ENHANCING COLLABORATIVE PEER-TO-PEER SYSTEMS USING RESOURCE AGGREGATION AND CACHING: A MULTI-ATTRIBUTE RESOURCE AND QUERY AWARE APPROACH

Resource-rich computing devices, decreasing communication costs, and Web 2.0 technologies are fundamentally changing the way distributed applications communicate and collaborate. With these changes, we envision Peer-to-Peer (P2P) systems that will allow for the integration and collaboration of peers with diverse capabilities to a virtual community thereby empowering it to engage in greater tasks beyond what can be accomplished by individual peers, yet are beneficial to all the peers. Collaborations involving application-specific resources and dynamic quality of service goals will stress current P2P architectures that are designed for best-effort environments with pair-wise interactions among nodes with similar resources. These systems will share a variety of resources such as processor cycles, storage capacity, network bandwidth, sensors/actuators, services, middleware, scientific algorithms, and data. However, very little is known about the specific characteristics of real-world resources and queries as well as their impact on resource aggregation in these collaborative P2P systems. We developed resource discovery, caching, and distributed data fusion solutions that are more suitable for collaborative P2P systems while characterizing real-world resource, query, and user behavior. The contributions of this research are: (1) a detailed analysis of real-world resource, query, and user characteristics and their impact on resource discovery solutions, (2) a tool to generate large synthetic traces of multi-attribute resources and range queries