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Self organized sensor deployment with Brownian motion in wireless sensor and robot networks

机译:在无线传感器和机器人网络中采用布朗运动自组织传感器部署

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In this paper, we propose a novel self organized sensor deployment protocol to ensure proper surveillance through better coverage in urban search and rescue (USAR) operations using customized Brownian motion scheme. Specifically, we use density control over Brownian Motion (DCBM) to make an adaptive self deployment protocol which can be used on heterogeneous wireless sensor and robot networks. Generally, Brownian Motion scatters particles in a random manner with disjoint behaviour which is not appropriate to be used as a mobility model for wireless network. Additionally, the model has higher collision rate among the moving particles. To avoid the previous two issues, every node in the network computes node density and decides particular direction at any timestamp. The nodes may take pause in their movement and start over from that location instead of starting every time from the initial starting point to make the model behave continuously. We simulated DCBM scheme on a series of different topologies and compared with Random waypoint model that shows promising insights.
机译:在本文中,我们提出了一种新颖的自组织传感器部署协议,以通过使用自定义的布朗运动方案更好地覆盖城市搜索和救援(USAR)的操作来确保进行适当的监视。具体来说,我们使用布朗运动密度控制(DCBM)来制定自适应的自部署协议,该协议可用于异构无线传感器和机器人网络。通常,布朗运动以不相交的行为以随机方式散射粒子,这不适合用作无线网络的移动性模型。此外,该模型在运动的粒子之间具有更高的碰撞率。为了避免上述两个问题,网络中的每个节点都会计算节点密度并在任何时间戳下确定特定方向。节点可能会暂停移动并从该位置重新开始,而不是每次都从初始起点开始,以使模型连续运行。我们在一系列不同的拓扑上模拟了DCBM方案,并与随机航点模型进行了比较,该模型显示出了有希望的见识。

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