An energy efficient clustering and routing design using cross layer architecture to enhance network lifetime

Abstract

Small, low-cost sensor devices have been developed as a result of recent advancements in wireless communication and embedded microprocessors. A network that is made up of several tiny sensors that are dispersed throughout a geographical area and are either fixed or randomly placed is called WSN (Wireless Sensor Networks).Various activities of sensors include sensing, data processing, and communication. They sense the environment within their ranges and send the information to one another using wireless media and a multi-hop technique. In contrast to the low-end, the data is finally collected at sinks or base stations, which have plenty of memory, energy, and processing capacity sensor nodes. Studies in the vicinity of Sensor Networks (WSNs) have experienced an explosive boom over the last decade because of advances in electronics and wireless technologies. Wireless Sensor Networks are used to monitor the physical quantities (consisting of temperature, humidity, pressure, sound,etc.) and to offer controls accordingly. Army (army command, surveillance, and targeting, combat harm assessment), habitat preservation (woodland fire detection, flood detection, precision agriculture), domestic automation (automated control of home equipment, home safety), and many other uses use WSNs. smart building electricity management, fitness monitoring, aged care, assistive technology, activity detection, interior localization, security, and other WSN applications encompass smart campus monitoring. commercial systems and large campuses are common in emerging countries like India (along with schools, universities, hospitals, and so forth.) are a chief source of high electricity consumption due to careless utilization of electricity. This research is divided into two parts: network lifespan maximization and clustering, as well as route optimization. The Energy Efficient Clustering and Routing Optimization model, which employs a cross-layer architecture for a network of heterogeneous devices, is first developed (EECRO). In this concept, the physical layer is employed to obtain channel gain information. At the MAC layer, for the communication amongst Intra and intercluster, the TDMA-based technique is used. Furthermore, optimization of clustering and routing are discussed to achieve a better balance between reducing the Cluster head power, improving the coverage time, and increasing the longevity of the sensor network. Studies were carried out to determine how well EECRO outperforms in comparison to the prevailing model in terms of lowering the overhead of routing, communication and increasing the longevity of WSNs. EECRO outperforms the present paradigm significantly. In the second part of the work, we create a model when sensor node location is unknown, the EE-NCT (Energy Efficient xi model for maximizing network coverage time) is a non-deterministic model that aids in enhancing network coverage time. The non-deterministic paradigm makes optimization challenging because node placement is random. This is also done utilizing a routing-based clustering technique and tracking the location of sensor nodes. The models proposed in this research are evaluated by considering some constraints, such as the first node failure, 75 percent node failure, and network connectivity loss, as well as parameters like energy consumption and average, failed nodes are finally recommended.