaves consistently in the coming hours. The proposed “Fibonacci Tree Optimization Strategy” (“FTOS”) outperforms lightweight deployment-aware scheduling (LDAS), balanced-energy scheduling (BS), distributed self-spreading algorithm (DSS) and probing environment and collaborating adaptive sleeping (PECAS) in achieving the aforementioned scheduling objectives. The Fibonacci tree optimization algorithm has attained a better optimistic effect than the artificial bee colony (ABC) algorithm, differential evolution (DE) algorithm, genetic algorithm (GA) algorithm, particle swarm optimization (PSO) algorithm, and comprehensive learning particle swarm optimization (CLPSO) algorithm in multiple runs.

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Jaffri, Zain ul Abidin, Muhammad Asif, Wali Ullah Khan, Zeeshan Ahmad, Zain ul Abiden Akhtar, Kalim Ullah, and Md Sadek Ali. "TEZEM: A new energy-efficient routing protocol for next-generation wireless sensor networks." International Journal of Distributed Sensor Networks 18, no. 6 (June 2022): 155013292211072. http://dx.doi.org/10.1177/15501329221107246.

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The design and implementation of energy-efficient routing protocols for next-generation wireless sensor networks is always a challenge due to limited power resource capabilities. Hierarchical (clustering) routing protocols appeared to be a remarkable solution for extending the lifetime of wireless sensor networks, particularly in application-aware (threshold-sensitive) and heterogeneity-aware cluster-based routing protocols. In this article, we propose a protocol, namely, Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol. It is a heterogeneity-aware and threshold-based protocol that provides a better solution to existing problems in next-generation wireless sensor networks. During execution, the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol splits the entire network area into several zones to manage network traffic efficiently. In the first step, Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol is designed for a homogeneous network where the initial energy of all the nodes is the same. Thereafter, we bring in heterogeneity in the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol execution environment to optimize its energy consumption. By investigating the performance of the various numbers of divisions, it is proved that the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol with 9 zonal divisions has higher stability and throughput. The performance of the proposed Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol is compared with those of Stable Election Protocol, Low-Energy Adaptive Clustering Hierarchy, Modified Low-Energy Adaptive Clustering Hierarchy, and Gateway-Based Energy-Efficient Routing Protocol through computer simulations. Simulation results verify the improved performance of the proposed Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol in terms of network stability, lifetime, and throughput.

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Peng, Cong, Yuanzhi He, Shanghong Zhao, Yongjun Li, Xiang Wang, and Boyu Deng. "Energy efficiency optimization for uplink traffic offloading in the integrated satellite-terrestrial network." Wireless Networks 28, no. 3 (February 10, 2022): 1147–61. http://dx.doi.org/10.1007/s11276-022-02895-0.

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Murugan, K., and S. Shanmugavel. "Delay and traffic based on-demand routing algorithms for improving energy efficiency in mobile ad hoc networks." International Journal of Wireless and Mobile Computing 2, no. 4 (2007): 362. http://dx.doi.org/10.1504/ijwmc.2007.016728.

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Kannan, Srihari, Gaurav Dhiman, Yuvaraj Natarajan, Ashutosh Sharma, Sachi Nandan Mohanty, Mukesh Soni, Udayakumar Easwaran, Hamidreza Ghorbani, Alia Asheralieva, and Mehdi Gheisari. "Ubiquitous Vehicular Ad-Hoc Network Computing Using Deep Neural Network with IoT-Based Bat Agents for Traffic Management." Electronics 10, no. 7 (March 26, 2021): 785. http://dx.doi.org/10.3390/electronics10070785.

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In this paper, Deep Neural Networks (DNN) with Bat Algorithms (BA) offer a dynamic form of traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles across highly congested paths to enhance efficiency, with a lower average latency. The latter is combined with the Internet of Things (IoT) and it moves across the VANETs to analyze the traffic congestion status between the network nodes. The experimental analysis tests the effectiveness of DNN-IoT-BA in various machine or deep learning algorithms in VANETs. DNN-IoT-BA is validated through various network metrics, like packet delivery ratio, latency and packet error rate. The simulation results show that the proposed method provides lower energy consumption and latency than conventional methods to support real-time traffic conditions.

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Habib, Md Arafat, and Sangman Moh. "Robust Evolutionary-Game-Based Routing for Wireless Multimedia Sensor Networks." Sensors 19, no. 16 (August 14, 2019): 3544. http://dx.doi.org/10.3390/s19163544.

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Nowadays, wireless multimedia sensor networks (WMSNs) are used in various applications. An energy-efficient and robust routing protocol is essential for WMSNs because the quality of service is important for traffic-intensive multimedia data, such as images and videos. A WMSN with multiple sinks allows cluster heads (CHs) to deliver the collected data to the nearest sink, thereby mitigating the delivery overhead. In this study, we propose a novel evolutionary-game-based routing (EGR) protocol for WMSNs with multiple sinks, in which the evolutionary game theory is exploited for selecting CHs. In EGR, an algorithm to mitigate data redundancy, based on the overlapping field of views of the multimedia sensor nodes, is also presented. This algorithm decreases the number of redundant transmissions, thereby increasing energy efficiency and network performance. According to the performance evaluation results of this study, the proposed EGR significantly outperforms the state-of-art protocols in terms of energy efficiency, end-to-end delay, packet delivery ratio, cluster formation time, and network lifetime.

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Ji, Jiequ, Kun Zhu, Ran Wang, Bing Chen, and Chen Dai. "Energy Efficient Caching in Backhaul-Aware Cellular Networks with Dynamic Content Popularity." Wireless Communications and Mobile Computing 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/7532049.

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Caching popular contents at base stations (BSs) has been regarded as an effective approach to alleviate the backhaul load and to improve the quality of service. To meet the explosive data traffic demand and to save energy consumption, energy efficiency (EE) has become an extremely important performance index for the 5th generation (5G) cellular networks. In general, there are two ways for improving the EE for caching, that is, improving the cache-hit rate and optimizing the cache size. In this work, we investigate the energy efficient caching problem in backhaul-aware cellular networks jointly considering these two approaches. Note that most existing works are based on the assumption that the content catalog and popularity are static. However, in practice, content popularity is dynamic. To timely estimate the dynamic content popularity, we propose a method based on shot noise model (SNM). Then we propose a distributed caching policy to improve the cache-hit rate in such a dynamic environment. Furthermore, we analyze the tradeoff between energy efficiency and cache capacity for which an optimization is formulated. We prove its convexity and derive a closed-form optimal cache capacity for maximizing the EE. Simulation results validate the proposed scheme and show that EE can be improved with appropriate choice of cache capacity.

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Journal articles on the topic 'Energy efficiency, traffic engineering, wired networks'

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