Fuzzy Cost Modeling for Peer-to-Peer Systems

The objective of query optimizers is to select a good execution plan for a given query. In a distributed system, it is crucial for a query optimizer to have effective remote cost estimation in order to make a satisfactory decision. There are two categories of cost estimation models: static cost model and dynamic cost model. Unfortunately, these models suffer from several limitations. First, the static cost model is not capable of reflecting real-time situations. Second, dynamic cost model is not scalable due to its extensive probe queries. Third, these models are not designed for ad-hoc systems such as P2P, since the dynamism of peers is not taken into consideration. In this paper, we firstly propose a progressive “push-based” remote cost monitoring approach. We derive a generic static cost model from conventional static approach. Agents will be sent to remote hosts with a generic cost model and epsilons (ε) indicating magnitude of cost change, i.e., percentage of coefficient change. An update will be sent (push) to original host once the magnitude of the cost change exceeds ε. Second, we introduce a fuzzy cost evaluation metric in additional to traditional evaluation criteria for handling the dynamism of P2P systems. This metric gives a confident measurement of a peer’s reliability. Our contributions have successfully addressed some of the issues concerning the cost modeling in environment of dynamic peers.