Exploiting Heterogeneity in Peer-to-Peer Systems Using Gradient Topologies

A peer-to-peer system can be de ned as an overlay network built by a set of nodes on top of a physical network infrastructure and its operating protocols, such as the Internet. In a peer-to-peer network, each node maintains a limited number of connections with other nodes, called peers, and the graph of peer connections constitutes the overlay's topology. One of the most fundamental properties of existing large-scale peer-to-peer systems is a very high heterogeneity and dynamism of peers participating in the system. Studies show that the distributions of peer characteristics, such as peer session duration, available bandwidth, and storage space, are highly skewed and often heavy-tailed, with small fractions of peers possessing disproportionally large fractions of the total system resources. Such heterogeneity introduces both challenges and opportunities when designing peer-to-peer systems. The use of lowperformance or low-stability nodes for maintaining system data or services can easily lead to a poor performance of the entire system, while the placement of critical data and services on the most reliable, high-capacity nodes may improve the overall system stability and performance. Current state-of-the-art peer-to-peer systems exploit their heterogeneity by introducing two-level hierarchies of peers. High capability peers, so called super-peers, form an independent sub-topology within the existing peer-to-peer network and handle the core system functionality, such as indexing peer data and handling search queries, or relaying tra c on behalf of rewalled peers. Ordinary peers connect directly to super-peers and act as their clients. However, many existing systems lack an e cient, decentralised super-peer election algorithm. In many systems, super-peers are selected manually, through an out-of-band mechanism, or are elected using simple local heuristics, which are likely to generate suboptimal super-peer sets. Sophisticated super-peer election algorithms exist, but they are usually highly speci c to particular systems and are not easily portable to other application areas. This thesis presents a novel class of peer-to-peer topologies, called gradient topologies, which generalise the concept of super-peer networks. In gradient topologies, the position of each peer is determined by a continuous utility function, and the highest utility peers are clustered in a logical centre of the topology, while peers with lower utility are located at gradually increasing distance from the centre. The utility metric captures application-speci c peer requirements and re ects peers'