CGrAnt: a swarm intelligence-based routing protocol for delay tolerant networks

Authors:
Ana Cristina Barreiras Kochem Vendramin;Anelise Munaretto;Myriam Regattieri de Biase da Silva Delgado;Aline Carneiro Viana
Affiliations:
Federal Technological University of Parana, Curitiba, Brazil;Federal Technological University of Parana, Curitiba, Brazil;Federal Technological University of Parana, Curitiba, Brazil;Inventeurs du monde numérique (INRIA), Saclay, France
Venue:
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Year:
2012

Citing 10
Cited 0

The ant colony optimization meta-heuristic

New ideas in optimization
A delay-tolerant network architecture for challenged internets

Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Knowledge-based solution to dynamic optimization problems using cultural algorithms

Knowledge-based solution to dynamic optimization problems using cultural algorithms
Social network analysis for routing in disconnected delay-tolerant MANETs

Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Working day movement model

Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
On ant routing algorithms in ad hoc networks with critical connectivity

Ad Hoc Networks
Ant-based adaptive message forwarding scheme for challenged networks with sparse connectivity

MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
GrAnt: Inferring best forwarders from complex networks' dynamics through a greedy Ant Colony Optimization

Computer Networks: The International Journal of Computer and Telecommunications Networking
Ant system: optimization by a colony of cooperating agents

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
DTN: an architectural retrospective

IEEE Journal on Selected Areas in Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new routing protocol for Delay Tolerant Networks (DTNs), based on a distributed swarm intelligence approach. The protocol is called Cultural Greedy Ant (CGrAnt), as it uses a Cultural Algorithm (CA) and a greedy version of the Ant Colony Optimization (ACO) metaheuristic. The term greedy implies the use of a deterministic transition rule to exploit previously found good paths or explore new paths by selecting, from among a set of candidates, the most promising message forwarders. CGrAnt chooses each next node toward the message destination based on pheromone concentration (i.e., global information) whenever it is available. However, as the pheromone is not always available due to connectivity partitions, local information (i.e., heuristic function) captured from DTN nodes also supports a routing decision. Specific metrics and information gathered from the evolution are stored in Situational, Domain, and Historical Knowledge. The knowledge composes the CA's belief space, which is used to guide and improve the search. CGrAnt is compared with two DTN routing protocols (Epidemic and PROPHET) in an activity-based scenario. The results show that CGrAnt achieves a higher delivery ratio and lower byte redundancy than Epidemic and PROPHET.