Reliable many-to-many routing in wireless sensor networks using ant colony optimisation

Abstract

A wireless Sensor Network (WSN) consists of many simple sensor nodes gathering information, such as air temperature or pollution. Nodes have limited energy resources and computational power. Generally, a WSN consists of source nodes that sense data and sink nodes that require data to be delivered to them; nodes communicate wirelessly to deliver data between them. Reliability is a concern as, due to energy constraints and adverse environments, it is expected that nodes will become faulty. Thus, it is essential to create fault-tolerant routing protocols that can recover from faults and deliver sensed data efficiently. Often studied are networks with a single sink. However, as applications become increasingly sophisticated, WSNs with multiple sources and multiple sinks become increasingly prevalent but the problem is much less studied. Unfortunately, current solutions for such networks are heuristics based on specific network properties, such as number of sources and sinks. It is beneficial to develop efficient (fault-tolerant) routing protocols, independent of network architecture. As such, the use of meta heuristics are advocated. Presented is a solution for efficient many-to-many routing using the meta heuristic Ant Colony Optimisation (ACO). The contributions are: (i) a distributed ACObased many-many routing protocol, (ii) using the novel concept of beacon ants, a fault-tolerant ACO-based routing protocol for many-many WSNs and (iii) demonstrations of how the same framework can be used to generate a routing protocol based on minimum Steiner tree. Results show that, generally, few message packets are sent, so nodes deplete energy slower, leading to longer network lifetimes. The protocol is scalable, becoming more efficient with increasing nodes as routes are proportionally shorter compared to network size. The fault-tolerant variant is shown to recover from failures while remaining efficient, and successful at continuously delivering data. The ACO-based framework is used to create Steiner Trees in WSNs, an NP-hard problem with many potential applications. The ACO concept provides the basis for a framework that enables the generation of efficient routing protocols that can solve numerous problems without changing the ACO concept. Results show the protocols are scalable, efficient, and can successfully deliver data in numerous different topologies