Abstract not found

Despite the abundance of frequently changing information, the Web lacks a publish-subscribe interface for delivering updates to clients. The use of naïve polling for detecting updates leads to poor performance and limited scalability as clients do not detect updates quickly and servers face high loads imposed by active polling. This paper describes a novel publish-subscribe system for the Web called Corona, which provides high performance and scalability through optimal resource allocation. Users register interest in Web pages through existing instant messaging services. Corona monitors the subscribed Web pages, detects updates efficiently by allocating polling load among cooperating peers, and disseminates updates quickly to users. Allocation of resources for polling is driven by a distributed optimization engine that achieves the best update performance without exceeding load limits on content servers. Large-scale simulations and measurements from PlanetLab deployment demonstrate that Corona achieves orders of magnitude improvement in update performance at a modest cost. 1

While current Peer-to-Peer (P2P) systems facilitate static file sharing, newly-developed applications demand that P2P systems be able to manage dynamically-changing files. Maintaining consistency between frequently-updated files and their replicas is a fundamental reliability requirement for a P2P system. In this paper, we present SCOPE, a structured P2P system supporting consistency among a large number of replicas. By building a replica-partition-tree (RPT) for each key, SCOPE keeps track of the locations of replicas and then propagates update notifications. Our theoretical analyses and experimental results demonstrate that SCOPE can effectively maintain replica consistency while preventing hot-spot and node-failure problems. Its efficiency in maintenance and failure-recovery is particularly attractive to the deployment of large-scale P2P systems.

Abstract—Over the past few years, peer-to-peer (P2P) systems have rapidly grown in popularity and have become a dominant means for sharing resources. In these systems, load balancing is a key challenge because nodes are often heterogeneous. While several load-balancing schemes have been proposed in the literature, these solutions are typically ad hoc, heuristic based, and localized. In this paper, we present a general framework, HiGLOB, for global load balancing in structured P2P systems. Each node in HiGLOB has two key components: 1) a histogram manager maintains a histogram that reflects a global view of the distribution of the load in the system, and 2) a load-balancing manager that redistributes the load whenever the node becomes overloaded or underloaded. We exploit the routing metadata to partition the P2P network into nonoverlapping regions corresponding to the histogram buckets. We propose mechanisms to keep the cost of constructing and maintaining the histograms low. We further show that our scheme can control and bound the amount of load imbalance across the system. Finally, we demonstrate the effectiveness of HiGLOB by instantiating it over three existing structured P2P systems: Skip Graph, BATON, and Chord. Our experimental results indicate that our approach works well in practice. Index Terms—Peer-to-peer, framework, load balancing, histogram, DHT, overlay network. Ç

We propose a new overlay network, called Generic Identifier Network (GIN), for collaborative nodes to share objects with transactions across affiliated organizations by merging the organizational local namespaces upon mutual agreement. Using local namespaces instead of a global namespace can avoid excessive dissemination of organizational information, reduce maintenance costs, and improve robustness against external security attacks. GIN can forward a query with an (1) latency stretch with high probability and achieve high performance. In the absence of a complete distance map, its heuristic algorithms for self configuration are scalable and efficient. Routing tables are maintained using soft-state mechanisms for fault tolerance and adapting to performance updates of network distances. Thus, GIN has significant new advantages for building an efficient and scalable Distributed Hash Table for modern collaborative applications across organizations. 1.

Abstract—A fundamental challenge of managing mutable data replication in a Peer-to-Peer (P2P) system is how to efficiently maintain consistency under various sharing patterns with heterogeneous resource capabilities. This paper presents a framework for balanced consistency maintenance (BCoM) in structured P2P systems. Replica nodes of each object are organized into a tree for disseminating updates, and a sliding window update protocol is developed to bound the consistency. The effect of window size in response to dynamic network conditions, workload updates and resource limits is analyzed through a queueing model. This enables us to balance availability, performance and consistency strictness for various application requirements. On top of the dissemination tree, two enhancements are proposed: a fast recovery scheme to strengthen the robustness against node and link failures; and a node migration policy to remove and prevent the bottleneck for better system performance. Simulations are conducted using P2PSim to evaluate BCoM in comparison to SCOPE [24]. The experimental results demonstrate that BCoM significantly improves the availability of SCOPE by lowering the discard rate from almost 100 % to 5 % with slight increase in latency.

Abstract — We had previously shown that the average search distance in unstructured peer-to-peer networks having an Erdos-Renyi random graph search topology is minimized when the number of replicas of objects is proportional to the object request probabilities and this results in a minimum search distance is equal to the entropy in object request probabilities minus the logarithm of per-node cache size. In this paper we show that these results also hold for DHT-based peer-to-peer networks that employ prefix-based routing. The advantage of proportional replication in minimizing the search distance adds to the benefits of proportional replication for download time, network resources usage and fairness we have found in our earlier work. In order to show the above result, we generalize a recently proposed replication approach where an object is replicated at nodes with ids adjacent to the id of the node responsible for the object. We show that the average search distance for an object is logarithmically related to the number of replicas of the object in prefix-routingbased DHT systems when the replicas are placed in the manner described. This result can be easily extended to randomized DHTs that make exponential progress to the destination address in O(1) steps. Finally, we generalize the relation between the optimal average search distance and entropy in object request probabilities to any peer-to-peer network with an overlay topology that exhibits exponential expansion regardless of whether the network is structured or unstructured by mapping the search problem in a peer-topeer network to a coding problem. 1.