Готові списки джерел за темами / Energy Packet

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Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Energy Packet"

1

Aguilar, Sergio, Antonis Platis, Rafael Vidal, and Carles Gomez. "Energy Consumption Model of SCHC Packet Fragmentation over Sigfox LPWAN." Sensors 22, no. 6 (March 9, 2022): 2120. http://dx.doi.org/10.3390/s22062120.

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Анотація:
The Internet Engineering Task Force (IETF) has standardized a new framework, called Static Context Header Compression and fragmentation (SCHC), which offers adaptation layer functionality designed to support IPv6 over Low Power Wide Area Networks (LPWANs). The IETF is currently profiling SCHC, and in particular its packet fragmentation and reassembly functionality, for its optimal use over certain LPWAN technologies. Considering the energy constraints of LPWAN devices, it is crucial to determine the energy performance of SCHC packet transfer. In this paper, we present a current and energy consumption model of SCHC packet transfer over Sigfox, a flagship LPWAN technology. The model, which is based on real hardware measurements, allows to determine the impact of several parameters and fragment transmission strategies on the energy performance of SCHC packet transfer over Sigfox. Among other results, we have found that the lifetime of a device powered by a 2000 mAh battery, transmitting packets every 5 days, is 168 days for 2250-byte packets, while it increases to 1464 days for 77-byte packets.
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2

Doncel, Josu. "Age of information of a server with energy requirements." PeerJ Computer Science 7 (March 1, 2021): e354. http://dx.doi.org/10.7717/peerj-cs.354.

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Анотація:
We investigate a system with Poisson arrivals to two queues. One queue stores the status updates of the process of interest (or data packets) and the other handles the energy that is required to deliver the updates to the monitor. We consider that the energy is represented by packets of discrete unit. When an update ends service, it is sent to the energy queue and, if the energy queue has one packet, the update is delivered successfully and the energy packet disappears; however, in case the energy queue is empty, the update is lost. Both queues can handle, at most, one packet and the service time of updates is exponentially distributed. Using the Stochastic Hybrid System method, we characterize the average Age of Information of this system. Due to the difficulty of the derived expression, we also explore approximations of the average Age of Information of this system.
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3

Hanji, Bhagyashri R., and Rajashree Shettar. "Cross Layer Solution for Energy and Delay Optimization in MANETs." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4745. http://dx.doi.org/10.11591/ijece.v8i6.pp4745-4754.

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A novel method for packet forwarding in MANETs has been proposed in this paper. A node in the network acts as both host and router. Energy utilization of the node increases as all nodes in MANET operate as source, destination, and router to forward packets to the next hop ultimately to reach destination. Routers execute a variety of functions from simple packet classification for forwarding to complex payload revision. As the number of tasks and complexity increases, processing time required also increases resulting in significant processing delay in routers. The proposed work optimizes packet header at transport and network layer by calculating Unique Identifier using pairing function for the fields which do not change for a source–destination pair. This technique optimizes the processing cost of each packet header thereby conserving energy and reducing delay. It also simplifies the task of system administration. This paper elucidates an extension to basic AODV protocol, allowing routing of most packets without an explicit header, reducing the overhead of the protocol while still conserving its basic properties. The proposed method improves the network performance significantly compared to AODV, MTPR, and S-AODV protocol.
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4

Liang, Guangjun, Qi Zhu, Jianfang Xin, Jiashan Tang, and Tianjiao Zhang. "Performance Analysis of Buffer-Aided Relaying System Based on Data and Energy Coupling Queuing Model for Cooperative Communication Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/9287489.

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Анотація:
We focus on the performance analysis of the buffer-aided relaying system which allows data and energy packets to arrive independently and depart interactively. First, we profile the cooperative relaying system model as a data arrival and energy arrival coupling queuing model. Considering the influence of channel condition on the data departure rate, a new relay transmit protocol which permits exhausting more energy packet to send one data packet in the bad channel environment is proposed. Second, the joint data packet and energy packet handling problem is ascribed to a Coupled Processor Queuing Model which could achieve its steady state transition probability by Quasi-Birth and Death method. Third, the expressions of throughput, delay, and packet drop rate for both data queue and energy queue are also derived. Simulations are demonstrated to verify the analytical results under different data arrival rate, energy arrival rate, and relaying strategy.
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5

Akbar, Shuja, Muhammad Mohsin Mehdi, M. Hasan Jamal, Imran Raza, Syed Asad Hussain, Jose Breñosa, Julio César Martínez Espinosa, Alina Eugenia Pascual Barrera, and Imran Ashraf. "Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring." Healthcare 10, no. 11 (November 17, 2022): 2297. http://dx.doi.org/10.3390/healthcare10112297.

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Анотація:
Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing.
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6

Sabbineni, Harshavardhan, and Krishnendu Chakrabarty. "An Energy-Efficient Data Delivery Scheme for Delay-Sensitive Traffic in Wireless Sensor Networks." International Journal of Distributed Sensor Networks 6, no. 1 (January 1, 2010): 792068. http://dx.doi.org/10.1155/2010/792068.

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Анотація:
We propose a novel data-delivery method for delay-sensitive traffic that significantly reduces the energy consumption in wireless sensor networks without reducing the number of packets that meet end-to-end real-time deadlines. The proposed method, referred to as SensiQoS, leverages the spatial and temporal correlation between the data generated by events in a sensor network and realizes energy savings through application-specific in-network aggregation of the data. SensiQoS maximizes energy savings by adaptively waiting for packets from upstream nodes to perform in-network processing without missing the real-time deadline for the data packets. SensiQoS is a distributed packet scheduling scheme, where nodes make localized decisions on when to schedule a packet for transmission to meet its end-to-end real-time deadline and to which neighbor they should forward the packet to save energy. We also present a localized algorithm for nodes to adapt to network traffic to maximize energy savings in the network. Simulation results show that SensiQoS improves the energy savings in sensor networks where events are sensed by multiple nodes, and spatial and/or temporal correlation exists among the data packets. Energy savings due to SensiQoS increase with increase in the density of the sensor nodes and the size of the sensed events.
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7

Hossain, Md Shakhawat, and M. Tariq Iqbal. "Wind Energy Based Packet Energy System." International Journal of Energy Science 4, no. 4 (2014): 123. http://dx.doi.org/10.14355/ijes.2014.0404.02.

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8

Gelenbe, Erol, and Elif Tugce Ceran. "Energy Packet Networks With Energy Harvesting." IEEE Access 4 (2016): 1321–31. http://dx.doi.org/10.1109/access.2016.2545340.

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9

Yin, Yonghua. "OPTIMUM ENERGY FOR ENERGY PACKET NETWORKS." Probability in the Engineering and Informational Sciences 31, no. 4 (April 9, 2017): 516–39. http://dx.doi.org/10.1017/s0269964817000067.

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Анотація:
The concept of Energy Packet Network (EPN) proposed by Gelenbe, is a new framework for modeling power grids that takes distributed energy generation such as renewable energy sources into consideration, and which contributes to modeling the smart grid. Based on G-network theory, this paper presents a simplified model of EPN and formulates energy-distribution as an optimization problem. We analyze it theoretically, and detail its optimal solutions. In addition to using existing optimization algorithms, a heuristic algorithm is proposed to solve for EPN optimization. The optimal solutions and efficacy of the algorithm are illustrated with numerical experiments. Further, we present an EPN with disconnections and a similar optimization problem is investigated. Optimal solutions are presented, and numerical results using the analytic optimal solutions, random solutions, a cooperative particle swarm optimizer and a heuristic algorithm illustrate the power of different approaches for solving energy-distribution problems using the EPN formalism.
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10

Guo, Qingjie, Fengxu Yang, and Jianming Wei. "Experimental Evaluation of the Packet Reception Performance of LoRa." Sensors 21, no. 4 (February 4, 2021): 1071. http://dx.doi.org/10.3390/s21041071.

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Анотація:
LoRa technology is currently one of the most popular Internet of Things (IoT) technologies. A substantial number of LoRa devices have been applied in a wide variety of real-world scenarios, and developers can adjust the packet reception performance of LoRa through physical layer parameter configuration to meet the requirements. However, since the important details of the relationship between the physical layer parameters and the packet reception performance of LoRa remain unknown, it is a challenge to choose the appropriate parameter configuration to meet the requirements of the scenarios. Moreover, with the increase in application scenarios, the requirements for energy consumption become increasingly high. Therefore, it is also a challenge to know how to configure the parameters to maximize the energy efficiency while maintaining a high data rate. In this work, a complex evaluation experiment on the communication capability under a negative Signal to Noise Ratio is presented, and the specific details of the relationship between physical layer parameters and the packet reception performance of LoRa are clarified. Furthermore, we study the impact of the packet length on the packet reception performance of LoRa, and the experimental results show that when there is a large amount of data to be transmitted, it is better to choose long packets instead of short packets. Finally, considering the influence of physical layer parameters and the packet length on the packet reception performance of LoRa, the optimal parameter combination is explored, so as to propose a transmission scheme with a balanced reliability, delay, and energy consumption. This scheme is the first to consider the physical layer parameters and packet length together to study the communication transmission scheme, which reduces the communication time by 50% compared with the traditional transmission scheme and greatly reduces the energy consumption.
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Дисертації з теми "Energy Packet"

1

Nilsson, Samuel, and Joakim Eriksson. "Estimating Application Energy Consumption Through Packet Trace Analysis." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110348.

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Анотація:
The advancement of mobile clients and applications makes it possible for people to always stayconnected, sending and receiving data constantly. The nature of the 3G technology widelyused, however, causes a high battery drain in cellular phones and because of that a lot of toolsfor measuring mobile phones energy consumption has been developed. In this report we lookinto the trace-driven tool EnergyBox and find out how we can use it to estimate the energyconsumption of 3G transmissions for an application we’ve developed ourselves. We beginwith identifying the types of traffic our application generates and identify which parts of itmake up our applications background traffic. Different combinations of the identified traffictypes are looked into in order to decide which ones that need to be present in the packet tracesfor an estimation of our applications energy footprint for 3G transmission. Further, answersare sought to how long the time span should be for which the packet traces are collected andhow many of them are needed in order to draw a conclusion about our application’s energyfootprint. We conclude that all traffic types responsible for our application’s backgroundtraffic need to be present in the analyzed packet traces, and data suggests that collectingmore than 10 one minute packet traces does not improve accuracy significantly (less than1%). Without user interaction, our application generates traffic, which transmitted over 3G,drains as much as an average of 930mW, meaning that a Samsung Galaxy S4 battery with acapacity of 9.88Wh would last for a maximum of 10 hours and 30 minutes (excluding otherenergy consuming sources inside the handset).
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2

Sanjuan, Joseba. "3G Energy-Efficient Packet Handling Kernel Module for Android." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84507.

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Анотація:
The use of mobile devices is increasing due to the constant development of more advanced and appealing applications and computing features. However, these new features are very power hungry leading to short battery lifetimes. Research shows that a major reason for fast battery depletion is the excessive and inefficient use of the wireless interfaces. This thesis studies how we can attempt to increase the battery lifetime of the devices without having to sacrifice the usage of these advanced features in some applications. The thesis focuses on adapting the traffic pattern characteristics of mobile communication using a widespread wireless communication technology like 3G. Traffic pattern adaptation is performed at packet level in kernel space in Android. The data transfers are scheduled with the knowledge of the energy consumption characteristics of 3G. The performed measurements indicate that our solution can provide energy savings ranging from 7% to 59%. This work confirms that 3G conscious scheduling of network traffic reduces energy consumption, and that, both applications and energy saving libraries are potential directions to be further studied.
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3

Oto, Mert Can. "Energy-efficient Packet Size Optimization For Cognitive Radio Sensor Networks." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613040/index.pdf.

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Анотація:
Cognitive Radio (CR) has emerged as the key technology to enable dynamic spectrum access. Capabilities of CR can meet the unique requirements of many wireless networks. Hence, Cognitive Radio Sensor Networks (CRSN) is introduced as a promising solution to address the unique challenges of Wireless Sensor Networks (WSN) which have been widely used for reliable event detection for many applications. However, there exist many open research issues for the realization of CRSN. Among others, determination of optimal packet size for CRSN is one of the most fundamental problems to be addressed. The existing optimal packet size solutions devised for CR networks as well as WSN are not applicable in CRSN regime and would cause a waste of energy resources. Hence, the objective of this thesis is to determine the optimal packet size for CRSN that maximizes energy-efficiency while maintaining acceptable interference level for licensed primary users (PU) and remaining under the maximum allowed distortion level between tracked event signal and its estimation at sink. Energy-efficient packet size reduces energy consumption and increases the transmission efficiency for CRSN. In this thesis, the energy-efficient packet size optimization problem is analytically formulated. Then, sequential quadratic programming (SQP) method is used for solving the optimization problem. The variation of optimal packet size with respect to different parameters of CRSN network is observed through numerical analysis. Results reveal that PU behavior and channel bit error rate (BER) are the most critical parameters in determining energy-efficient optimal packet size for CRSN.
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4

Mobin, Iftekharul. "Energy efficient packet size optimization for wireless ad hoc networks." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8769.

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Анотація:
Energy efficiency is crucial for ad hoc networks because of limited energy stored in the battery. Recharging the nodes frequently is sometimes not possible. Therefore, proper energy utilization is paramount. One possible solution of increasing energy efficiency is to optimize the transmitted packet size. But, we claim that only optimal packet size can not boost the energy efficiency in the noisy channel due to high packet loss rate and overhead. Hence, to reduce the overhead size and packet loss, compression and Forward Error Correction (FEC) code are used as remedy. However, every method has its own cost. For compression and FEC, the costs are computation energy cost and extra processing time. Therefore, to estimate the energy-optimize packet size with FEC or compression, processing energy cost and delay need to be considered for precise estimation. Otherwise, for delay sensitive real time applications (such as: VoIP, multimedia) over ad hoc network, energy efficient optimal packet size can be overestimated. We will investigate without degrading the Quality of Service (QoS) with these two different techniques FEC and compression, how much energy efficiency can be achieved by using the energy efficient optimal packet size for different scenarios such as: single hop, multi-hop, multiple source congested network etc. This thesis also shows the impact of time variable channel, packet fragmentation, packet collision on the optimal packet size and energy efficiency. Our results show that, for larger packets, error correction improves the energy efficiency in multi-hop networks only for delay tolerant applications. Whereas for smaller packets, compression is more energy efficient most of the cases. For real-time application like VoIP the scope of increasing the energy efficiency by optimizing packet after maintaining all the constraints is very limited. However, it is shown that, in many cases, optimal packet size improves energy efficiency significantly and also reduces the overall packet loss.
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5

Kassab, Hisham Ibrahim. "low-energy mobile packet radio networks : routing, scheduling, and architecture." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9121.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2000.
Includes bibliographical references (leaves 171-176).
Packet Radio Networks (PRNETs), which are also called ad-hoc networks, have the capability of fast (and ad-hoc) deployment and set-up, and therefore potentially have several useful civilian and military applications. Building low-energy PRNETs is an important design goal, because the communication devices are typically powered by batteries, and therefore are useless when the batteries are depleted. We choose to look at low-energy PRNETs by focusing on the problem of minimum-energy communication over a PRNET, resolving any related issues or design decisions in a manner consistent with the overall goal of low-energy PRNETs. We conclude that the problem of minimum-energy communication over a PRNET is really a joint routing-scheduling-topological problem. We find the joint problem to be intractable, and therefore propose to solve it by decomposing it, solving each component separately. The resulting solution is not optimal but the degree of suboptimality depends on how the problem is decomposed. Therefore we compare different decomposition methods, and select the one that is likely to yield the best solution to the joint problem. After deciding how to decompose the joint problem, we study the separate components. For the topological problem we decide that nodes should communicate with a limited number of other nodes, referred to as neighbors. We also propose and analyze the performance of a procedure for managing the set of neighbors. For the scheduling problem, we propose a novel and practical class of scheduling algorithms. The routing problem is more complex than wireline routing because of interference and fading. When they are incorporated, routing becomes a non-convex problem; and we overcome this by a novel approach that is non-optimal, but is more robust than the optimal approach.
by Hisham Ibrahim Kassab.
Ph.D.
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6

Reza, C. M. F. S. "Design of Energy Mixer and Router for DC Power Packet Distribution System." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20137.

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Анотація:
Energy internet (EI) is introduced recently aiming to improve power system reliability, security and efficiency through advanced information and power electronic technologies. A power packet distribution system (PPDS) is a promising candidate for the EI implementation, as it transfers information alongside the distribution of electric power. The PPDS can be realized for both DC and AC power distribution. This thesis has made four key contributions to the DC-PPDS: (1) A revised PP structure is proposed, which has a reduced footer bit and hence reduction in power switching losses. A routing scheme which does not need footer bits like handshaking protocol is proposed to increase PP distribution efficiency. A new algorithm for PP generation is also proposed capable of generating the PP based on the load power requests and the source power availability. A systematic approach is given to select the energy buffer which is needed to sustain the load voltage. (2) An over-current protection (OCP) scheme based on a simple analog circuit and integrated with the PPDS is proposed to monitor and protect the system during the over-current scenario. The routing algorithm is also modified, which utilizes the information received from the OCP circuit to isolate the faulty loads without interrupting the PP delivery to the other loads. (3) A multiple- energy-source mixer based on a single-inductor, multiple-input and single-output converter structure is proposed to attain power conditioning and voltage regulation simultaneously to send power to various loads at distinct voltage levels. (4) A four-port converter-based mixer is also proposed, which can interface with battery to mitigate intermittency problem of RESs, hence ensure reliable power distribution in islanded mode. The proposed solutions have been verified through experimental results. The PPDS has the potential to be applied in systems where communication and power transfer occur simultaneously.
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7

Morfopoulou, Christina. "Queuing analysis and optimization techniques for energy efficiency in packet networks." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/11681.

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Анотація:
Energy efficiency in all aspects of human life has become a major concern, due to its significant environmental impact as well as its economic importance. Information and Communication Technology (ICT) plays a dual role in this; not only does it constitute a major consumer itself (estimated 2-10% of the global consumption), but is also expected to enable global energy efficiency through new technologies tightly dependent on networks (smart grid, smart homes, cloud computing etc.). To this purpose, this work studies the problem of energy efficiency in wired networks. As this subject has recently become very active in the research community, there is parallel research towards several research directions. In this work, the problem is being examined from its foundations and a solid analytical approach is presented. Specifically, a network model based on G-network queuing theory is built, which can incorporate all the important parameters of power consumption together with traditional performance metrics and routing control capability. This generalized model can be applied for any network case to build optimization algorithms and estimate the performance of different policies and network designs. Composite optimization goals functions are proposed, comprising both power consumption and performance metrics. A gradient descent optimization algorithm that can run in O(N3) time complexity is built thereof. Using power consumption characteristics of current and future equipment, several case studies are presented and the optimization results are evaluated. Moreover, a faster gradient-descent based heuristic and a decentralized algorithm are proposed. Apart from the routing control analysis, the case of a harsher energy saving solution, namely turning o the networking equipment, is also experimentally explored. Applying a tradeoff study on a laboratory testbed, implementation challenges are identified and conclusions significant for future work are drawn. Finally, a novel admission control mechanism is proposed and experimentally evaluated, which can monitor and manage the power consumption and performance of a network.
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8

Eriksson, Daniel, and Axel Persson. "Energy Optimization of Scheduling and Packet Loss in Wireless Sensor Networks." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214699.

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Анотація:
We study the data aggregation of Wireless SensorNetworks (WSN). This is done by considering two problemformulations. The problems examine two different parts of thenetworks and their impact on its energy consumption. The firstproblem looks at the impact of packet loss and the secondproblem on the impact of network scheduling. The reason behindthis is that WSN usually operate on battery power and may beplaced in locations where they are hard to replace. Thus if itis possible to reduce the energy consumption of a WSN, thetotal lifespan of it will be increased. This led to the formulationof a NP-hard deadline constraint problem that is solved bysimulation. For simulation purposes a fixed tree topology wasused to investigate the impact of packet loss rate. The simulationsof the seven different scheduling policies use the same tree. Itcould be concluded from this that an increase in packet lossby only 12% percent leads to two times as long transmissiontime and therefore also twice the energy consumption. For thesecond problem the scheduling policies are evaluated by theirspeed, reliability and evenness and assigned an index based onthese parameters. Here we could see that clear improvementscould be done to a system depending on which parameters wereprioritized.
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9

Sachdeva, Gitanjali. "Measuring and Optimizing Energy Efficiency in Internet Communication : Implementing a Packet-Level Energy Model for Content Delivery Networks." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-22693.

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Анотація:
Green ICT (Information and Communication Technology) aims at reducing the environmental impacts of ICT operations, maximizing energy efficiency and promoting recyclability. The ICT industry is resource intensive with rapidly increasing demands for more infrastructure and power. It is heavily dependent on full-time network connectivity. Therefore, networks play a crucial role in the overall green ICT initiatives. Various research efforts are being made by network equipment manufacturers as well as researchers to promote energy efficiency in the networks. The target of this master thesis is to develop mechanisms that allow measuring the energy consumption in networks and using them to optimize network usage. The thesis implements a packet-level energy accounting model using NS-3 simulator. The main idea is that IP packets collect the information of energy they consume at each hop while traversing a network. This information is later processed to account for the overall network energy consumption.The thesis work analyzes a specific use case of selecting energy-efficient servers in Content Delivery Networks (CDNs) to deliver content to end users. The energy model is implemented and tested for different traffic scenarios and sample network topologies. Simulation results show that the model can prove highly useful in the CDN use case. The energy accounting scheme allows end users to choose energy-efficient server alternatives for accessing content over the internet. End users are made aware of their carbon footprint and are able to contribute to green networking.Additionally, there is also a possibility to integrate the model with other network performance metrics such as network throughput in order to increase its usability.
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10

Nawata, Shinya. "Design of Electrical Energy Network Based on Power Packetization." 京都大学 (Kyoto University), 2017. http://hdl.handle.net/2433/225598.

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Книги з теми "Energy Packet"

1

Kenton, Leslie. The raw energy bible: Packed with raw energy goodness and food combining facts. London: Vermilion, 1998.

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2

What your broadband provider knows about your web use: Deep packet inspection and communications laws and policies : hearing before the Subcommittee on Telecommunications and the Internet of the Committee on Energy and Commerce, House of Representatives, One Hundred Tenth Congress, second session, July 17, 2008. Washington: U.S. G.P.O., 2008.

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3

Chattopadhyay, P. Absorption & stripping. New Delhi: Asian Books, 2007.

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4

The complete encyclopedia of superfoods: With 150 high-impact power-packed recipes : cooking for health, energy, weight loss and fitness : a comprehensive guide to the most powerful nutrient-rich incredients and their properties. Wigston, U.K.]: Hermes House, 2014.

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5

United States. Congress. House. Committee on Small Business. Subcommittee on Agriculture, Energy, and Trade. Regulatory injury: How USDA's proposed GIPSA rule hurts America's small businesses : hearing before the Subcommittee on Agriculture, Energy, and Trade of the Committee on Small Business, United States House of Representatives, One Hundred Twelfth Congress, first session, hearing held July 7, 2011. Washington: U.S. G.P.O., 2011.

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6

Lender information packet for energy efficient mortgages. IDaho. Dept. of Water Resources, 1988.

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7

Schulman, Joan. Conserving energy in the home (Competency achievement packet). Media Materials, 1986.

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8

Mola, Gustave Loret de. Physical Science: Exploring Matter and Energy - BLM Assessment Packet. McGraw-Hill Education, 2008.

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9

Binh, Le Nguyen. Optical Multi-Bound Solitons. Taylor & Francis Group, 2018.

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10

Binh, Le Nguyen. Optical Multi-Bound Solitons. Taylor & Francis Group, 2017.

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Частини книг з теми "Energy Packet"

1

Jiang, Weirong, and Viktor K. Prasanna. "Energy-Efficient Parallel Packet Forwarding." In Green IT: Technologies and Applications, 151–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22179-8_8.

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2

Gelenbe, Erol. "Energy Packet Networks: ICT Based Energy Allocation and Storage." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 186–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33368-2_16.

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3

Horváth, Dániel, Imre Bertalan, István Moldován, and Tuan Anh Trinh. "An Energy-Efficient FPGA-Based Packet Processing Framework." In Lecture Notes in Computer Science, 31–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13971-0_4.

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4

Lee, Sung-Keun, Yong-Jae Jang, and Kyoung-Wook Park. "Adaptive Packet Coalescing Mechanism in Energy Efficient Ethernet." In Lecture Notes in Electrical Engineering, 371–79. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5857-5_40.

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5

Patil, Madhu, and Chirag Sharma. "Energy-Efficient Packet Routing Model for Wireless Sensor Network." In Lecture Notes in Electrical Engineering, 341–50. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4765-7_36.

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6

Anuroopa, A., P. Sujatha Therese, and K. S. Biju. "Improved Exergy in Three Phase Induction Motor by Eliminating Harmonics Using Wavelet Packet Transform." In Green Energy and Technology, 383–90. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8278-0_25.

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7

Yang, Yibo, Honglin Zhao, and Xuemai Gu. "Improve Energy Consumption and Packet Scheduling for Mobile Edge Computing." In Lecture Notes in Electrical Engineering, 1659–66. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_201.

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8

Köppel, H., and U. Manthe. "Femtosecond Wave-Packet Dynamics on Strongly Coupled Potential Energy Surfaces." In Nato ASI Series, 83–95. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-2326-4_7.

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9

Liu, Yi, Caiming Zhang, and Yuhua Peng. "Neural Classification of Lung Sounds Using Wavelet Packet Coefficients Energy." In Lecture Notes in Computer Science, 278–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-36668-3_31.

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10

Ganhão, Francisco, Miguel Pereira, Luis Bernardo, Rui Dinis, Rodolfo Oliveira, Paulo Pinto, Mário Macedo, and Paulo Pereira. "Energy Efficient NDMA Multi-packet Detection with Multiple Power Levels." In Technological Innovation for Sustainability, 581–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19170-1_64.

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Тези доповідей конференцій з теми "Energy Packet"

1

Gelenbe, Erol. "Energy packet networks." In the 2nd International Workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2168697.2168698.

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2

Kadioglu, Yasin Murat, and Erol Gelenbe. "Packet transmission with K energy packets in an energy harvesting sensor." In e-Energy'16: The Seventh International Conference on Future Energy Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2939948.2939949.

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3

Muttath, Dony J., M. Santhoshkumar, and K. Premkumar. "Energy Optimal Packet Scheduling with Individual Packet Delay Constraints." In 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). IEEE, 2018. http://dx.doi.org/10.1109/ants.2018.8710104.

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4

Samain, Sébastien, Josu Doncel, Ana Busic, and Jean-Michel Fourneau. "Energy Packet Networks with Finite Capacity Energy Queues." In VALUETOOLS '20: 13th EAI International Conference on Performance Evaluation Methodologies and Tools. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3388831.3388841.

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5

Chen, Wanshi, Urbashi Mitra, and Michael Neely. "Packet Dropping Algorithms for Energy Savings." In 2006 IEEE International Symposium on Information Theory. IEEE, 2006. http://dx.doi.org/10.1109/isit.2006.261838.

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6

Kennedy, Alan, Xiaojun Wang, and Bin Liu. "Energy efficient packet classification hardware accelerator." In Distributed Processing Symposium (IPDPS). IEEE, 2008. http://dx.doi.org/10.1109/ipdps.2008.4536216.

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7

Doncel, Josu, and Jean-Michel Fourneau. "Balancing Energy Consumption and Losses with Energy Packet Network Models." In 2019 IEEE International Conference on Fog Computing (ICFC). IEEE, 2019. http://dx.doi.org/10.1109/icfc.2019.00017.

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8

Ceran, Elif Tugce, and Erol Gelenbe. "Energy packet model optimisation with approximate matrix inversion." In e-Energy'16: The Seventh International Conference on Future Energy Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2939948.2939952.

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9

Eaves, Stephen S. "Network remote powering using packet energy transfer." In INTELEC 2012 - 2012 IEEE International Telecommunications Energy Conference. IEEE, 2012. http://dx.doi.org/10.1109/intlec.2012.6374488.

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10

Di Gregorio, L. "Energy budget simulation for deep packet inspection." In 2013 International Conference on Computing, Networking and Communications (ICNC 2013). IEEE, 2013. http://dx.doi.org/10.1109/iccnc.2013.6504151.

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Звіти організацій з теми "Energy Packet"

1

Winterheimer, Clarence. Comparison of Three Methods of Remote Metering of Electrical Energy: Telephone Line, Fiber Optic, and Radio Packet. Fort Belvoir, VA: Defense Technical Information Center, July 1998. http://dx.doi.org/10.21236/ada352081.

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2

Arimilli, R., and C. Moy. Boiling/evaporative heat transfer from spheres in packed-bed thermal energy storage units. Office of Scientific and Technical Information (OSTI), May 1990. http://dx.doi.org/10.2172/6817824.

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3

Yoo, Jun, Sunming Qin, and Terry Morton. TEDS Test Plan for Performance Characterization of Packed-bed Thermal Energy Storage Unit. Office of Scientific and Technical Information (OSTI), September 2022. http://dx.doi.org/10.2172/1908716.

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4

Mariager, P., Z. Shelby, M. Van de Logt, and D. Barthel. Transmission of IPv6 Packets over Digital Enhanced Cordless Telecommunications (DECT) Ultra Low Energy (ULE). Edited by J. Petersen. RFC Editor, May 2017. http://dx.doi.org/10.17487/rfc8105.

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5

Qin, Sunming, Jun Yoo, and Terry Morton. Thermal Ratcheting Analysis of TEDS Packed-bed Thermocline Energy Storage Tank - Modeling Methodology and Data Validation. Office of Scientific and Technical Information (OSTI), May 2022. http://dx.doi.org/10.2172/1868532.

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6

Leventis, Greg, and Jeff Deason. Practices for Demonstrating Energy Savings from Commercial PACE Projects. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1822413.

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7

none,. Accelerating the Pace of Change in Energy Technologies Through an Integrated Federal Energy Policy. Office of Scientific and Technical Information (OSTI), November 2010. http://dx.doi.org/10.2172/1218979.

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8

Posewitz, Matthew. PACE: Producing Algae for Co-Products and Energy (Final Report). Office of Scientific and Technical Information (OSTI), January 2022. http://dx.doi.org/10.2172/1839024.

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9

Lunn, Maureen. From climate and cancer solutions to commitment to the mission: Secretary of Energy ‘visits’ Los Alamos for packed virtual tour. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1798083.

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10

Deason, Jeff, Sean Murphy, and Charles Goldman. Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1855369.

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