IP networks today require massive effort to configure and manage. Ethernet is vastly simpler to manage, but does not scale beyond small local area networks. This paper describes an alternative network architecture called SEATTLE that achieves the best of both worlds: The scalability of IP combined with the simplicity of Ethernet. SEATTLE provides plug-and-play functionality via flat addressing, while ensuring scalability and efficiency through shortest-path routing and hash-based resolution of host information. In contrast to previous work on identity-based routing, SEAT-TLE ensures path predictability and stability, and simplifies network management. We performed a simulation study driven by real-world traffic traces and network topologies, and used Emulab to evaluate a prototype of our design based on the Click and XORP open-source routing platforms. Our experiments show that SEAT-TLE efficiently handles network failures and host mobility, while reducing control overhead and state requirements by roughly two orders of magnitude compared with Ethernet bridging.

Abstract — Existing solutions to achieve load balancing in DHTs incur a high overhead either in terms of routing state or in terms of load movement generated by nodes arriving or departing the system. In this paper, we propose a set of general techniques and use them to develop a protocol based on Chord, called Y0, that achieves load balancing with minimal overhead under the typical assumption that the load is uniformly distributed in the identifier space. In particular, we prove that Y0 can achieve near-optimal load balancing, while moving little load to maintain the balance, and increasing the size of the routing tables by at most a constant factor. Using extensive simulations based on real-world and synthetic capacity distributions, we show that Y0 reduces the load imbalance of Chord from O(log n) to a less than 4 without increasing the number of links that a node needs to maintain. In addition, we study the effect of heterogeneity on both DHTs, demonstrating significantly reduced average route length as node capacities become increasingly heterogeneous. For a real-word distribution of node capacities, the route length in Y0 is asymptotically less than half the route length in the case of a homogeneous system. Index Terms — System design, Simulations I.

This paper studies the problem of balancing the demand for content in a peer-to-peer network across heterogeneous peer nodes that hold replicas of the content. Previous decentralized load balancing techniques in distributed systems base their decisions on periodic updates containing information about load or available capacity observed at the serving entities. We show that these techniques do not work well in the peer-to-peer context; either they do not address peer node heterogeneity, or they suffer from significant load oscillations which result in unutilized capacity. We propose a new decentralized algorithm, Max-Cap, based on the maximum inherent capacities of the replica nodes. We show that unlike previous algorithms, it is not tied to the timeliness or frequency of updates, and consequently requires significantly less update overhead. Yet, Max-Cap can handle the heterogeneity of a peer-to-peer environment without suffering from load oscillations.

We study randomized algorithms for placing a sequence of n nodes on a circle with unit perimeter. Nodes divide the circle into disjoint arcs. We desire that a newly-arrived node (which is oblivious of its index in the sequence) choose its position on the circle by learning the positions of as few existing nodes as possible. At the same time, we desire that that the variation in arc-lengths be small. To this end, we propose a new algorithm that works as follows: The k th node chooses r random points on the circle, inspects the sizes of v arcs in the vicinity of each random point, and places itself at the mid-point of the largest arc encountered. We show that for any combination of r and v satisfying rv ≥ c log k, where c is a small constant, the ratio of the largest to the smallest arc-length is at most eight w.h.p., for an arbitrarily long

Super-peer architectures exploit the heterogeneity of nodes in a P2P network by assigning additional responsibilities to higher-capacity nodes. In the design of a super-peer network for file sharing, several issues have to be addressed: how client peers are related to super-peers, how super-peers locate files, how the load is balanced among the super-peers, and how the system deals with node failures. In this paper we introduce a self-organizing super-peer network architecture (SOSPNet) that solves these issues in a fully decentralized manner. SOSPNet maintains a super-peer network topology that reflects the semantic similarity of peers sharing content interests. Super-peers maintain semantic caches of pointers to files which are requested by peers with similar interests. Client peers, on the other hand, dynamically select super-peers offering the best search performance. We show how this simple approach can be employed not only to optimize searching, but also to solve generally difficult problems encountered in P2P architectures such as load balancing and fault tolerance. We evaluate SOSPNet using a model of the semantic structure derived from the 8-month traces of two large file-sharing communities. The obtained results indicate that SOSPNet achieves close-to-optimal file search performance, quickly adjusts to changes in the environment (node joins and leaves), survives even catastrophic node failures, and efficiently distributes the system load taking into account peer capacities. 1

This paper presents the design, implementation, and evaluation of EnviroMic, a novel distributed acoustic monitoring, storage, and trace retrieval system. Audio represents one of the least exploited modalities in sensor networks to date. The relatively high frequency and large size of audio traces motivate distributed algorithms for coordinating recording tasks, reducing redundancy of data stored by nearby sensors, filtering out silence, and balancing storage utilization in the network. Applications of acoustic monitoring with EnviroMic range from the study of mating rituals and social behavior of animals in the wild to audio surveillance of military targets. EnviroMic is designed for disconnected operation, where the luxury of having a basestation cannot be assumed. We implement the system on a TinyOS-based platform and systematically evaluate its performance through both indoor testbed experiments and a preliminary outdoor deployment. Results demonstrate up to a 4-fold improvement in effective storage capacity of the network compared to uncoordinated recording. Index Terms Sensor networks, applications, acoustics, distributed storage, group management

Abstract — This paper presents a new cooperative storage system for sensor networks geared for disconnected operation (where sensor nodes do not have a connected path to a basestation). The goal of the system is to maximize its data storage capacity by appropriately distributing storage utilization and opportunistically offloading data to external devices when possible. The system is motivated by the observation that a large

Many emerging distributed applications require the processing of massive amounts of data in real-time. As a result, distributed stream processing systems have been introduced, offering a scalable and efficient means of in-network processing. Managing however the load among the nodes of such a large-scale, dynamic system in real-time is challenging. The peer-to-peer paradigm can help address these challenges via self-organization. We describe a self-managing architecture for identifying and alleviating hot-spots in a peer-to-peer stream processing environment. Resource monitoring and hot-spot detection are carried out by all peers independently, building upon a completely decentralized architecture. To alleviate hot-spots we empower peers to autonomously migrate the execution of stream processing components using a non-disruptive migration protocol. We have integrated our techniques in Synergy, our distributed stream processing middleware. The experimental evaluation of our implementation over PlanetLab demonstrates substantial performance benefits for distributed stream processing applications, with moderate monitoring and migration overheads.

In this paper we present a technique for fair resource allocation in unstructured Peer-to-Peer systems. Our technique uses the Fairness Index of a distribution as a measure of fairness and shows how to optimize the fairness of the distribution using only local decisions. Load balancing is achieved by replicating documents across multiple nodes in the system. Our experimental results demonstrate that our technique is scalable, has low overhead and achieves good load balance even under skewed demand.

Balancing of structured peer-to-peer graphs, including their zone sizes, has recently become an important topic of distributed hash table (DHT) research. To bring analytical understanding into the various peer-join mechanisms based on consistent hashing, we study how zone-balancing decisions made during the initial sampling of the peer space affect the resulting zone sizes and derive several asymptotic bounds for the maximum and minimum zone sizes that hold with high probability. Several of our results contradict those of prior work and shed new light on the theoretical performance limitations of consistent hashing. We use simulations to verify our models and compare the performance of the various methods using the example of recently proposed de