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Data Aggregation Using Dynamic Selection of Aggregation Points Based on RSSI for Wireless Sensor Networks

机译:无线传感器网络中基于RSSI的基于聚合点动态选择的数据聚合

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In wireless sensor networks (WSNs), due to dense deployment, sensory data gathered by sensor nodes in close proximity tend to exhibit high correlation and therefore redundant. Transmitting such redundant data is not practical in the energy-constrained WSNs. Data aggregation offers a key solution to reduce such redundancy by allowing intermediate nodes to aggregate raw data streams before routing them toward a sink node. This in turn reduces transmission energy consumption. Prior work in data aggregation often rely on node's location for selecting an aggregator node, a fusion point. In this work, we propose two data aggregation mechanisms where aggregator nodes are determined opportunistically without dependency on global knowledge of data flow, network topology and nodes' geographical location. These mechanisms aggregate and route data packets based on Received Signal Strength Indicator (RSSI). An aggregation identification (Agg_ID) is associated with each data packet generated by a sensor node. The RSSI and Agg_ID are used in the RSSI-Based Fowarding for favoring nodes closer to sink to be an aggregator and also a relay node. We show via simulation the performance of the proposed mechanisms in terms of normalized number of transmissions, total number of packets transmissions and receptions, average energy consumed per data packet, network lifetime, end-to-end delay and packet loss probability.
机译:在无线传感器网络(WSN)中,由于部署密集,由附近的传感器节点收集的传感数据往往表现出较高的相关性,因此具有冗余性。在能量受限的无线传感器网络中,传输此类冗余数据并不可行。数据聚合通过允许中间节点在将原始数据流路由到宿节点之前聚合原始数据流,从而提供了减少此类冗余的关键解决方案。这进而减少了传输能量消耗。数据聚合的现有工作通常依赖于节点的位置来选择聚合器节点(融合点)。在这项工作中,我们提出了两种数据聚合机制,这些机制是在不依赖于数据流,网络拓扑和节点地理位置的全局知识的情况下,机会性地确定聚合器节点的。这些机制根据接收信号强度指示器(RSSI)聚合和路由数据包。聚合标识(Agg_ID)与传感器节点生成的每个数据包关联。 RSSI和Agg_ID在基于RSSI的转发中用于使更靠近接收器的节点成为聚合器,也成为中继节点。通过仿真,我们从归一化的传输数量,数据包传输和接收的总数,每个数据包消耗的平均能量,网络寿命,端到端延迟和数据包丢失概率方面展示了所提出机制的性能。

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