Studying Bio-Inspired Coalition Formation of Robots for Detecting Intrusions Using Game Theory

Self Cite

In social groups, complex group behavior often emerges from the local interaction among simple individuals. Throughout this study, we assume that individuals can access information by way of wireless communication. In this case, individuals are able to exchange accurate information with each other as long as wireless communication links between them are allowed. Subsequently, we propose a consensus decision-making model for studying the consistency of group behavior considering both the wireless communication range and the probability of successful communication. Our simulation results show the following conclusions: (i) consistency of the group behavior is absolutely achieved, when the wireless communication range is large enough and the probability of successful communication p D 1; (ii) when the wireless communication range is large enough, the consistency of the group behavior is still achieved as long as p is bigger than some small constant; and (iii) the law in (iii) remains applicable when the number of individuals in the group changes. Therefore, one may infer that consistency of group behavior in mobile sensors is much more related to the extent of distribution of obtainable information than the amount of information, where the extent of distribution of obtainable information means that each individual can obtain information from wider area or from those individuals who are not only in its local area.

Section: Related Workmentioning

confidence: 99%

The effects of wireless communication failures on group behavior of mobile sensors

Zheng

Huang

Wang

et al. 2012

Self Cite

“…A preliminary of this work was presented in Reference 18. Authors in References 19–21 study collaborations among robots using game theory. A robot communication is studied in Reference 22.…”

Section: Related Workmentioning

confidence: 99%

Divide‐ and conquer‐based surveillance framework using robots, sensor nodes, and RFID tags

Xiao¹,

Zhang²

2011

Self Cite

Sensor networks are adopted in many surveillance applications. A traditional method for such applications is to deploy sensor nodes all over the surveillance region in order to cover as much area as possible. However, this way not only waste huge amounts of money for sensor nodes and resources, but it is also unnecessary and unrealistic sometimes. It provides huge amounts of garbage in the form of dead sensor nodes and batteries. It invokes many data collisions and places a serious burden on network protocols. In many applications, we have no need to have detail on every point inside the area, but only in some critical places. For example, in a forest fire surveillance application, covering the whole forest is unnecessary and unrealistic. In this paper, we propose a divide-and conquer-based surveillance framework, in which a large surveillance area is divided into small areas by critical points and critical lines. Sensor nodes, sinks, robots, and RFID tags are all used. We only deploy sensor nodes along critical lines instead of all over the region. Our aim is to do surveillance with efficient deployment of sensor nodes and sinks, and to detect, track, and even capture targets, e.g., an intrusion tank or forest fire, with the collaboration of robots and sensor nodes. We study boundary coverage along critical lines. Robots perform tasks of patrolling, handling incidents, communicating with sensor nodes/sinks, and even being capable of deploying/throwing-out sensor nodes/RFID tags. Finally, we evaluate perimeter coverage, robot patrol routing, and so on.

“…Meanwhile, we set fixed expired time (TTL) for each packet to ensure the packet delivery delay and restrict the behavior of the ferry. In the scenario where multiple ferries are working together, by using the a Bayesian game , we make all ferries work more effectively. In the main sections of this paper, we make a deep analysis and conclude that the non‐cooperative Bayesian game is the appropriate model for the proposed packet selection strategy.…”

Section: Introductionmentioning

confidence: 99%

Non‐cooperative game‐based packet ferry forwarding for sparse mobile wireless networks

Guan

Chen

Ohtsuki

2013

In sparse mobile wireless networks, normally, the mobile nodes are carried by people, and the moving activity of nodes always happens in a specific area, which corresponds to some specific community. Between the isolated communities, there is no stable communication link. Therefore, it is difficult to ensure the effective packet transmission among communities, which leads to the higher packet delivery delay and lower successful delivery ratio. Recently, an additional ferry node was introduced to forward packets between the isolated communities. However, most of the existing algorithms are working on how to control the trajectory of only one ferry work in the network. In this paper, we consider multiple ferries working in the network scenario and put our main focus on the optimal packet selection strategy, under the condition of mutual influence between the ferries and the buffer limitation. We introduce a non-cooperative Bayesian game to achieve the optimal packet selection strategy. By maximizing the individual income of a ferry, we optimize the network performance on packet delivery delay and successful delivery ratio. Simulation results show that our proposed packet selection strategy improves the network performance on packet delivery delay and successful delivery ratio.