Ant-based load balancing in telecommunications networks
Adaptive Behavior
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
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The ant colony optimization meta-heuristic
New ideas in optimization
Ad Hoc Wireless Networks: Protocols and Systems
Ad Hoc Wireless Networks: Protocols and Systems
Mobile ad hoc networking and the IETF
ACM SIGMOBILE Mobile Computing and Communications Review
A Novel Routing Algorithm for Ad Hoc Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
ARA - The Ant-Colony Based Routing Algorithm for MANETs
ICPPW '02 Proceedings of the 2002 International Conference on Parallel Processing Workshops
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Performance analysis of the AntNet algorithm
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysis of various swarm-based & ant-based algorithms
ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
Towards practical attacker classification for risk analysis in anonymous communication
CMS'06 Proceedings of the 10th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
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A mobile ad-hoc network (MANET) is a collection of mobile nodes which communicate over radio. These networks have an important advantage, they do not require any existing infrastructure or central administration. Therefore, mobile ad-hoc networks are suitable for temporary communication links. This flexibility, however, comes at a price: communication is difficult to organize due to frequent topology changes.The Ant-Colony-Based Routing Algorithm (ARA) is highly adaptive, efficient and scalable. It is based on ant algorithms which are a class of swarm intelligence. Ant algorithms try to map the solution capability of ant colonies to mathematical and engineering problems.In this paper we present some extensions to the basic idea and show through simulation results the performance gain and compare it with AODV and DSR.