Swarm intelligence, as demonstrated by natural biological swarms, exhibits numerous powerful features that are desirable in many engineering systems, such as communication networks. In addition, new paradigms for designing autonomous and scalable systems may result from analytically understanding and extending the design principles and operations inherent in intelligent biological swarms. A key element of future design paradigms will be emergent intelligence - simple local interactions of autonomous swarm members, with simple primitives, giving rise to complex and intelligent global behavior. Communication network management is becoming increasingly difficult due to the increasing network size, rapidly changing topology, and complexity. A new class of algorithms, inspired by swarm intelligence, is currently being developed that can potentially solve numerous problems of such networks. These algorithms rely on the interaction of a multitude of simultaneously interacting agents. A survey of such algorithms and their performance is presented here.

http://staff.washington.edu/paymana/papers/globecom01_2.pdf

Swarm intelligence for routing in communication networks

Applications of agent technology in communications: a review

In this paper we focus on the network routing problem, and survey swarm intelligent approaches for its efficient solution, after a brief overview of power-aware routing schemes, which are important in the network examples outlined above

https://faculty.washington.edu/paymana/papers/aiaa01_2.pdf

Adaptive routing in wireless communication networks using swarm intelligence

Swarm intelligence forms the core of a new class of algorithms inspired by the social behavior of insects that live in swarms. Its attractive features include adaptation, robustness and a distributed, decentralized nature, rendering swarm-based algorithms well-suited for routing in wireless or satellite networks, where it is difficult it implement centralized network control. We propose one such routing algorithm, dubbed adaptive swarm-based distributed routing (adaptive-SDR), which is scalable, robust and suitable to handle large amounts of network traffic, while minimizing delay and packet loss.

https://faculty.washington.edu/paymana/papers/wcci02_1.pdf

Adaptive-SDR: adaptive swarm-based distributed routing

: This report describes the current state of research in the area known as Swarm Intelligence. Swarm Intelligence relies upon stigmergic principles in order to solve complex problems using only simple agents. Swarm Intelligence has been receiving increasing attention over the last 10 years as a result of the acknowledgement of the success of social insect systems in solving complex problems without the need for central control or global information. In swarm-based problem solving, a solution emerges as a result of the collective action of the members of the swarm, often using principles of communication known as stigmergy. The individual behaviours of swarm members do not indicate the nature of the emergent collective behaviour and the solution process is generally very robust to the loss of individual swarm members. This report describes the general principles for swarm-based problem solving, the way in which stigmergy is employed, and presents a number of high level algorithms that have proven utility in solving hard optimization and control problems. Useful tools for the modelling and investigation of swarm-based systems are then briefly described. Applications in the areas of combinatorial optimization, distributed manufacturing, collective robotics, and routing in networks (including mobile ad hoc networks) are then reviewed. Military and security applications are then described, specifically highlighting the groups that have been or continue to be active in swarm research. The final section of the document identifies areas of future research of potential military interest. A substantial bibliography is provided in support of the material provided in the report.

Expert Assessment of Stigmergy: A Report for the Department of National Defence

Networks today are growing continuously complex, with new kinds of services being included and heterogeneous networks interworking as a whole. Telecommunications networks in particular have become truly global networks, consisting of a variety of national and regional networks, both wired and wireless. Consequently, the management of telecommunications networks is becoming an increasingly complex task, as size and complexity constitute critical requirements that have to be met. Decentralized approaches to network management are currently being discussed, as is has become evident that central solutions cannot cope with scalability issues. Mobile agent technology in particular is being examined as a new distributed system and network paradigm. One vital issue in telecommunications networks management is load balancing, as it allows to efficiently use the network to capacity and avoid overload situations. In this paper, we will examine swarming intelligence of mobile agents as a basis for the development of a decentralized load balancing mechanism in telecommunications networks. Various strategies for swarming intelligence will be evaluated and compared to conventional approaches with a simulative approach.

http://staff.washington.edu/paymana/swarm/lipperts99-isas.pdf

Steffen Lipperts

Papers

Mobile Agents in Telecommunications Networks – A Simulative Approach to Load Balancing