A multipath energy-conserving routing protocol for wireless ad hoc networks lifetime improvement

Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. Traditional techniques of routing are not well adapted. Indeed, their lack of reactivity with respect to the variability of network changes makes them difficult to use. Moreover, conserving energy is a critical concern in the design of routing protocols for ad hoc networks, because most mobile nodes operate with limited battery capacity, and the energy depletion of a node affects not only the node itself but also the overall network lifetime. In all proposed single-path routing schemes a new path-discovery process is required once a path failure is detected, and this process causes delay and wastage of node resources. A multipath routing scheme is an alternative to maximize the network lifetime. In this paper, we propose an energy-efficient multipath routing protocol, called AOMR-LM (Ad hoc On-demand Multipath Routing with Lifetime Maximization), which preserves the residual energy of nodes and balances the consumed energy to increase the network lifetime. To achieve this goal, we used the residual energy of nodes for calculating the node energy level. The multipath selection mechanism uses this energy level to classify the paths. Two parameters are analyzed: the energy threshold beta and the coefficient alpha. These parameters are required to classify the nodes and to ensure the preservation of node energy. Our protocol improves the performance of mobile ad hoc networks by prolonging the lifetime of the network. This novel protocol has been compared with other protocols: AOMDV and ZD-AOMDV. The protocol performance has been evaluated in terms of network lifetime, energy consumption, and end-to-end delay

Scalable energy-efficient routing in mobile Ad hoc network

The quick deployment without any existing infrastructure makes mobile ad hoc networks (MANET) a striking choice for dynamic situations such as military and rescue operations, disaster recovery, and so on and so forth. However, routing remains one of the major issues in MANET due to the highly dynamic and distributed environment. Energy consumption is also a significant issue in ad hoc networks since the nodes are battery powered. This report discusses some major dominating set based approaches to perform energy efficient routing in mobile ad hoc networks. It also presents the performance results for each of these mentioned approaches in terms of throughput, average end to end delay and the life time in terms of the first node failure. Based on the simulation results, I identified the key issues in these protocols regarding network life time. In this report, I propose and discuss a new approach “Dynamic Dominating Set Generation Algorithm” (DDSG) to optimize the network life time. This algorithm dynamically selects dominating nodes during the process of routing and thus creates a smaller dominating set. DDSG algorithm thereby eliminates the energy consumption from the non-used dominating nodes. In order to further increase the network life time, the algorithm takes into consideration the threshold settings which helps to distribute the process of routing within the network. This helps to eliminate a single dominating node from getting drained out by continuous transmission and reception of packets. In this report, the detailed algorithmic design and performance results through simulation is discussed

Underwater spray and wait routing technique for mobile ad-hoc networks

1648-1655The underwater mobile ad-hoc networks comprise sensor nodes that are source nodes for gathering underwater-related data. Relay nodes are the mobile nodes for collecting data from sensor nodes and achieving intermittent connectivity among source and destination nodes. Developing an efficient routing protocol for underwater communication is a challenging issue due to limitations of the underwater environment. Underwater mobile ad-hoc networks are intermittent networks where end-to-end path does not exist from source to destination. To overcome these problems a delay and disruption tolerant network (DTN) is a good solution. In the current paper, we consider the Spray and Wait (SaW) routing technique. In SaW, source and relay nodes represents the moving nodes, and they try to send data to destination nodes. Based on this, we propose the replica based underwater SaW (USaW) routing for underwater mobile ad-hoc networks. In USaW, source nodes are fixed to the bottom of the surface. Underwater sensor nodes replicate sensor data and provide maximum copies of data to the relay nodes that they encounter. In generally, relay nodes have high capability of transmitting data as compared to sensor nodes in an underwater environment. We analyze the performance of USaW with respect to delivery ratio, network throughput, energy consumption, end-to-end delay, and packet drop rate comparing with existing SaW and prophet routing protocols

Energy Efficient Stable Cluster Scheme for MANET

In Mobile Ad-hoc Networks, cluster based routing protocol(CBRP) is robustly used since they combine the advantages of Reactive and Proctive routing protocols. And they have less routing overhead and less end-to-end delay compared to Reactive and Proctive routing protocols respectively. Energy source for a mobile node is limited, and even difficult to recharge. The life time of the network depends on the life time of the nodes. So we propose different shemes to have energy efficient stable clusters. By using stable clustering algorithm to avoid frequent reclustering, efficient clustering scheme to minimize overlapping clusters, and allow nodes to save their energy by changing their mode to sleep mode

Performance Improvement of AODV in Wireless Networks using Reinforcement Learning Algorithms

This paper investigates the application of reinforcement learning (RL) techniques to enhance the performance of the Ad hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad hoc networks (MANETs). MANETs are self-configuring networks consisting of mobile nodes that communicate without the need for a centralized infrastructure. AODV is a widely used routing protocol in MANETs due to its reactive nature, which reduces overhead and conserves energy. This research explores three popular Reinforcement Learning algorithms: SARSA, Q-Learning and Deep Q-Network (DQN) to optimize the AODV protocol's routing decisions. The RL agents are trained to learn the optimal routing paths by interacting with the network environment, considering factors such as link quality, node mobility, and traffic load. The experiments are conducted using network simulators to evaluate the performance improvements achieved by the proposed RL-based enhancements. The results demonstrate significant enhancements in various performance metrics, including reduced end-to-end delay, increased packet delivery ratio, and improved throughput. Furthermore, the RL-based approaches exhibit adaptability to dynamic network conditions, ensuring efficient routing even in highly mobile and unpredictable MANET scenarios. This study offers valuable insights into harnessing RL techniques for improving the efficiency and reliability of routing protocols in mobile ad hoc networks

Adaptive Cross-Layer Multipath Routing Protocol for Mobile Ad Hoc Networks

[EN] Mobile ad hoc networks (MANETs) are generally created for temporary scenarios. In such scenarios, where nodes are in mobility, efficient routing is a challenging task. In this paper, we propose an adaptive and cross-layer multipath routing protocol for such changing scenarios. Our routing mechanisms operate keeping in view the type of applications. For simple applications, the proposed protocol is inspired from traditional on-demand routing protocols by searching shortest routes from source to destination using default parameters. In case of multimedia applications, the proposed mechanism considers such routes which are capable of providing more data rates having less packet loss ratio. For those applications which need security, the proposed mechanism searches such routes which are more secure in nature as compared to others. Cross-layer methodology is used in proposed routing scheme so as to exchange different parameters across the protocol stack for better decision-making at network layer. Our approach is efficient and fault tolerant in a variety of scenarios that we simulated and tested.The authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding this research group no. 037-1435-RG.Iqbal, Z.; Khan, S.; Mehmood, A.; Lloret, J.; Alrajeh, NA. (2016). Adaptive Cross-Layer Multipath Routing Protocol for Mobile Ad Hoc Networks. Journal of Sensors. 2016:1-18. https://doi.org/10.1155/2016/5486437S1182016Abusalah, L., Khokhar, A., & Guizani, M. (2008). A survey of secure mobile Ad Hoc routing protocols. IEEE Communications Surveys & Tutorials, 10(4), 78-93. doi:10.1109/surv.2008.080407Murthy, S., & Garcia-Luna-Aceves, J. J. (1996). An efficient routing protocol for wireless networks. Mobile Networks and Applications, 1(2), 183-197. doi:10.1007/bf01193336Toh, C.-K. (1997). Wireless Personal Communications, 4(2), 103-139. doi:10.1023/a:1008812928561Pearlman, M. R., & Haas, Z. J. (1999). Determining the optimal configuration for the zone routing protocol. IEEE Journal on Selected Areas in Communications, 17(8), 1395-1414. doi:10.1109/49.779922ZHEN, Y., WU, M., WU, D., ZHANG, Q., & XU, C. (2010). Toward path reliability by using adaptive multi-path routing mechanism for multimedia service in mobile Ad-hoc network. The Journal of China Universities of Posts and Telecommunications, 17(1), 93-100. doi:10.1016/s1005-8885(09)60431-3Sivakumar, R., Sinha, P., & Bharghavan, V. (1999). CEDAR: a core-extraction distributed ad hoc routing algorithm. IEEE Journal on Selected Areas in Communications, 17(8), 1454-1465. doi:10.1109/49.779926Zapata, M. G. (2002). Secure ad hoc on-demand distance vector routing. ACM SIGMOBILE Mobile Computing and Communications Review, 6(3), 106-107. doi:10.1145/581291.581312Khan, S., & Loo, J. (2010). Cross Layer Secure and Resource-Aware On-Demand Routing Protocol for Hybrid Wireless Mesh Networks. Wireless Personal Communications, 62(1), 201-214. doi:10.1007/s11277-010-0048-ySharma, V., & Alam, B. (2012). Unicaste Routing Protocols in Mobile Ad Hoc Networks: A Survey. International Journal of Computer Applications, 51(14), 9-18. doi:10.5120/8108-1714Tarique, M., Tepe, K. E., Adibi, S., & Erfani, S. (2009). Survey of multipath routing protocols for mobile ad hoc networks. Journal of Network and Computer Applications, 32(6), 1125-1143. doi:10.1016/j.jnca.2009.07.002Shiwen Mao, Shunan Lin, Yao Wang, Panwar, S. S., & Yihan Li. (2005). Multipath video transport over ad hoc networks. IEEE Wireless Communications, 12(4), 42-49. doi:10.1109/mwc.2005.1497857Li, Z., Chen, Q., Zhu, G., Choi, Y., & Sekiya, H. (2015). A Low Latency, Energy Efficient MAC Protocol for Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 11(8), 946587. doi:10.1155/2015/946587Zheng, Z., Liu, A., Cai, L. X., Chen, Z., & Shen, X. (2016). Energy and memory efficient clone detection in wireless sensor networks. IEEE Transactions on Mobile Computing, 15(5), 1130-1143. doi:10.1109/tmc.2015.2449847Dong, M., Ota, K., Liu, A., & Guo, M. (2016). Joint Optimization of Lifetime and Transport Delay under Reliability Constraint Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 27(1), 225-236. doi:10.1109/tpds.2015.2388482Hamrioui, S., Lorenz, P., Lloret, J., & Lalam, M. (2013). A Cross Layer Solution for Better Interactions Between Routing and Transport Protocols in MANET. Journal of Computing and Information Technology, 21(3), 137. doi:10.2498/cit.1002136Sanchez-Iborra, R., & Cano, M.-D. (2014). An approach to a cross layer-based QoE improvement for MANET routing protocols. Network Protocols and Algorithms, 6(3), 18. doi:10.5296/npa.v6i3.5827Cho, J.-H., Swami, A., & Chen, I.-R. (2011). A Survey on Trust Management for Mobile Ad Hoc Networks. IEEE Communications Surveys & Tutorials, 13(4), 562-583. doi:10.1109/surv.2011.092110.0008

Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

Vehicular Ad Hoc Network (VANET) is an emerging area of wireless ad hoc networks that facilitates ubiquitous connectivity between smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Roadside (V2R) and Roadside-to- Vehicle (R2V) communications. This emerging field of technology aims to improve safety of passengers and traffic flow, reduces pollution to the environment and enables in-vehicle entertainment applications. The safety-related applications could reduce accidents by providing drivers with traffic information such as collision avoidances, traffic flow alarms and road surface conditions. Moreover, the passengers could exploit an available infrastructure in order to connect to the internet for infomobility and entertainment applications.Lloret, J.; Ghafoor, KZ.; Rawat, DB.; Xia, F. (2013). Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks. Mobile Networks and Applications. 18(6):749-754. doi:10.1007/s11036-013-0490-7S749754186Lloret J, Canovas A, Catalá A, Garcia M (2013) Group-based protocol and mobility model for VANETs to offer internet access. J Netw Comput Appl 36(3):1027–1038. doi: 10.1016/j.jnca.2012.02.009Khokhar RH, Zia T, Ghafoor KZ, Lloret J, Shiraz M (2013) Realistic and efficient radio propagation model for V2X communications. KSII Trans Internet Inform Syst 7(8):1933–1953. doi: 10.3837/tiis.2013.08.011Ghafoor KZ (2013) Routing protocols in vehicular ad hoc networks: survey and research challenges, Netw Protocol Algorithm 5(4). doi: 10.5296/npa.v5i4.4134Ghafoor KZ, Bakar KA, Lloret J, Ke C-H, Lee KC (2013) Intelligent beaconless geographical routing for urban vehicular environments. Wirel Netw 19(3):345–362. doi: 10.1007/s11276-012-0470-zGhafoor KZ, Bakar KA, Lee K, AL-Hashimi H (2010) A novel delay- and reliability- aware inter-vehicle routing protocol. 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