Decentralized resource sharing and multimedia workflow processing
Gisik Kwon · 2008
Peer-to-Peer (P2P) computing has been gaining popularity due to the decentralized organization, high scalability, and the manipulation of abundant resources at the edge machines. Of many P2P applications, file sharing is the most ubiquitous with multiple implementations where users of P2P networks can find the files of interest from other computers on the network and download them locally. Most of P2P file sharing systems search the files using either simple flooding or indexed routing with the complex structures, such as the Distributed Hash Table (DHT). However, the file locating performance in these approaches turns out to be poor without a careful consideration of the machine heterogeneity and the network hierarchy. From this observation preliminary works introduce two asymmetric file sharing systems for large-scale P2P networks. Both systems provide not only efficient and deterministic file location, but also self-organization and load balancing by exploiting underlying network topology. This thesis extends the researches to the dynamic service composition in which multimedia workflow processing systems like ARchitecture for Interactive Arts (ARIA) organize workflow operators in a purely decentralized manner. The traditional approach involves a centralized data warehouse, permitting the extensive resource provisioning and replication to manage server load. Recent works propose to leverage routing paths in the DHT to obtain a set of candidate nodes for service placement. However the DHT is not designed to optimize workflow processing in overlay networks, yielding small candidate set sizes for service placement. This work proposes a noble Decentralized, Autonomous and Network-wide service workflow processing System (DANS), which explores DHT-based P2P substrates to lookup and publish the underlying peer information. This system achieves network adaptivity by using sender-initiated operator mapping, as opposed to the receiver-initiation used in most current systems, eliminating pre-establishment of workflow networks. In addition, DANS supports multi-constrained workflow execution. To this end this thesis solves the nested chain workflow problem based on probabilistic models which select qualified service paths enforcing Quality of Service (QoS) metrics, while requiring low bandwidth consumption and sharing processing workloads.