Efficient Content Location Using Interest-Based Locality In Peer-To-Peer Systems

Locating content in decentralized peer-to-peer systems is a challenging problem. Gnutella, a popular file-sharing application, relies on flooding queries to all peers. Although flooding is simple and robust, it is not scalable. In this paper, we explore how to retain the simplicity of Gnutella, while addressing its inherent weakness: scalability. We propose a content location solution in which peers loosely organize themselves into an interest-based structure on top of the existing Gnutella network. Our approach exploits a simple, yet powerful principle called interest-based locality, which posits that if a peer has a particular piece of content that one is interested in, it is very likely that it will have other items that one is interested in as well. When using our algorithm, called interest-based shortcuts, a significant amount of flooding can be avoided, making Gnutella a more competitive solution. In addition, shortcuts are modular and can be used to improve the performance of other content location mechanisms including distributed hash table schemes. We demonstrat

The Case for Cooperative Networking

... CoopNet) where end-hosts cooperate to improve network performance perceived by all. In CoopNet, cooperation among peers complements traditional client-server communication rather than replacing it. We focus on the Web flash crowd problem and argue that CoopNet offers an effective solution. We present an evaluation of the CoopNet approach using simulations driven by traffic traces gathered at the MSNBC website during the flash crowd that occurred on September 11, 2001

A Third-Party Value-Added Network Service Approach to Reliable Multicast

We propose a third-party value-added services framework for enhancing the performance of reliable multicast protocols. In this framework, a value-added service provider will place servers called waypoints throughout ISPs ’ networks. Waypoints run a fully distributed, dynamic algorithm to determine which multicast groups to join. Having joined a group, a waypoint participates in the error recovery protocol, supplying repairs to receivers. From the application’s perspective, waypoints appear to be additional application endpoints in the network. Waypoints seamlessly interoperate with current reliable multicast algorithms with only a minor change to receivers and no changes to routers. In our implementation, receivers and waypoints use STORM, a structure-based error recovery protocol. The waypoint recovery service is not limited to one error recovery protocol, and can be extended to enhance other reliable multicast protocols. Results from simulation experiments are presented to evaluate the potential benefits of theproposed scheme. We find that when multicast group members are isolated from each other, a waypoint recovery service can significantly enhance receivers ’ performance.

Dealer: Dynamic Request Splitting for Performance-Sensitive Applications in Multi-Cloud Environments

Enterprises are increasingly deploying their applicationsin the cloud given the cost-saving advantages,and the potential to geo-distribute applications to ensureresilience and better service experience. However,a key unknown is whether it it is feasible to meet thestringent response time requirements of enterprise applicationsusing the cloud. We make several contributions.First, we show through empirical measurementstudies that (i) there is significant short-term variabilityin application workload and response times of individualcomponents; however (ii) the response timesof the same component in different data-centers are oftenuncorrelated. This leads us to argue that there arepotential latency savings if work related to a poorlyperforming component is dynamically reassigned toa replica in a remote data-center. We leverage thisinsight to build a system that we term Dealer whichfor each component, dynamically splits transactionsamong its replicas in different data-centers. In doingso, Dealer seeks to minimize user response times, andtakes component performance, as well as intra-datacenterand inter-data-center communication latenciesinto account. We have implemented Dealer in a waythat it can be added to any multi-tier application. Evaluationsof our approach on two multi-tier applicationson actual Azure cloud deployments indicates the importanceand feasibility of our mechanisms. For instance,the 90%ile of application response times couldbe reduced by as much as 6 times under natural clouddynamics