As-Soon-As-Possible Top-k Query Processing in P2P Systems

International audienceTop-k query processing techniques provide two main advantages for unstructured peer-to-peer (P2P) systems. First they avoid overwhelming users with too many results. Second they reduce significantly network resources consumption. However, existing approaches suffer from long waiting times. This is because top-k results are returned only when all queried peers have finished processing the query. As a result, query response time is dominated by the slowest queried peer. In this paper, we address this users' waiting time problem. For this, we revisit top-k query processing in P2P systems by introducing two novel notions in addition to response time: the stabilization time and the cumulative quality gap. Using these notions, we formally define the as-soonas-possible (ASAP) top-k processing problem. Then, we propose a family of algorithms called ASAP to deal with this problem. We validate our solution through implementation and extensive experimentation. The results show that ASAP significantly outperforms baseline algorithms by returning final top-k result to users in much better times

Probabilistic Identification for Hard to Classify Protocol

Abstract. With the growing use of protocols obfuscation techniques, protocol identification for Q.O.S enforcement, traffic prohibition, and intrusion detection has became a complex task. This paper address this issue with a probabilistic identification analysis that combines multiples advanced identification techniques and returns an ordered list of probable protocols. It combines a payload analysis with a classifier based on several discriminators, including packet entropy and size. We show with its implementation, that it overcomes the limitations of traditional port-based protocol identification when dealing with hard to classify protocol such as peer to peer protocols. We also details how it deals with tunneled session and covert channel