Energy-efficient routing is an extremely critical issue in unattended, tiny and battery equipped Wireless Sensor Networks (WSNs). Clustering the network is a promising approach for energy aware routing in WSN, as it has a hierarchical structure. The Connected Dominating Set (CDS) is an appropriate and prominent approach for cluster formation. This paper proposes an Energy-efficient Self-load Balanced Clustering algorithm (SLBC) for routing in WSN. SLBC has two phases: The first phase clusters the network by constructing greedy connected dominating set and the nodes are evenly distributed among them, using the defined parent fitness cost. The second phase performs data manipulations and new on-demand re-clustering. The efficiency of the proposed algorithm is analysed through simulation study. The obtained results show that SLBC outperforms than the recent algorithms like GSTEB and DGA-EBCDS in terms of network lifetime, CDS size, load dissemination, and efficient energy utilization of the network.

Wireless sensor networks (WSNs) consist of a large number of tiny sensors with sensing, processing and transmission capabilities. Reducing energy consumption of nodes is one of the major objectives in the design of wireless sensor networks, as sensors have low power batteries. As data collection is the primary objective of WSNs and it consumes more energy, energy-efficient routing is a prominent solution to reduce the sensors energy consumption. This paper proposes an Energy-efficient and Load Distributed Clustering Algorithm (ELDCA) for routing in dense wireless sensor networks to reduce and distribute the sensors’ energy consumption. The network is divided into number of virtual congruent square grids of defined sizes. The algorithm constructs optimal and load balanced clusters at every inner crossing point of grid cells using defined cluster fitness value. As early energy depletion is a major design issue in clustering protocols, the proposed algorithm provides a local substitution for energy suffering clusterheads (CHs). To prove the excellence of the proposed algorithm, extensive simulation experiments are performed under different network scenario. The results are compared with latest routing algorithms in terms of network lifetime, energy dissemination, and energy utilization.