Adaptive Routing Protocol for Lifetime Maximization in Multi-Constraint Wireless Sensor Networks

Abstract

Routing in wireless sensor networks plays a crucial role in deploying and managing an efficient and adaptive network. Ensuring efficient routing entails an ever-increasing necessity for optimized energy consumption and reliable resource management of both the sensor nodes and the overall sensor network. An efficient routing solution is characterized by its ability to increase network lifetime, enhance efficiency, and ensure the appropriate quality of service. Therefore, the routing protocols need to be designed with an ultimate objective by considering and efficiently managing many characteristics and requirements, such as fault tolerance, scalability, production costs, and others. Unfortunately, many of the existing solutions lead to higher power consumption and communication control overheads, which not only increase network congestion but also decrease network lifetime. In addition, most of these protocols consider a limited number of criteria, in contrast to the complexity and the evolution of WSNs. This paper presents a new adaptive and dynamic multi-criteria routing protocol. Our protocol operates in multi-constraint environments, where most of the current solutions fail to monitor successive and continuous changes in network state and user preferences. This approach provides a routing mechanism, which creates a routing tree based on the evaluation of many criteria. These criteria can cover the topological metrics of neighboring nodes (the role of the nodes in intracommunications, connections between different parts of the network, etc.), the estimated power consumption to reach each direct neighbor, the path length (number of hops to the sink), the remaining energy of individual sensor nodes, and others. These criteria are controlled and supervised dynamically through a detection scheme. In addition, a dynamic selection mechanism, based on multi-attribute decision-making methods, is implemented to build and update the routing tree. In response to changes in the network state, user preferences, and application-defined goals, the election mechanism provides the best routing neighbor between each node and the sink.