Abstract

One of the constraints in Wireless Sensor Network (WSN) is the limited power of distributed interconnected sensor nodes over the space. There are several proposed architectures for handling power consumption in a WSN. Traditional clustering and routing methods improve the Cluster Head (CH) selection of WSN internodes for balancing energy in the network. In such clustering methods, every message is transmitted from a source node to its CH, from the CH to other CHs, and finally to the BS (Base Station). Therefore, a high amount of energy should be consumed for routing when the source nodes are far from CHs or the BS. This paper proposes an integrated LBSN (Location-Based Social Network) and WSN routing and CH selection method for reducing routes from source nodes to BSs to reduce the energy consumption of WSN. In the integrated network, LBSN nodes can be added to the WSN as BS or WSN sensor nodes. In the first situation, the integrated network is called IPAWL I and the latter builds the IPAWL II network.To evaluate the method, we considered a scenario of smoke detection and reporting on the campus of the University of Calgary and generated a simulation dataset for the LBSN and WSN. Then, results of implementing IPAWL I, IPAWL II, and a stand-alone WSN on the dataset were compared in terms of network energy consumption and message transmission latency. Results demonstrated a 42% reduction in energy consumption in IPAWL I and 33% in IPAWL II. Moreover, a significant reduction of time latency was observed in bigger size networks.

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