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Journal articles on the topic 'Traffic Aware Routing'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Mohammadzadeh, Hekmat, and Shapour Joudi Bigdello. "UTCARP: Urban Traffic Control Aware Routing Protocol." International Journal on AdHoc Networking Systems 3, no. 1 (January 31, 2013): 1–13. http://dx.doi.org/10.5121/ijans.2013.3101.

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2

Vinnarasi, F. Sangeetha Francelin, and A. Chandrasekar. "VANET routing protocol with traffic aware approach." International Journal of Advanced Intelligence Paradigms 12, no. 1/2 (2019): 3. http://dx.doi.org/10.1504/ijaip.2019.096944.

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3

Chandrasekar, A., and F. Sangeetha Francelin Vinnarasi. "VANET routing protocol with traffic aware approach." International Journal of Advanced Intelligence Paradigms 12, no. 1/2 (2019): 3. http://dx.doi.org/10.1504/ijaip.2019.10017739.

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4

Parsa, Ali, and Neda Moghim. "QoS-aware routing and traffic management in multi-flow opportunistic routing." Computers & Electrical Engineering 94 (September 2021): 107330. http://dx.doi.org/10.1016/j.compeleceng.2021.107330.

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5

Hu, Yaqin, Mingyue Xu, Ming Tang, Dingding Han, and Ying Liu. "Efficient traffic-aware routing strategy on multilayer networks." Communications in Nonlinear Science and Numerical Simulation 98 (July 2021): 105758. http://dx.doi.org/10.1016/j.cnsns.2021.105758.

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6

YAMASHITA, Shigeyuki, Tomohiko YAGYU, and Miki YAMAMOTO. "Time-Dimensional Traffic Engineering with Storage Aware Routing." IEICE Transactions on Communications E97.B, no. 12 (2014): 2641–49. http://dx.doi.org/10.1587/transcom.e97.b.2641.

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7

Della Valle, Emanuele, Irene Celino, Daniele Dell'Aglio, Ralph Grothmann, Florian Steinke, and Volker Tresp. "Semantic Traffic-Aware Routing Using the LarKC Platform." IEEE Internet Computing 15, no. 6 (November 2011): 15–23. http://dx.doi.org/10.1109/mic.2011.107.

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8

Park, Chongmyung, Harksoo Kim, and Inbum Jung. "Traffic-aware routing protocol for wireless sensor networks." Cluster Computing 15, no. 1 (December 4, 2010): 27–36. http://dx.doi.org/10.1007/s10586-010-0146-3.

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9

Anderson, Eric J., Thomas E. Anderson, Steven D. Gribble, Anna R. Karlin, and Stefan Savage. "A quantitative evaluation of traffic-aware routing strategies." ACM SIGCOMM Computer Communication Review 32, no. 1 (January 2002): 67. http://dx.doi.org/10.1145/510726.510741.

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10

Wang, Cuixiang, Xing Shao, Zhi Gao, Chuanxin Zhao, and Jun Gao. "Common network coding condition and traffic matching supported network coding aware routing for wireless multihop network." International Journal of Distributed Sensor Networks 15, no. 6 (June 2019): 155014771985397. http://dx.doi.org/10.1177/1550147719853978.

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Network coding–based routing has been widely considered as a promising technology to improve the network throughput of wireless multihop network. However, existing network coding aware routings have the problem of failure decoding and usually neglect the transmission scheduling, which degrades the gain of network coding. In this article, a common network coding condition and traffic matching supported network coding aware routing is proposed for wireless multihop network. In this, common network coding condition is proposed to avoid the problem of failed decoding. In addition, traffic matching mechanism is presented to promote the occurrence of network coding. Besides, a coding and load aware routing metric, which jointly considers the network coding opportunity and node load, is designed to evaluate the discovered paths. Extensive simulations on NS2 demonstrate that CTNR increases the number of coding opportunities and network coding occurrence, and improves network throughput.

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11

Tang, Minghua, Xiaola Lin, and Maurizio Palesi. "Routing Pressure: A Channel-Related and Traffic-Aware Metric of Routing Algorithm." IEEE Transactions on Parallel and Distributed Systems 26, no. 3 (March 2015): 891–901. http://dx.doi.org/10.1109/tpds.2013.184.

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12

Muthukumaran V., Vinothkumar V., Rose Bindu Joseph, Meram Munirathanam, and Balajee Jeyakumar. "Improving Network Security Based on Trust-Aware Routing Protocols Using Long Short-Term Memory-Queuing Segment-Routing Algorithms." International Journal of Information Technology Project Management 12, no. 4 (October 2021): 47–60. http://dx.doi.org/10.4018/ijitpm.2021100105.

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Defending all single connection failures for a particular system, segment routing issue, the switch will focus on the problems of selecting a small subset of trust-aware routing to improve the deep learning (DL). In the end, even if there were multiple path failures, these paths may introduce long-term, unnecessary overload in the proposed long short-term memory networks-based queuing routing segmentation (LSTM-QRS) experience of reducing traffic delays and adjusting traffic length by reducing network bandwidth. The critical factor is a novel traffic repair technique used to create a traffic repair path that switches to software-defined network (SDN) using multiple routing and providing additional flexibility in re-routing using long short-term memory networks (LSTM)-based queuing routing segment (LSTM-QRS) algorithms. It reduces the repair path length and recommends replacing the target-based traffic with the connection-based traffic fault detection router to avoid targeted traffic network congestion.

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13

Abu Al-Haija, Qasem, and Ahmad Al-Badawi. "Attack-Aware IoT Network Traffic Routing Leveraging Ensemble Learning." Sensors 22, no. 1 (December 29, 2021): 241. http://dx.doi.org/10.3390/s22010241.

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Network Intrusion Detection Systems (NIDSs) are indispensable defensive tools against various cyberattacks. Lightweight, multipurpose, and anomaly-based detection NIDSs employ several methods to build profiles for normal and malicious behaviors. In this paper, we design, implement, and evaluate the performance of machine-learning-based NIDS in IoT networks. Specifically, we study six supervised learning methods that belong to three different classes: (1) ensemble methods, (2) neural network methods, and (3) kernel methods. To evaluate the developed NIDSs, we use the distilled-Kitsune-2018 and NSL-KDD datasets, both consisting of a contemporary real-world IoT network traffic subjected to different network attacks. Standard performance evaluation metrics from the machine-learning literature are used to evaluate the identification accuracy, error rates, and inference speed. Our empirical analysis indicates that ensemble methods provide better accuracy and lower error rates compared with neural network and kernel methods. On the other hand, neural network methods provide the highest inference speed which proves their suitability for high-bandwidth networks. We also provide a comparison with state-of-the-art solutions and show that our best results are better than any prior art by 1~20%.

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14

Khokhar, R. H., M. A. Ngadi, M. S. Latiff, and M. A. Amin. "Reactive traffic-aware routing strategy for urban vehicular environments." International Journal of Ad Hoc and Ubiquitous Computing 10, no. 3 (2012): 149. http://dx.doi.org/10.1504/ijahuc.2012.048625.

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15

Anand, Vijay, Ankush Jain, K. K. Pattanaik, and Ajay Kumar. "Traffic aware field-based routing for wireless sensor networks." Telecommunication Systems 71, no. 3 (October 24, 2018): 475–89. http://dx.doi.org/10.1007/s11235-018-0519-0.

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16

Amaldi, E., A. Capone, and L. G. Gianoli. "Energy-aware IP traffic engineering with shortest path routing." Computer Networks 57, no. 6 (April 2013): 1503–17. http://dx.doi.org/10.1016/j.comnet.2013.02.006.

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17

Rao Musala, Venkateswara, and T. V Rama Krishna. "Low latency Path Aware XY-X Routing Algorithm for NoC Architectures." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 763. http://dx.doi.org/10.14419/ijet.v7i2.7.10941.

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Route specific information with the SoC needs a great deal of wiring, which increases the Resistance & Capacitance (RC) component of the system. Network on Chip (NoC) is utilized as the interface to address the problems in SoC, On-chip interconnection network in NoC has gained more consideration over steadfast wiring and buses, like lower latency, scalability and high performance. Present routing algorithms in NoC is suffered from load balancing at incarnation networks under non-uniform traffic conditions, causes increase the NoC trade-offs (latency and throughput). Adaptive routing is a technique to progress the load balance, but previous adaptive routing techniques used uniform traffic patterns to form the routing decisions. This paper proposes a new approach at non- uniform traffic patterns in channel state and path specific, Path Aware Routing (PAR XY-X) uses a timeout piggybacking for acknowledgement and load shedding to avoid congestion which choose optimistic path calculation unit to connect the destination node without glue logic decisions in routing. PAR XY-X outperforms the Normal XY routing by 20% and 33% with respect to Avg.latency and throughput.

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18

Firdausi, Ahmad. "Pengoptimasian Traffic pada Jaringan Wide Area Network Menggunakan Application Aware Routing Berbasis SD-WAN." InComTech : Jurnal Telekomunikasi dan Komputer 12, no. 2 (August 18, 2022): 154. http://dx.doi.org/10.22441/incomtech.v12i2.15180.

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Abstrak:Seiring dengan berkembangnya zaman, pengguna internet saat ini terus bertambah. Pengguna internet dunia yang diprediksi akan mencapai 66% populasi dunia pada tahun 2023, selain itu perkembangan tersebut juga didukung oleh munculnya berbagai jenis aplikasi dan komputasi berbasis awan. Tentunya dengan seiring bertambahnya pengguna internet dan penggunaan berbagai aplikasi tersebut diperlukan kehandalan jaringan WAN (Wide Area Network) dalam menangani traffic yang masih terdapat beberapa tantangan diantaranya terbatasnya bandwidth, latensi tinggi, kemacetan data dan hilangnya paket data pada jaringan. Oleh karena itu penulis mengusulkan implementasi application aware routing berbasis SD-WAN yang diharapkan dapat memberikan pengalaman akses yang lebih baik sekaligus menjadi solusi ketika terdapat gangguan pada jaringan WAN yang dapat menurunkan performansi traffic data dan suara. Berdasarkan pengukuran dan simulasi sistem yang telah diimplementasikan pada GNS3 terhadap performasi traffic suara, performansi QoS traffic suara saat peak traffic menggunakan SD-WAN application aware routing lebih baik dibandingkan dengan BGP multihomed dengan rata-rata latency 20,77 ms, rata-rata jitter 27,26 ms dan packet loss 3,7%. Performansi QoS traffic suara tersebut masih dalam kategori “Bagus” dan “Sangat Bagus” berdasarkan standar TIPHON. Sedangkan performansi traffic data HTTP saat peak traffic menggunakan SD-WAN application aware routing juga lebih baik dibandingkan dengan BGP Multihomed dengan rata-rata waktu tanggap 146.812 ms, dan TCP retransmission 15 paket.

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19

Yan, Jiangyu, and Bing Qi. "CARA: A Congestion-Aware Routing Algorithm for Wireless Sensor Networks." Algorithms 14, no. 7 (June 30, 2021): 199. http://dx.doi.org/10.3390/a14070199.

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Congestion control is one of the key research topics in relation to the routing algorithms of wireless sensor networks (WSNs). In this paper, we propose a congestion-aware routing algorithm (CARA) for unlimited-lifetime wireless sensor networks by integrating the geographic distance and traffic load of sensor nodes. The algorithm takes alleviating congestion as the primary purpose and considers the traffic of the node itself and local network traffic. According to the geographic distance between nodes, CARA defines four decision parameters (node load factor, forward rate, cache remaining rate, and forward average cache remaining rate), selecting the best node as the next-hop through the multi-attribute decision-making method. Compared with the two existing algorithms for congestion control, our simulation results suggest that the CARA algorithm alleviates network congestion and meets reasonable network delay and energy consumption requirements.

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20

Jaskóła, Przemysław, Piotr Arabas, and Andrzej Karbowski. "Simultaneous routing and flow rate optimization in energy–aware computer networks." International Journal of Applied Mathematics and Computer Science 26, no. 1 (March 1, 2016): 231–43. http://dx.doi.org/10.1515/amcs-2016-0016.

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Abstract The issue of energy-aware traffic engineering has become prominent in telecommunications industry in the last years. This paper presents a two-criteria network optimization problem, in which routing and bandwidth allocation are determined jointly, so as to minimize the amount of energy consumed by a telecommunication infrastructure and to satisfy given demands represented by a traffic matrix. A scalarization of the criteria is proposed and the choice of model parameters is discussed in detail. The model of power dissipation as a function of carried traffic in a typical software router is introduced. Then the problem is expressed in a form suitable for the mixed integer quadratic programming (MIQP) solver. The paper is concluded with a set of small, illustrative computational examples. Computed solutions are implemented in a testbed to validate the accuracy of energy consumption models and the correctness of the proposed traffic engineering algorithm.

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21

Yu, Ji Ming, Xiao Yong Yan, Nan Xu, and Yu Wang Yang. "Collision-Avoiding Aware Routing Based on Real-Time Hybrid Traffic Infomations." Advanced Materials Research 396-398 (November 2011): 2511–14. http://dx.doi.org/10.4028/www.scientific.net/amr.396-398.2511.

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Vehicular Ad Hoc Networks (VANET) is a peculiar type of mobile Ad Hoc networks for ITS,compared with MANET, it has following distinguishing feature: high dynamic topology changing, speed-moving nodes, frequently disconnected network, unlimited battery power and storage, network node movement restraind by traffic rule. The article definition the concept collision-set,and derive a novel collision-avoiding aware routing based on real-time hybrid-traffic infomations which restricted by traffic rule(RHCAR). Nodes will builting subnetworks based on collision-set, every node will communicate with its neighbours of collision-set for collision-avoiding,extensive simulations the collision-avoiding trend with two type of scenario.

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22

Liu, Hanyan, Xiaowen Chen, Yunping Zhao, Chen Li, and Jianzhuang Lu. "TTQR: A Traffic- and Thermal-Aware Q-Routing for 3D Network-on-Chip." Sensors 22, no. 22 (November 11, 2022): 8721. http://dx.doi.org/10.3390/s22228721.

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The die-stacking structure of 3D network-on-chips (3D NoC) leads to high power density and unequal thermal conductance between different layers, which results in low reliability and performance degradation of 3D NoCs. Congestion-aware adaptive routing, which is capable of balancing the network’s traffic load, can alleviate congestion and thermal problems so as to improve the performance of the network. In this study, we propose a traffic- and thermal-aware Q-routing algorithm (TTQR) based on Q-learning, a reinforcement learning method. The proposed algorithm saves the local traffic status and the global temperature information to the Q1-table and Q2-table, respectively. The values of two tables are updated by the packet header and saved in a small size, which saves the hardware overhead. Based on the ratio of the Q1-value to the Q2-value corresponding to each direction, the packet’s output port is selected. As a result, packets are transferred to the chosen path to alleviate thermal problems and achieve more balanced inter-layer traffic. Through the Access Noxim simulation platform, we compare the proposed routing algorithm with the TAAR routing algorithm. According to experimental results using synthetic traffic patterns, our proposed methods outperform the TAAR routing algorithm by an average of 63.6% and 41.4% in average latency and throughput, respectively.

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23

SUN, Haifeng, Guangchun LUO, and Hao CHEN. "JTAR: Junction-Based Traffic Aware Routing in Sparse Urban VANETs." IEICE Transactions on Communications E95-B, no. 3 (2012): 1007–10. http://dx.doi.org/10.1587/transcom.e95.b.1007.

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24

Din, Sadia, Kashif Naseer Qureshi, M. Sheheryar Afsar, Joel J. P. C. Rodrigues, Awais Ahmad, and Gyu Sang Choi. "Beaconless Traffic-Aware Geographical Routing Protocol for Intelligent Transportation System." IEEE Access 8 (2020): 187671–86. http://dx.doi.org/10.1109/access.2020.3030982.

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25

Sharma, Deepak, and Amol P. Bhondekar. "Traffic and Energy Aware Routing for Heterogeneous Wireless Sensor Networks." IEEE Communications Letters 22, no. 8 (August 2018): 1608–11. http://dx.doi.org/10.1109/lcomm.2018.2841911.

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26

Shao, Xing, Cuixiang Wang, Chuanxin Zhao, and Jun Gao. "Traffic Shaped Network Coding Aware Routing for Wireless Sensor Networks." IEEE Access 6 (2018): 71767–82. http://dx.doi.org/10.1109/access.2018.2882427.

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27

Darwish, Tasneem, and Kamalrulnizam Abu Bakar. "Lightweight intersection-based traffic aware routing in Urban vehicular networks." Computer Communications 87 (August 2016): 60–75. http://dx.doi.org/10.1016/j.comcom.2016.04.008.

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28

Houaidia, Chiraz, Hanen Idoudi, Adrien Van Den Bossche, Thierry Val, and Leila Azouz Saidane. "Towards an optimised traffic-aware routing in wireless mesh networks." International Journal of Space-Based and Situated Computing 4, no. 3/4 (2014): 217. http://dx.doi.org/10.1504/ijssc.2014.066013.

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29

Bhoi, Sourav Kumar, Pratap Kumar Sahu, Munesh Singh, Pabitra Mohan Khilar, Rashmi Ranjan Sahoo, and Rakesh Ranjan Swain. "Local Traffic Aware Unicast Routing Scheme for Connected Car System." IEEE Transactions on Intelligent Transportation Systems 21, no. 6 (June 2020): 2360–75. http://dx.doi.org/10.1109/tits.2019.2918161.

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30

Tan, Do Duy, Nguyen Quoc Dinh, and Dong-Seong Kim. "GRATA: gradient-based traffic-aware routing for wireless sensor networks." IET Wireless Sensor Systems 3, no. 2 (June 1, 2013): 104–11. http://dx.doi.org/10.1049/iet-wss.2012.0083.

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31

Huang, Kai, Jingkang Wu, Xiaowen Jiang, Dongliang Xiong, Kaitian Huang, Hao Yao, Wenyuan Xu, Yonggang Peng, and Zhili Liu. "A Period-Aware Routing Method for IEEE 802.1Qbv TSN Networks." Electronics 10, no. 1 (December 31, 2020): 58. http://dx.doi.org/10.3390/electronics10010058.

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The IEEE 802.1Qbv standard provides deterministic delay and low jitter guarantee for time-critical communication using a precomputed cyclic transmission schedule. Computing such transmission schedule requires routing the flows first, which significantly affects the quality of the schedule. So far off-the-shelf algorithms like load-balanced routing, which minimize the maximum scheduled traffic load (MSTL), have been used to accommodate more time-triggered traffic. However, they do not consider that the bandwidth utilization of periodic flows is decentralized and their criteria for bottleneck of scheduling are imprecise. In this paper, we firstly explore the combinability among different periods of flows, which can measure their ability to share bandwidth without conflict. Then, we propose a novel period-aware routing algorithm to reduce the scheduling bottleneck, thus more flows can be accommodated. The experiment results show that the success rate of scheduling is significantly improved compared to shortest path routing and load balanced routing.

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32

Wilson, M., and K. O. Boateng. "Congestion-Aware Routing (CAR):Vehicular Traffic Routing Based on Real-Time Road Occupancy Estimates." Ghana Journal of Science 59 (December 22, 2018): 5. http://dx.doi.org/10.4314/gjs.v59i1.1.

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33

Bourdena, Athina, Constandinos X. Mavromoustakis, George Kormentzas, Evangelos Pallis, George Mastorakis, and Muneer Bani Yassein. "A resource intensive traffic-aware scheme using energy-aware routing in cognitive radio networks." Future Generation Computer Systems 39 (October 2014): 16–28. http://dx.doi.org/10.1016/j.future.2014.02.013.

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34

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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35

Garroppo, Rosario G., Stefano Giordano, Gianfranco Nencioni, and Maria Grazia Scutellà. "Power-Aware Routing and Network Design with Bundled Links: Solutions and Analysis." Journal of Computer Networks and Communications 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/154953.

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The paper deeply analyzes a novel network-wide power management problem, called Power-Aware Routing and Network Design with Bundled Links (PARND-BL), which is able to take into account both the relationship between the power consumption and the traffic throughput of the nodes and to power off both the chassis and even the single Physical Interface Card (PIC) composing each link. The solutions of the PARND-BL model have been analyzed by taking into account different aspects associated with the actual applicability in real network scenarios: (i) the time for obtaining the solution, (ii) the deployed network topology and the resulting topology provided by the solution, (iii) the power behavior of the network elements, (iv) the traffic load, (v) the QoS requirement, and (vi) the number of paths to route each traffic demand. Among the most interesting and novel results, our analysis shows that the strategy of minimizing the number of powered-on network elements through the traffic consolidation does not always produce power savings, and the solution of this kind of problems, in some cases, can lead to spliting a single traffic demand into a high number of paths.

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36

Mavromoustakis, Constandinos X., Athina Bourdena, George Mastorakis, and Evangelos Pallis. "Using Incoming Traffic for Energy-Efficient Routing in Cognitive Radio Networks." Journal of Information Technology Research 8, no. 1 (January 2015): 1–24. http://dx.doi.org/10.4018/jitr.2015010102.

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This paper proposes an energy-efficient routing scheme that is based on a resource intensive traffic-aware approach, enabling for the maximization of the energy conservation in cognitive radio networks. The proposed approach interrelates the moments of the backward difference traffic, together with the sleep-time duration, towards tuning the activity periods of the network nodes. The effective operation of the proposed scheme, in terms of minimum energy consumption, minimum delays and maximum number of the routing paths established, is achieved through the exploitation of a signaling mechanism. The validity of the proposed traffic-aware scheme is tested, through several simulation tests, by obtaining multiple performance evaluation results. The experimental results verified the proper operation of the proposed scheme to maximize the energy conservation, optimize the data exchange among the network nodes and minimize the routing delays.

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37

Zhang, Aiqi, Meiyi Sun, Jiaqi Wang, Zhiyi Li, Yanbo Cheng, and Cheng Wang. "Deep Reinforcement Learning-Based Multi-Hop State-Aware Routing Strategy for Wireless Sensor Networks." Applied Sciences 11, no. 10 (May 13, 2021): 4436. http://dx.doi.org/10.3390/app11104436.

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With the development of wireless sensor network technology, the routing strategy has important significance in the Internet of Things. An efficient routing strategy is one of the fundamental technologies to ensure the correct and fast transmission of wireless sensor networks. In this paper, we study how to combine deep learning technology with routing technology to propose an efficient routing strategy to cope with network topology changes. First, we use the recurrent neural network combined with the deep deterministic policy gradient method to predict the network traffic distribution. Second, the multi-hop node state is considered as the input of a double deep Q network. Therefore, the nodes can make routing decisions according to the current state of the network. Multi-hop state-aware routing strategy based on traffic flow forecasting (MHSA-TFF) is proposed. Simulation results show that the MHSA-TFF can improve transmission delay, average routing length, and energy efficiency.

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38

Son, Sunghwa, Gwangjin Wi, and Kyung-Joon Park. "Situation-Aware Survivable Network Design for Tactical Environments." Applied Sciences 12, no. 13 (July 3, 2022): 6738. http://dx.doi.org/10.3390/app12136738.

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A tactical sensor network is a representative safety-critical environment that should satisfy strict guarantee of the requirements of tactical traffic. However, because of the lack of infrastructure in a military network environment, resource constraints on wireless channel and nodes can cause problems such as network congestion and packet collision. If critical tactical data is lost or does not arrive on time, it can degrade the efficiency of military operations and even threaten the survival of soldiers. To resolve this critical issue, we propose a situational backoff reset algorithm that utilizes a quality of service (QoS) field information to determine the priority of received tactical packets and control the deferral time of low-priority traffic. From a packet routing path connectivity perspective, we propose a branch node-based routing algorithm in order to provide a resilient path by excluding the isolated single path. Our simulation results demonstrate that the proposed solution can prioritize tactical traffic from the channel preemption perspective and construct a robust end-to-end path avoiding an isolated single path.

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39

Wang, Xiaoni. "Resource-Aware Clustering Based AODVjr Routing Protocol in the Internet of Things." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 4 (July 20, 2013): 622–27. http://dx.doi.org/10.20965/jaciii.2013.p0622.

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Through ad hoc routing protocol AODVjr and resource-aware data mining algorithms research, a resource-aware clustering based routing protocol in the Internet of Things, RA-AODVjr, is proposed. It solves the short comings of the constrained resources of memory, computing power, and the power energy of the wireless sensor’s terminal node in the Internet of Things. RA-AODVjr protocol is designed combining with the RA-cluster and AODVjr routing protocol. This protocol selects the best neighbor in the terminal node and balances the network traffic when terminal node resource is constrained, using the relevance of the ad hoc network. The simulation results show that the agreement achieves load balancing of energy constrained nodes to a certain extent. Compared with the original AODVjr protocol, due to the best neighbor node delivery technology, the local network traffic gets a better balance and less time delay means better choice of routing.

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40

Almeida, Eduardo Nuno, André Coelho, José Ruela, Rui Campos, and Manuel Ricardo. "Joint traffic-aware UAV placement and predictive routing for aerial networks." Ad Hoc Networks 118 (July 2021): 102525. http://dx.doi.org/10.1016/j.adhoc.2021.102525.

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Mohammed, Belghachi, and Debab Naouel. "An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles." Computers, Materials & Continua 60, no. 3 (2019): 959–72. http://dx.doi.org/10.32604/cmc.2019.07580.

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Jiang, Ming, Chengxing Zhou, Min Zhang, Chunming Wu, and Xiao Min. "TM-EAR: An Energy-aware Routing Algorithm Based on Traffic Matrix." Information Technology Journal 12, no. 4 (April 1, 2013): 811–16. http://dx.doi.org/10.3923/itj.2013.811.816.

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Tague, Patrick, Sidharth Nabar, James A. Ritcey, and Radha Poovendran. "Jamming-Aware Traffic Allocation for Multiple-Path Routing Using Portfolio Selection." IEEE/ACM Transactions on Networking 19, no. 1 (February 2011): 184–94. http://dx.doi.org/10.1109/tnet.2010.2057515.

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Dharmaweera, Madushanka Nishan, Juzi Zhao, Li Yan, Magnus Karlsson, and Erik Agrell. "Traffic-Grooming- and Multipath-Routing-Enabled Impairment-Aware Elastic Optical Networks." Journal of Optical Communications and Networking 8, no. 2 (January 8, 2016): 58. http://dx.doi.org/10.1364/jocn.8.000058.

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Gavrilut, Voica, Luxi Zhao, Michael L. Raagaard, and Paul Pop. "AVB-Aware Routing and Scheduling of Time-Triggered Traffic for TSN." IEEE Access 6 (2018): 75229–43. http://dx.doi.org/10.1109/access.2018.2883644.

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Yan, Boyuan, Yongli Zhao, Xiaosong Yu, Wei Wang, Yu Wu, Ying Wang, and Jie Zhang. "Tidal-Traffic-Aware Routing and Spectrum Allocation in Elastic Optical Networks." Journal of Optical Communications and Networking 10, no. 11 (September 4, 2018): 832. http://dx.doi.org/10.1364/jocn.10.000832.

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Ren, Fengyuan, Tao He, Sajal K. Das, and Chuang Lin. "Traffic-Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks." IEEE Transactions on Parallel and Distributed Systems 22, no. 9 (September 2011): 1585–99. http://dx.doi.org/10.1109/tpds.2011.24.

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Kunthara, Rose George, Rekha K. James, Simi Zerine Sleeba, and John Jose. "Traffic aware routing in 3D NoC using interleaved asymmetric edge routers." Nano Communication Networks 27 (March 2021): 100334. http://dx.doi.org/10.1016/j.nancom.2020.100334.

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Ding, Wei, Liangrui Tang, and Sen Feng. "Traffic-Aware and Energy-Efficient Routing Algorithm for Wireless Sensor Networks." Wireless Personal Communications 85, no. 4 (July 19, 2015): 2669–86. http://dx.doi.org/10.1007/s11277-015-2927-8.

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Darwish, Tasneem, and Kamalrulnizam Abu Bakar. "Traffic aware routing in vehicular ad hoc networks: characteristics and challenges." Telecommunication Systems 61, no. 3 (March 13, 2015): 489–513. http://dx.doi.org/10.1007/s11235-015-0008-7.

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