Research Area:  Wireless Sensor Networks

Abstract:

Successful behavioural and communication strategies of biotic communities can serve as an inspiration for algorithms used to design, manage, and control real-world networks. Many natural systems exhibit complex yet efficient behaviours. Some animal communities display sophisticated behavioural patterns arising from fairly simple activities of their members. The behaviours of ant colonies, swarms of bees, schools of fish, and even some human communities, can be seen as properties of distributed systems consisting of individual agents performing straightforward actions and communicating using simple strategies. Formally, the behaviour of such communities can be modelled as a massive yet intuitive multiagent system . The ensuing models can be applied to a variety of networking problems. This chapter looks at routing in wireless sensor networks and mobile ad-hoc networks as tasks that bear similarities to communication in biotic societies and swarms, and underlines the role of propagation phenomena in routing . It summarizes the basic principles of swarm intelligence and evolutionary computing and reviews recent advances in biologically-inspired network routing.

Keywords:  
Particle Swarm Optimization
Wireless Sensor Network
Network Lifetime
Swarm Intelligence
Mobile Sink

Author(s) Name:   Pavel Krömer & Petr Musilek

Publisher name:  Springer

DOI:  10.1007/978-3-319-15916-4_7

Volume Information:  

Paper Link:   https://link.springer.com/chapter/10.1007/978-3-319-15916-4_7