Energy-Efficient Clustering Algorithms for Edge-Based Wireless Sensor Networks

Abstract

A wireless sensor network (WSN) is a spatially distributed autonomous sensor nodes to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. Sensor nodes’ resources have been a primary concern in designing any wireless sensor network application, since they are limited and non-renewable. Most of the current efforts on sensor network research have limited their design space solely to the sensor nodes themselves. Under such an approach, the burden of achieving complex networking functions all rests upon the sensor nodes. Thus, the search for alternative resources got much attention in sensor networks. Base station is one such resource abundant and constraint-free network component in wireless sensor network. By exploring base station’s capabilities, functional complexities in existing and upcoming algorithms can be simplified. A Base station Assisted Novel Network Design Space (BANDS) is proposed to exploit edge-base-station capabilities to offer new possibilities to meet up-to-minute requirements. Experimental results prove that the proposed work conserves network resources by shifting control overhead from sensor nodes to the base station. Based on the proposed network design space, a Zone-Based Routing Protocol (ZBRP) is introduced to enhance sensor network lifetime. ZBRP uses random back-off timers having communication cost and neighborhood count as primary parameters to select cluster heads for each data forwarding round. From the simulation results, it is observed that the proposed routing protocol improves network lifetime by distributing energy consumption evenly among clusters. To overcome the problems that arise with uneven energy dissipation, a novel Energy-efficient UnEqual Clustering algorithm (EUEC) is proposed. It creates limited and equivalent number of clusters in each level, which allows energy to be consumed evenly among cluster heads. Also, a disjoint multi-hop routing mechanism is proposed to balance network routing load among data forwarding paths. Experimental results prove that the proposed algorithm overcomes hot-spot problem with uniform energy dissipation among clusters and elevates network lifetime. iA novel and extended scale-free clustering technique called, Energy-efficient Hybrid Clustering Mechanism (EHCM) is proposed to overcome hot-spot problem without scalability issues. EHCM creates dynamic number of clusters in different sizes based on sensor node’s location information, which distributes energy dissipation uniformly among sensor nodes. From the simulation results, it is realized that the proposed work achieves hot-spot free network and prolongs network lifetime. Since the number of clusters are generated dynamically, the proposed algorithm is easily scalable.