An efficient and distributed file search in unstructured peer-to-peer networks
Peer-to-peer (P2P) networks are gaining increased attention from both the scientific community and the larger Internet user community. Data retrieval algorithms lie at the center of P2P networks, and this paper addresses the problem of efficiently searching for files in unstructured P2P systems. We propose an Improved Adaptive Probabilistic Search (IAPS) algorithm that is fully distributed and bandwidth efficient. IAPS uses ant-colony optimization and takes file types into consideration in order to search for file container nodes with a high probability of success. We have performed extensive simulations to study the performance of IAPS, and we compare it with the Random Walk and Adaptive Probabilistic Search algorithms. Our experimental results show that IAPS achieves high success rates, high response rates, and significant message reduction.
Abstract In this paper, we investigate the relations between the smallest entry of a doubly stochastic tree matrix associated with a tree and the diameter of the tree, which are used to deal with Merris’s conjecture on the algebraic connectivity and the smallest entries. Further, we present a new upper bound for algebraic connectivity in terms of the smallest entry, which improves Merris’ result.