Towards improved clustering and routing protocol for wireless sensor networks

Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multi-hop communication and a shorter transmission range. Clustering and routing are treated separately in different solutions and, therefore, efficient solutions in terms of energy consumption and network lifetime could not be provided. This work focuses data collection from IoT-nodes distributed in an area and connected through WSN. We address two interlinked issues, clustering and routing, for large-scale IoT-based WSN and propose an improved clustering and routing protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. During process of clustering, cluster-heads are selected in such a way that provide fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop-count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

This research article published by Cogent Engineering, 2020Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node’s energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an EnhancedLow-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigne

Enhanced Message-Passing Based LEACH Protocol for Wireless Sensor Networks

This paper proposes a distributed energy-efficient clustering protocol for wireless sensor networks (WSNs). Based on low-energy adaptive clustering hierarchy (LEACH) protocol, the proposed LEACH-eXtended Message-Passing (LEACH-XMP) substantially improves a cluster formation algorithm, which is critical for WSN operations. Unlike the previous approaches, a realistic non-linear energy consumption model is considered, which renders the clustering optimization highly nonlinear and challenging. To this end, a state-of-the-art message-passing approach is introduced to develop an efficient distributed algorithm. The main benefits of the proposed technique are its inherent nature of a distributed algorithm and the saving of computational load imposed for each node. Thus, it proves useful for a practical deployment. In addition, the proposed algorithm rapidly converges to a very accurate solution within a few iterations. Simulation results ensure that the proposed LEACH-XMP maximizes the network lifetime and outperforms existing techniques consistently