Efficient Data Aggregation Technique for Energy Efficiency in Wireless Sensor Networks

Abstract

The fast-growing Internet of Things (IoT) enabled communications evolved up with smart sensor technologies operable with resource constraint nodes in various field of interests. Since many years typical sensor node functionality usually emerged with the advancement of network requirements in practice. A wireless sensor node is a battery-driven miniature electronic device capable of doing some sort of operation within a specific human inaccessible region. A typical WSN consists of a set of spatially distributed independent sensor nodes well capable of cooperatively monitoring certain activities of human concern including network monitoring, sensing different physical attributes such as heat, pressure, etc. [1]. In a wide-range WSN, a sensor node performs sensing, computation, and communication with a very limited amount of resources which exhibits its potential drawbacks towards extending the network lifetime by conserving energy. However, owing to various potential beneficial aspects, WSN has newline2 newline newlinebecome a prominent area of research and still under the process of advancement where various research challenges as well as endless opportunities explored in various studies [2][3] WSN has a wide variety of applications and also its potential features made it an adaptive communication network.WSN communication and routing plays a crucial role in the effective monitoring of specific environmental factors. The prime operational goal of a typical WSN includes collecting data from the certain environment and forward that to sink node considering optimized communication route.Many investigational studies revealed the matter of fact where it is stated that energy is the prime obstacle which affects the network lifetime and superlative performance of WSN in terms of a data aggregation or cumulative performance. the study of W. R. Heinzelman et al. [9]evolved up with a new paradigm namely clustering which they have applied into designing an energy efficient hierarchical communication protocol (LEACH). There exists a various state of the art studies referred Low Energy Adaptive Clustering Hierarchical Protocol (LEACH) as a baseline to evaluate benchmarking where the studies considered few of the assumptions as similar as LEACH Battery energy consumption is the dominant factor in node aging when the network deployment environment is favorable, and the device is highly reliable. There newline10 newline newlineare several major operations done by sensor nodes, which consume most of battery energy. They include communication, sensing, and data processing. Sensor nodes participate in communications with various purposes depending on applications and network management schemes. In most of the applications, data gathering imposes the most critical communication requirement.The prime aim of the research work is to investigate a better possibility of using hierarchical routing protocols for ensuring optimization of energy conservation in wireless sensor network using Swarm Intelligence (SI newline