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.
With ever increasing Web traffic, a distributed multi server Web site can provide scalability and flexibility to cope with growing client demands. Load balancing algorithms to spread the requests across multiple Web servers are crucial to achieve the scalability. Various domain name server (DNS) based schedulers have been proposed in the literature, mainly for multiple homogeneous servers. The presence of heterogeneous Web servers not only increases the complexity of the DNS scheduling problem, but also makes previously proposed algorithms for homogeneous distributed systems not directly applicable. This leads us to propose new policies, cabled adaptive TTL algorithms, that take into account both the uneven distribution of client request rates and heterogeneity of Web servers to adaptively set the time-to-live (TTL) value for each address mapping request. Extensive simulation results show that these strategies are robust and effective in balancing load among geographically distributed heterogeneous Web servers.