GloMoSim: a library for parallel simulation of large-scale wireless networks
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Evaluation of Peer-to-Peer Network Content Discovery Techniques over Mobile Ad Hoc Networks
WOWMOM '05 Proceedings of the Sixth IEEE International Symposium on World of Wireless Mobile and Multimedia Networks
Routing in Ad Hoc Networks of Mobile Hosts
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
Free Search with Adaptive Differential Evolution Exploitation and Quantum-Inspired Exploration
Journal of Network and Computer Applications
BEEINFO: data forwarding based on interest and swarm intelligence for socially-aware networking
Proceedings of the 19th annual international conference on Mobile computing & networking
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In this work, we present a P2PBA algorithm that refers to a peer-to-peer file searching method, which uses the bees algorithm. The proposed algorithm has been designed with an aim towards providing an efficient peer-to-peer (P2P) file search in mobile ad hoc networks (MANETs). With reference to Li et al. (2004) and Gerla and Lindemann (2005) it has been observed that the implementation of P2P file sharing system on MANETs is quite tricky to implement as compared to that on a wired network. With the advent of swarm intelligence, the P2P file sharing methodology not only found an optimized search process involving a more selective node tracing, but it also proved to improve the time efficiency and robustness of the sharing mechanism. The P2P file searching system implementation, particularly in a network of mobile nodes, poses: (a) the percentage network area scanned and (b) the selective file retrieval from a set of file bearing nodes as the biggest challenges. Managing nodes scattered over a large terrain is not easy. Node connectivity and file information become more volatile as the network area increases. Probability of retrieving a file from a profitable source is also a yardstick to determine how good the file retrieval algorithm is. This algorithm referred to as P2PBA implements the P2P file searching process using the bee algorithm (Pham et al., 2006b; Wedde and Farooq, 2005) and aims at solving these two challenges. This scheme of swarm-based intelligence, which is based on the foraging behavior of honey bees, optimizes the search process selectively hunting for more promising honey sources and scans a sizeable area in a more comprehensive manner. Following a description of the proposed algorithm, this paper finally presents the simulation results for the network against various specified parameters. The simulation results show that our algorithm proposes to make file searching much more efficient and improves the statistics against the posed challenges.