A hybrid, game theory based, and distributed clustering protocol for wireless sensor networks

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Xing, Shaojing

doi:10.1007/s11276-015-1011-3

Cited by 44 publications

(34 citation statements)

References 30 publications

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“…Compared with CROSS, LGCA is more feasible since it is completely distributed and easily extendible. Based on LGCA, a hybrid, game theory–based and distributed clustering (HGTD) protocol is proposed. CH is elected based on node degree and distance to BS of a node.…”

Section: Related Workmentioning

confidence: 99%

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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%

“…The proposed algorithm uses first‐order radio model for handling energy dissipation in the network . Energy spent on transmitting and receiving “ l ” bits of data to and from distance “ d ” is given in Equations , , and , respectively.…”

Section: System Modelmentioning

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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“…is section leverages such contributions made previously to review the most related and credible studies regarding energy efficiency in communication networks. e hybrid game theory and a distributed cluster technique are applied in WSNs to control energy consumption by Yang et al [17]. Each node has a payoff that is designed based on various parameters that include node degree and distance to the base station.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Coalition Games with Incentives in Machine-to-Machine Communications

Juma

Kurien

Olwal

2019

Journal of Computer Networks and Communications

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The need to achieve energy efficiency in machine-to-machine (M2M) communications has been a driver of the use of coalition game-based cooperative communication schemes. The proposed schemes have shown good energy-efficient performance results in the recent past. However, sustaining cooperation amongst coalition games of M2M devices from different network-operating authorities requires appropriate incentives. A review of the literature demonstrates that a limited number of contributions have considered the use of coalition games with incentives in M2M communications. In this paper, an energy-efficient coalition game with incentives in M2M communications is proposed. This work considers a Sierpinski triangle technique to partition M2M devices into multiple networks of hierarchical zones. Based on the constructed zones, a contract-modelled incentive is invoked to stimulate multihop transmissions between devices up to the BS/sink. The results obtained demonstrate that the proposed approach is on average 10% more energy efficient than the closely related existing algorithm, the coalition game theoretical clustering (CGTC).

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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%

“…If the CHs are beyond a certain number, then they will consume more energy for their remote communication with the BS in the WSNs. Additionally, we first give the following formula 19,21 to compute the former optimal number…”

Section: Restriction On the Number Of Chsmentioning

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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A hybrid, game theory based, and distributed clustering protocol for wireless sensor networks

Cited by 44 publications

References 30 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

Energy-Efficient Coalition Games with Incentives in Machine-to-Machine Communications

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

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