An Energy-Efficient Clustering Algorithm Combined Game Theory and Dual-Cluster-Head Mechanism for WSNs

A novel energy-efficient clustering algorithm was proposed which aimed at improving the energy efficiency of WSNs via reducing and balancing energy consumption in this paper. The lemma concerning the dual-cluster-head mechanism which was designed to reduce the energy overhead during the process of rotation of Cluster Heads (CHs) was proposed and proven at first. In addition, a non-cooperative game model was presented with the purpose of balancing the energy consumption among the Cluster Heads. Besides, the Nash Equilibrium Point (NEP) of the game model was presented and the corresponding proof was provided. Subsequently, the Energy-efficient Clustering algorithm combined Game theory and Dual-cluster-head (ECGD) mechanism was detailed, which took the energy efficiency in both of the intra-cluster and inter-cluster communication into consideration. Finally, extensive experiments were conducted via simulation and the simulation results were compared with the existing Clustering strategies in terms of energy efficiency and network performance. The analyses of results have shown that the ECGD can improve energy efficiency and extend the network lifespan effectively.

[1]  Chung-Horng Lung,et al.  Using Hierarchical Agglomerative Clustering in Wireless Sensor Networks: An Energy-Efficient and Flexible Approach , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[2]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[3]  Altan Koçyigit,et al.  On determining cluster size of randomly deployed heterogeneous WSNs , 2008, IEEE Communications Letters.

[4]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[5]  Yueh-Min Huang,et al.  Localized and load‐balanced clustering for energy saving in wireless sensor networks , 2008, Int. J. Commun. Syst..

[6]  Juan Zhang,et al.  Application of Linear Predictive Coding and Data Fusion Process for Target Tracking by Doppler Through-Wall Radar , 2019, IEEE Transactions on Microwave Theory and Techniques.

[7]  Christian Enz,et al.  wiseMAC, an ultra low power MAC protocol for the wiseNET wireless sensor network. , 2003 .

[8]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[9]  Indranil Gupta,et al.  Cluster-head election using fuzzy logic for wireless sensor networks , 2005, 3rd Annual Communication Networks and Services Research Conference (CNSR'05).

[10]  Nathan Ickes,et al.  Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks , 2001, MobiCom '01.

[11]  Dirk Timmermann,et al.  Low energy adaptive clustering hierarchy with deterministic cluster-head selection , 2002, 4th International Workshop on Mobile and Wireless Communications Network.

[12]  Hisao Ishibuchi,et al.  Performance evaluation of genetic algorithms for flowshop scheduling problems , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[13]  Guangzhong Xie,et al.  A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks , 2010, Comput. Commun..

[14]  Ankit Thakkar,et al.  Cluster Head Election for Energy and Delay Constraint Applications of Wireless Sensor Network , 2014, IEEE Sensors Journal.

[15]  Jin-Shyan Lee,et al.  Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication , 2012, IEEE Sensors Journal.

[16]  Deyu Lin,et al.  A game theory based energy efficient clustering routing protocol for WSNs , 2017, Wirel. Networks.

[17]  Weifa Liang,et al.  Prolonging Network Lifetime via a Controlled Mobile Sink in Wireless Sensor Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[18]  Yong Wang,et al.  An Energy-Efficient and Swarm Intelligence-Based Routing Protocol for Next-Generation Sensor Networks , 2014, IEEE Intelligent Systems.

[19]  James Lam,et al.  An Energy-Efficient Adaptive Overlapping Clustering Method for Dynamic Continuous Monitoring in WSNs , 2017, IEEE Sensors Journal.

[20]  Rajesh Kumar,et al.  Realisation of a cluster-based protocol using fuzzy C-means algorithm for wireless sensor networks , 2013, IET Wirel. Sens. Syst..

[21]  Xuxun Liu,et al.  Atypical Hierarchical Routing Protocols for Wireless Sensor Networks: A Review , 2015, IEEE Sensors Journal.

[22]  S. Khorsandi,et al.  A Novel cluster-based routing protocol with extending lifetime for wireless sensor networks , 2008, 2008 5th IFIP International Conference on Wireless and Optical Communications Networks (WOCN '08).

[23]  Sangjun Lee,et al.  T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks , 2009, Inf. Syst. Frontiers.

[24]  Gregory M. P. O'Hare,et al.  A Stable Routing Framework for Tree-Based Routing Structures in WSNs , 2014, IEEE Sensors Journal.

[25]  Charalampos Tsimenidis,et al.  Energy-Aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[26]  Tao Liu,et al.  An energy-balancing clustering approach for gradient-based routing in wireless sensor networks , 2012, Comput. Commun..

[27]  Jianping Pan,et al.  NDCMC: A Hybrid Data Collection Approach for Large-Scale WSNs Using Mobile Element and Hierarchical Clustering , 2016, IEEE Internet of Things Journal.

[28]  A.E. Kamal,et al.  Data aggregation in wireless sensor networks - exact and approximate algorithms , 2004, 2004 Workshop on High Performance Switching and Routing, 2004. HPSR..

[29]  Jin-Shyan Lee,et al.  An Improved Three-Layer Low-Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks , 2016, IEEE Internet of Things Journal.

[30]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[31]  Pardeep Kumar,et al.  Level Based Routing Using Dynamic Programming for 2D Mesh , 2017 .

[32]  Rolland Vida,et al.  Deploying Multiple Sinks in Multi-hop Wireless Sensor Networks , 2007, IEEE International Conference on Pervasive Services.

[33]  Habib F. Rashvand,et al.  Geographical multi-layered energy-efficient clustering scheme for ad hoc distributed wireless sensor networks , 2016, IET Wirel. Sens. Syst..

[34]  D.P. Agrawal,et al.  APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[35]  Ying Liao,et al.  Load-Balanced Clustering Algorithm With Distributed Self-Organization for Wireless Sensor Networks , 2013, IEEE Sensors Journal.

[36]  Sanyang Liu,et al.  Clustering routing algorithm of wireless sensor networks based on Bayesian game , 2012 .

[37]  Lovepreet Kaur,et al.  Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey , 2014 .

[38]  Jenq-Shiou Leu,et al.  Energy Efficient Clustering Scheme for Prolonging the Lifetime of Wireless Sensor Network With Isolated Nodes , 2015, IEEE Communications Letters.

[39]  Yong Deng,et al.  An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks , 2015, Int. J. Distributed Sens. Networks.

[40]  Cheng Li,et al.  Distributed Data Aggregation Using Slepian–Wolf Coding in Cluster-Based Wireless Sensor Networks , 2010, IEEE Transactions on Vehicular Technology.

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

[42]  Xiaofeng Tao,et al.  Unbalanced Expander Based Compressive Data Gathering in Clustered Wireless Sensor Networks , 2017, IEEE Access.

[43]  Fei Dai,et al.  Increasing network lifetime by balancing node energy consumption in heterogeneous sensor networks , 2008, Wirel. Commun. Mob. Comput..

[44]  Hai Lin,et al.  Energy Efficient Clustering Protocol for Large-Scale Sensor Networks , 2015, IEEE Sensors Journal.

[45]  Abraham O. Fapojuwo,et al.  A centralized energy-efficient routing protocol for wireless sensor networks , 2005, IEEE Communications Magazine.

[46]  D. K. Lobiyal,et al.  An energy-efficient adaptive clustering algorithm with load balancing for wireless sensor network , 2012, Int. J. Sens. Networks.

[47]  Bara'a Ali Attea,et al.  Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks , 2011, Swarm Evol. Comput..

[48]  Emanuel Melachrinoudis,et al.  A New MILP Formulation and Distributed Protocols for Wireless Sensor Networks Lifetime Maximization , 2006, 2006 IEEE International Conference on Communications.

[49]  Nadeem Javaid,et al.  $(ACH)^2$ : Routing Scheme to Maximize Lifetime and Throughput of Wireless Sensor Networks , 2014, IEEE Sensors Journal.