Data Network complexity will increase dramatically over the next 5 years. Ad-hoc, active and parasitic paradigms will all make the already onerous task of network management increasingly problematic. An algorithm for managing data networks based on bacterial colony behaviour is discussed, offering automated management of essential tasks such as software distribution, load balancing, and quality of service. The algorithm is tested by using a log of real network requests to generate simulated network load. It is concluded that applying adaptive management could be the ideal approach to managing the behaviour of data networks of the future.
|Number of pages||6|
|Journal||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - 2001|
- Artificial life
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture