Adaptive Cross-Layer Routing Protocol for Optimizing Energy Harvesting Time in WSN

Trade-off between energy conservation and efficiency is one of the most important issues in designing Wireless Sensor Network (WSN) based applications. Network life time is primarily determined by the life time of battery. Recently, energy harvesting techniques that will recharge the battery in different non-conventional ways are being investigated by researchers. In this paper, an adaptive cross layer protocol is proposed which will provide trade off between energy harvesting time and active time for message transmission with the aim of increasing network lifetime. Depending on the value of various network parameters like, remaining energy of node, node density, message density in a particular region of the network, the cross-layer protocol will change its policy. The paper also proposes a cluster head selection method that ensures maximum network life time and higher quality of service. The result shows an overall increase in network lifetime as compared to other protocols.

[1]  Xiaoqi Qin,et al.  An energy-efficient clustering routing algorithm for WSN-assisted IoT , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).

[2]  Quan Wang,et al.  An Energy-Efficient Clustering Algorithm Combined Game Theory and Dual-Cluster-Head Mechanism for WSNs , 2019, IEEE Access.

[3]  Hongseok Yoo,et al.  Dynamic Duty-Cycle Scheduling Schemes for Energy-Harvesting Wireless Sensor Networks , 2012, IEEE Communications Letters.

[4]  Amir H. Gandomi,et al.  Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application , 2019, IEEE Internet of Things Journal.

[5]  P. Sengottuvelan,et al.  BAFSA: Breeding Artificial Fish Swarm Algorithm for Optimal Cluster Head Selection in Wireless Sensor Networks , 2017, Wirel. Pers. Commun..

[6]  M Selvi,et al.  HBO based clustering and energy optimized routing algorithm for WSN , 2017, 2016 Eighth International Conference on Advanced Computing (ICoAC).

[7]  Muhammad Zeeshan,et al.  Sleep-awake energy efficient distributed clustering algorithm for wireless sensor networks , 2016, Comput. Electr. Eng..

[8]  Vahid Rahmati.  Near Optimum Random Routing of Uniformly Load Balanced Nodes in Wireless Sensor Networks Using Connectivity Matrix , 2020 .

[9]  Suniti Dutt,et al.  Cluster-Head Restricted Energy Efficient Protocol (CREEP) for Routing in Heterogeneous Wireless Sensor Networks , 2018, Wireless Personal Communications.

[10]  Kaibin Huang,et al.  Energy Harvesting Wireless Communications: A Review of Recent Advances , 2015, IEEE Journal on Selected Areas in Communications.

[11]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[12]  Jonathan Loo,et al.  Secure Routing Protocol Using Cross-Layer Design and Energy Harvesting in Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[13]  Bin Li,et al.  Particle swarm optimization based clustering algorithm with mobile sink for WSNs , 2017, Future Gener. Comput. Syst..

[14]  Chaowei Wang,et al.  An Improved Distributed Energy Efficient Clustering Algorithm for Heterogeneous WSNs , 2017, 2017 IEEE Wireless Communications and Networking Conference (WCNC).

[15]  Padmalaya Nayak,et al.  Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic , 2017, IEEE Sensors Journal.

[16]  Shahriar Mirabbasi,et al.  Wireless Energy Harvesting for Internet of Things , 2014 .

[17]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[18]  Manas Ranjan Kabat,et al.  An Energy Efficient Advertisement Based Multichannel Distributed MAC Protocol for Wireless Sensor Networks (Adv-MMAC) , 2016, Wireless Personal Communications.

[19]  Li Qing,et al.  Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks , 2006, Comput. Commun..

[20]  Jie Chen,et al.  Energy efficient multi-target clustering algorithm for WSN-based distributed consensus filter , 2017, 2017 36th Chinese Control Conference (CCC).

[21]  Rencheng Jin,et al.  Energy-Efficient Cluster Head Selection Scheme Based on Multiple Criteria Decision Making for Wireless Sensor Networks , 2010, Wireless Personal Communications.