The application of structured overlay networks to implement index structures for data-oriented applications such as peer-to-peer databases or peer-to-peer information retrieval, requires highly efficient approaches for overlay construction, as changing application requirements frequently lead to re-indexing of the data and hence (re- )construction of overlay networks. This problem has so far not been addressed in the literature and thus we describe an approach for the efficient construction of data-oriented, structured overlay networks from scratch in a self-organized way. Standard maintenance algorithms for overlay networks cannot accomplish this efficiently, as they are inherently sequential. Our proposed algorithm is completely decentralized, parallel, and can construct a new overlay network with short latency. At the same time it ensures good loadbalancing for skewed data key distributions which result from preserving key order relationships as necessitated by data-oriented applications. We provide both a theoretical analysis of the basic algorithms and a complete system implementation that has been tested on PlanetLab. We use this implementation to support peer-to-peer information retrieval and database applications.

In this paper we show that the topologies of most logarithmic-style P2P systems like Pastry, Tapestry or P-Grid resemble small-world graphs. Inspired by Kleinberg’s small-world model [6] we extend the model of building “routing-efficient ” small-world graphs and propose two new models. We show that the graph, constructed according to our model for uniform key distribution and logarithmic outdegree, will have similar properties as the topologies of structured P2P systems with logarithmic outdegree. Moreover, we propose a novel model of building graphs which support uneven node distributions and preserves all desired properties of Kleinberg’s small-world model. With such a model we are setting a reference base for nowadays emerging P2P systems that need to support uneven key distributions.

We present a decentralized design for a server cluster that supports a single service with response time guarantees. Three distributed mechanisms represent the key elements of our design. Topology construction maintains a dynamic overlay of cluster nodes. Request routing directs service requests towards available servers. Membership control allocates/releases servers to/from the cluster, in response to changes in the external load. We advocate a decentralized approach, because it is scalable, fault-tolerant, and has a lower configuration complexity than a centralized solution. We demonstrate through simulations that our system operates efficiently by comparing it to an ideal centralized system. In addition, we show that our system rapidly adapts to changing load. We found that the interaction of the various mechanisms in the system leads to desirable global properties. More precisely, for a fixed connectivity c (i.e., the number of neighbors of a node in the overlay), the average experienced delay in the cluster is independent of the external load. In addition, increasing c increases the average delay but decreases the system size for a given load. Consequently, the cluster administrator can use c as a management parameter that permits control of the tradeoff between a small system size and a small experienced delay for the service.

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

Data replication is a central technique to increase availability and performance of distributed systems. While offering many advantages it also requires more effort for ensuring data consistency in case of updates. In the research literature various approaches for replication management in distributed databases have been presented, but they are mostly limited either in scalability or in the consistency guarantees they provide. On the other hand, P2P systems usually provide replication support but ignore the update problem. In this paper we present a new approach for managing replicated data in wide area distributed networks. Our solution is orthogonal to the underlying infrastructure and managed in a decentralized manner. It guarantees single-master consistency and allows updates at any node of the system by combining traditional replication techniques with ideas known from P2P systems. 1.

P2P networks have emerged as a powerful multimedia content distribution mechanism. However, the widespread deployment of P2P networks are hindered by several issues, especially ones that influence end-user satisfaction, including privacy protection. In this paper, we propose GhostShare, a P2P network built on the Pastry substrate, to distribute video content. The primary design goals of GhostShare are anonymity and load balancing for participating peers. We present simulation results that prove the effectiveness of GhostShare's load balancing mechanism and provide an analysis of the anonymity scheme.

Self-adaptive systems typically rely on a closed control loop which detects when the current behavior deviates too much from the optimal one, determines new optimal values for system parameters, and applies changes to the system configuration. In decentralized systems, implementing each of these steps is challenging, especially when nodes need to coordinate their local configurations. In this paper, we propose a decentralized method to automatically tune global system parameters in a coordinated manner. We use gossip-based protocols to continuously monitor system properties and to disseminate parameter updates. We show that this method applied to a decentralized resource selection service allows the system to quickly adapt to changes in workload types and node properties, and only incurs a negligible communication overhead.