This paper studies the problem of load-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. We propose a new decentralized algorithm, Max-Cap, based on the maximum inherent capacities of the replica nodes and show that unlike previous algorithms, it is not tied to the timeliness or frequency of updates. Yet, Max-Cap can handle the heterogeneity of a peer-to-peer environment without suffering from load oscillations.
URL, or layer-5, switches can be used to implement locally and globally distributed Web sites. URL switches must be able to exploit knowledge of server load and content (e.g., of reverse caches). Implementing globally distributed Web sites offers difficulties not present in local server clusters due to bandwidth and delay constraints in the Internet. With delayed load information, server selection methods based on choosing the least-loaded server will result in oscillations in network and server load. In this paper, methods that make effective use of delayed load information are described and evaluated. The new Pick-KX method is developed and shown to be better than existing methods. Load information is adjusted with probabilistic information using Bloom filter summaries of site content. A combined load and content metric is suggested for use for selecting the best server in a globally distributed site.