An Optimized Hierarchal Cluster Formation Approach for Smart Cities

Abstract

A smart city uses Internet of Things (IoT) to enhance the management of many daily routine tasks such as traffic system, energy consumption, and waste collection. The Quality of Service (QoS) of these daily routine tasks are based on an assistive observation system. Wireless Sensors Networks (WSNs) as the key component of IoT are used here to gather data into surveillance subsystems for supporting the decision making. To enhance the collected data management of surveillance subsystems, many clustering techniques are introduced. The low-power adaptive clustering protocol is a key technique of the Internet of Things (IoT). However, this protocol has deterring limitations, especially in the cluster formation step, which negatively affect many nodes. Considering this problem, the current research proposes an Opt-LEACH system that attempts to optimize the low-energy adaptive clustering hierarchy. The proposed system depends on the suitability of residual energy in nodes to cover the communication energy with CHs as a key factor when allocating the node clusters in the first competition. The remaining power and the density of CHs are employed to weight the accepted CHs and adjust the optimized size of clusters in the secondary competition. The impact factor of each candidate member node is applied in the third competition. The simulation results clarify the ability of Opt-LEACH to improve the cluster formation and to enhance communication within clusters. The advantages and efficiency of Opt-LEACH are observed via the increased number of surviving nodes, increased residual energy of nodes and higher network lifetime.