An Efficient Clustering Protocol for Wireless Sensor Networks Based on Localized Game Theoretical Approach

Xie, Dongfeng; Sun, Qi; Zhou, Qianwei; Qiu, Yunzhou; Yuan, Xia

doi:10.1155/2013/476313

Cited by 37 publications

(28 citation statements)

References 24 publications

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“…The demerit of CROSS is that it involves all sensor nodes in CH election, which is not possible in real‐time applications. In localized game theoretical clustering algorithm (LGCA), a clustering game is played with local neighbors to find the probability and decide selfishly to play CH or not. To avoid having more than one CH per cluster, the self‐selected nodes need to put effort to become CH.…”

Section: Related Workmentioning

confidence: 99%

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

Thandapani

Arunachalam

Durairaj

2020

Int J Communication

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Most of the current generation sensor nodes of mobile wireless sensor network (MWSN) are designed to have heterogeneous mobility to adapt itself in the applied environment. Energy optimization in MWSN with heterogeneous mobility is very challenging task. In this paper, a heterogeneous game theoretical clustering algorithm called mobile clustering game theory-1 (MCGT-1) is proposed for energy optimization in a heterogeneous mobile sensor environment. Energy optimization is achieved through energy-efficient cluster head election and multipath routing in the network. A heterogeneous clustering game is modelled with varying attributes and located an asymmetric equilibrium condition for a symmetric game with mixed strategies. The real-time parameters, namely, predicted remaining energy, distance between a base station and nodes, distance between nodes, and mobility speed, were used to calculate the probability to elect the cluster head (CH). The efficient multipath routing is achieved through prior energy prediction strategy. It has mitigated the generation of "hot spots," reducing its delay and improving the overall residual energy of the network. Simulation results showed that the average lifetime of MCGT-1 has increased by 6.33 %, 13.1% and 14.2% and the PDR has improved by 4.8%,11.8%, and 17.2% than MCGT, LEACH-ME and LEACH-M respectively. The hot spot delay is reduced to 0.063025 seconds, improving the efficiency of the network. K E Y W O R D Sclustering, mobility, predicted remaining energy, hot spot problem it is essential to use the battery power in an optimal way. Secondly, the battery energy gets depleted rapidly during active communication if it is not properly monitored and controlled. Therefore, a better energy optimization in a sensor network is inevitable, and hence, a clustering architecture is proposed.Many protocols for mobile sensing environment works with constant mobile speed or with homogeneous mobility. 4 In the existing protocols, the node speed and energy dissipation remain constant irrespective of the distance moved. These phenomena lead to waste of the attained bandwidth and timeslot and affect the overall network performance, lifetime, and quality of service (QoS). In practice, it is not possible to attain the constant mobility speed throughout thedeployment and in real-time, the nodes may move with different speeds either arbitrarily or naturally called-heterogeneous mobility. 4 According to Osborne, 5 a game is defined as a method of competitive play by-law. Game theory (GT) is a mathematical branch that deals with competitive situations while analyzing the strategies of every player and produce an outcome based on actions of other participants. In recent years, GT is applied in clustering of sensor network. Since then, all the algorithms are proposed for a static environment where the nodes are fixed without frequent clustering. The game of these algorithms is not defined from the view of sensors and its topology. Further, these algorithms do not provide a solution for hot spot problem i...

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Section: Related Workmentioning

confidence: 99%

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

Thandapani

Arunachalam

Durairaj

2020

Int J Communication

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“…In research literature it is generally found that cluster LGCA [35] uses game theory for the clustering of nodes where the nodes compete selfishly with its neighbor nodes which are in their communication ranges and suitable for the CH selection. In EEMA [36], the CH selection criterion has been enhanced by considering the centrality of the node and the proximity to the other neighboring CHs besides the residual energy of the nodes.…”

Section: Cluster Head Selection Criteriamentioning

confidence: 99%

A Survey of Energy Conservation Mechanisms for Dynamic Cluster Based Wireless Sensor Networks

Enam¹,

Tahir²,

Qureshi³

et al. 2018

Mehran Univ. res. j. eng. technol.

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WSN (Wireless Sensor Network) is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented.

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“…In the cluster formation phase, it is important to appropriately allocate nodes in cross coverages to different CHs to balance the energy consumption. In earlier papers, there are two simple but typical allocation schemes 7,18,19 that are used to address the issue. One is the distance scheme in which MNs join the nearest CH to form clusters; the other is the degree scheme in which MNs join the CHs with the smallest degree.…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…However, since the nodes' transmission capability is not restricted, CROSS is not suitable for practical applications. To meet the requirements in real networks, a localized game theoretical clustering algorithm (LGCA) 18 is presented. Each player communicates only with its neighbours within a fixed communication radius.…”

Section: Introductionmentioning

confidence: 99%

An energy-balance and game-theory-based cluster formation method for wireless sensor networks

Zeng

Fang

et al. 2017

International Journal of Distributed Sensor Networks

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Clustering techniques in wireless sensor networks have been widely utilized for their good performance in reducing energy dissipation and prolonging network lifetime. Once the cluster heads have been decided, the allocation of member nodes in the cross coverages formed by two or more clusters is critical to keep an energy balance on the cluster heads. In earlier studies, however, the allocation of member nodes simply depends on the distance or degree (the node number within the cluster heads' communication radius) and, therefore, could cause imbalance to the cluster heads' load and further degrade the whole wireless sensor network. To maintain the load balance of the cluster heads, in this article, game theory is introduced into the allocation problem of the member nodes. Before using the game theory approach, the number and distribution of cluster heads are first checked. If the cover rate of the cluster heads is low, then the node(s) uncovered by any cluster are randomly selected as new cluster head(s) to attain the cover rate required in the article. Furthermore, the number of cluster heads in a monitoring region is restricted. Finally, a game-based, energy-balance method is proposed and applied in the cluster-based routing protocols to improve their performance. For verification, the proposed method is embedded into the localized game theoretical clustering algorithm and hybrid, game theorybased and distributed clustering algorithm, which are two game theory and typical cluster-based routing protocols. The experimental results show that both of the improved protocols do balance the loads of the cluster heads and achieve better performance than their original versions in spanning the lifetime and balancing the energy in wireless sensor networks.

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An Efficient Clustering Protocol for Wireless Sensor Networks Based on Localized Game Theoretical Approach

Cited by 37 publications

References 24 publications

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

A Survey of Energy Conservation Mechanisms for Dynamic Cluster Based Wireless Sensor Networks

An energy-balance and game-theory-based cluster formation method for wireless sensor networks

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