Efficient content distribution with managed swarms

摘要: Content distribution has become increasingly important as people have more reliant on Internet services to provide large multimedia content. Efficiently distributing content is a complex and difficult problem: libraries are often distributed across many physical hosts, each host its own bandwidth storage constraints. Peer-to-peer peer-assisted download systems further complicate distribution. By contributing their bandwidth, end users can improve overall performance reduce load servers, but motivations incentives that not necessarily aligned with those of distributors. Consequently, existing distributors either opt serve exclusively from hosts under direct control, thus neglect the pool resources offer, or they allow contribute at expense sacrificing complete control over available resources. This thesis introduces new approach achieves high for bulk content, based managed swarms . Managed efficiently allocate origin in-network caches, achieve system-wide objectives. swarming characterized by presence logically centralized coordinator maintains global view system directs toward an efficient use bandwidth. The allocates empirical measurements swarm behavior combined model dynamics. enables predict how will respond changes in past performance. In this thesis, we focus objective maximizing system. To end, introduce two algorithms compute allocations result speeds clients. We implemented scalable uses these maximize aggregate actively measures dynamics data calculate, host, allocation among competing host's Extensive simulations live deployment show significantly outperform well completely decentralized peer-to-peer systems.