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Autonomous actor positioning in wireless sensor and actor networks using stable-matching

机译:使用稳定匹配在无线传感器和演员网络中自主演员定位

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In most of the wireless sensor and actor network applications, it is desirable to have an autonomous process for positioning the actors in order to eliminate human intervention as much as possible. For this purpose, sensors and actors deployed in an area of interest can collaborate in a distributed manner. Typically, sensors can instruct actors for their positioning in the area by considering the application level interests. This instruction is based on selecting representative sensor locations. One of the most common ways of selecting such representative locations is to cluster the network and determine cluster heads (CHs) as representatives. The actors can then move to such CH locations by talking to nearby sensors/actors. Such movement, however, should be done wisely in order to minimise the movement distance of actors so that their lifetimes can be extended. Nevertheless, this may not be possible since not all the actor and CH locations will be known by each actor. In this paper, we propose an actor-CH location matching algorithm which assigns the actors to appropriate CH locations in a distributed manner with minimised travel distance on actors and message overhead on sensors. We adapt the Gale-Shapley (GS) stable matching algorithm from stable matching theory. In this matching algorithm, actors are regarded as men and CHs are regarded as women. For distributed execution of the algorithm, sub-networks of actors and CHs are determined. Each sub-network elects a leader that performs the matching in the sub-network based on GS algorithm. If there are unmatched actors after this process, either a separate search is used to detect such nodes or leaders talk to each other to share this information so that further matching can be performed. We have evaluated the performance of our approach through simulation and shown that our approach can produce travel distance results that are very close to the brute-force approach with minimal messaging overhead.
机译:在大多数无线传感器和演员网络应用中,希望有一个自主过程来定位演员,以便尽可能消除人为干预。为此,部署在感兴趣区域中的传感器和参与者可以以分布式方式进行协作。通常,传感器可以通过考虑应用程序级别的兴趣来指示角色在该区域中的位置。该说明基于选择代表性的传感器位置。选择此类代表位置的最常见方法之一是对网络进行集群并确定集群头(CH)作为代表。然后,演员可以通过与附近的传感器/演员交谈来移动到此类CH位置。但是,应该明智地进行这种运动,以使演员的运动距离最小化,从而可以延长其寿命。但是,这可能是不可能的,因为并非每个演员都知道所有演员和CH位置。在本文中,我们提出了一种actor-CH位置匹配算法,该算法以分布式方式将actor分配给适当的CH位置,从而使actor上的行进距离最小并且传感器上的消息开销最小。我们根据稳定匹配理论改编了Gale-Shapley(GS)稳定匹配算法。在该匹配算法中,将演员视为男性,将CH视为女性。为了算法的分布式执行,要确定参与者和CH的子网。每个子网选择一个领导者,该领导者根据GS算法在子网中执行匹配。如果在此过程之后有不匹配的参与者,则可以使用单独的搜索来检测此类节点,或者领导者相互交谈以共享此信息,从而可以执行进一步的匹配。我们已经通过仿真评估了我们方法的性能,并表明我们的方法可以以最小的消息传递开销产生非常接近于蛮力方法的行驶距离结果。

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