\chapter*{ABSTRACT}
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Over the last few years, Wireless Sensors Networks (WSNs) witness tremendous growth in every sphere of life due to low-cost and multi-functional capabilities which make them functional even in diverse and complex applications such as habitant monitoring, enemy surveillance, or smart farming to name a few. Latest advancements in electronics and wireless communication led the development of highly capable Sensor Nodes (SNs) that can operate in most adverse and  dynamic environment for long duration. Every SN is equipped with a transceiver and a processing unit backed with a power supply unit having limited battery life, which  may cause premature exhaust of the network, due to excessive usage. As manual re-charging of batteries or human intervention is not possible in most of applications after deployments, efficient use of the residual energy becomes a tough challenge to support network for a longer duration.

Researchers around the world are heavily involved in designing better and efficient SNs  however, network life of a WSN can also be extended by devising energy-efficient routing techniques. Cluster based hierarchical approach prove to be an efficient way to save network energy, which helps to increase network life by effectively utilize the node energy thus support dynamic WSNs environment for long duration. Further, Computational Intelligence (CI) based metaheuristic like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA)  and more recently, Artificial Bee Colony (ABC), have been used extensively as population based optimization techniques for designing energy-efficient routing protocols in WSNs.

In this research work, an energy-efficient hierarchical routing protocol \emph{BeeSwarm}, is presented which is based on a nature inspired improved Artificial Bee Colony \((iABC)\) metaheuristic. The proposed protocol will consist of three phases namely 1. BeeCluster, 2. BeeSearch and 3. BeeCarrier, for optimal CH selection, optimal route discovery and finally data transmission respectively. The proposed protocol is extensively evaluated with other existing well known routing protocols on \emph{Nature Inspired Tool for Sensor Simulation} (NITSS), a simulation tool specially developed to evaluate routing protocols for WSNs with different scenarios. Simulation results prove that \emph{BeeSwarm} outperforms other existing routing protocols over various performance metric and establish it as a better energy-efficient routing protocol among its peers even for scalable WSNs.
