EARM: An Efficient and Adaptive File Replication with Consistency Maintenance in P2P Systems

In p2p systems, file replication and replica consistency maintenance are most widely used techniques for better system performance. Most of the file replication methods replicates file in all nodes or at two ends in a clientserver query path or close to the server, leading to low replica utilization, produces unnecessary replicas and hence extra consistency maintenance overhead. Most of the consistency maintenance methods depends on either message spreading or structure based for update message propagation without considering file replication dynamism, leading to inefficient file update and outdated file response. These paper presents an Efficient and Adaptive file Replication and consistency Maintenance (EARM) that combines file replication and consistency maintenance mechanism that achieves higher query efficiency in file replication and consistency maintenance at a low cost. Instead of accepting passively file replicas and updates, each node determines file replication and update polling by adapting to time-varying file query and update rates. Simulation results demonstrate the effectiveness of EARM in comparison with other approaches

Improving the Asymmetric TSP by Considering Graph Structure

Recent works on cost based relaxations have improved Constraint Programming (CP) models for the Traveling Salesman Problem (TSP). We provide a short survey over solving asymmetric TSP with CP. Then, we suggest new implied propagators based on general graph properties. We experimentally show that such implied propagators bring robustness to pathological instances and highlight the fact that graph structure can significantly improve search heuristics behavior. Finally, we show that our approach outperforms current state of the art results.Comment: Technical repor

Constraint-based reachability

Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.Comment: In Proceedings Infinity 2012, arXiv:1302.310