A distributed routing algorithm for mobile wireless networks
Wireless Networks
A routing protocol for packet radio networks
MobiCom '95 Proceedings of the 1st annual international conference on Mobile computing and networking
Multicluster, mobile, multimedia radio network
Wireless Networks
The performance of query control schemes for the zone routing protocol
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
A performance comparison of multi-hop wireless ad hoc network routing protocols
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
Distributed fault location in networks using mobile agents
IATA '98 Proceedings of the second international workshop on Intelligent agents for telecommunication applications
Dynamic Agent Domains in Mobile Agent Based Network Management
ICN '01 Proceedings of the First International Conference on Networking-Part 2
Adaptive clustering for mobile wireless networks
IEEE Journal on Selected Areas in Communications
A mobility-based framework for adaptive clustering in wireless ad hoc networks
IEEE Journal on Selected Areas in Communications
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A Mobile ad-hoc network is a multihop wireless network, where nodes communicate with each other without any pre-deployed infrastructure. The most important problem on such dynamic networks is to find routing algorithms well performing in most cases. Cluster based algorithms are among the most effective and scaleable approaches. Up till now creation and maintenance clusters were mostly based on basic heuristic methods. Deploying mobile agents has several advantages in the ad-hoc environment due to their flexible, robust and autonomous nature, and their use seems promising for the clustering problem as well. In our proposed architecture every cluster has a clustering agent that is capable of making membership modification decisions, transferring nodes and splitting or merging clusters. Communication is used only between neighbouring agents to reduce the signalling overhead. Clustering decisions can be based on several network parameters modified by an adaptation mechanism to provide adequate performance even under dynamic conditions.