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Game Theory Inspired Mobile Object Trapping System in Mobile Wireless Sensor Network

机译:移动无线传感器网络中博弈论启发的移动物体诱捕系统

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In the current scenario, wireless sensor network (WSN) is used in substantial number of applications. Mobile WSN (MWSN) is preferred over static WSN in many applications especially in mobile object tracking and trapping system. Coverage is strongly related to object trapping as it is easier to trap an object in fully covered area compare to partially covered area. MWSN becomes default selection when it comes to trap a mobile object in a partially covered area because mobility of sensor nodes can be utilized to enhance the coverage of the network and thus able to detect and trap target. One of the fundamental problems of MWSN is how to coordinate these mobile sensors in such a way that they can move together in order to achieve their common goal. In this paper, we present a game theory inspired mobile object trapping system (GT-MOTS) where mobile nodes form a coalition such that they trap a mobile object by exchanging some key information between themselves. Through this information exchange movement of one sensor influence the movements of its neighbours. The objective of the proposed scheme is to minimize the trapping time by reducing travel distance of each sensor node. The concept of cooperative game theory is used for coalition and concept of pursuer evasion game is used for mobile target trapping. The effectiveness of the proposed approach is evaluated and compared with random way-point mobility model (RWP) and three other variants of RWP using NS-3 simulation.
机译:在当前情况下,无线传感器网络(WSN)被大量应用。在许多应用中,尤其是在移动对象跟踪和捕获系统中,移动WSN(MWSN)优于静态WSN。覆盖率与对象捕获密切相关,因为与部分覆盖的区域相比,将对象捕获在完全覆盖的区域更容易。当要将移动对象捕获在部分覆盖的区域中时,MWSN成为默认选择,因为可以利用传感器节点的移动性来增强网络的覆盖范围,从而能够检测和捕获目标。 MWSN的基本问题之一是如何协调这些移动传感器,使其可以一起移动以实现其共同目标。在本文中,我们提出了一种受博弈论启发的移动对象捕获系统(GT-MOTS),其中移动节点形成联盟,以便它们通过在彼此之间交换一些关键信息来捕获移动对象。通过这种信息交换,一个传感器的运动会影响其邻居的运动。所提出的方案的目的是通过减少每个传感器节点的行进距离来使捕获时间最小化。合作博弈论的概念用于联盟,追击者逃避博弈的概念用于移动目标诱捕。评估了所提出方法的有效性,并使用NS-3仿真与随机航点移动模型(RWP)和RWP的其他三个变体进行了比较。

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