PROLONGING STABILITY AND ENERGY CONSERVATION OF CDS-BASED WSN USING NATURE-INSPIRED TECHNIQUES

Abstract

Wireless Sensor Networks is a collection of tiny, battery-operated but smart sensors in a distributed environment for sensing tasks. Being the foundation of Internet-of-Things (IoT), the battery powered nodes in WSN are eligible to Energy Constraints. As the Energy is consumed during the communication in a WSN, this makes construction of a large-scaled and efficient WSN a difficult task. A popular technique for regulation the energy costs and to prolong the lifespan of a wireless sensor network is Clustering. “Clusters” consist of a Cluster-Head and Border Nodes (or Edge Nodes), where all Cluster-Heads are conjoined together to aggregate and deliver data to the Base Station (or Sink). The connected Cluster-Heads form a multi-hop Virtual-Backbone, using which any message can be sent from any source to any destination, directly or indirectly. As there is no predefined physical backbone infrastructure, a virtual backbone can be formed by constructing a Connected Dominating Set (CDS). In order to reduce the Energy costs of a WSN, focus remains on constructing a Minimum CDS (MCDS). However, construction of a minimum connected dominating set falls under the set of NP-Hard problems. With the advancement of various soft computing techniques, nature-inspired algorithms have shown much promise to resolve many optimization problems. Concentration is focused on using such algorithms (Artificial Bee Colony, & Grey-Wolf Optimizer) to solve Energy-Constraints in construction of a CDS to prolong the stability and form even Cluster-Heads (Dominator Nodes). For confirmation of results obtained, they are compared with the previously researched algorithms and proving that with tweaks in fitness function and choosing appropriate nature-inspired optimization algorithm, better results can be found.