A P2P Computing System for Overlay Networks

A distributed computing system is able to perform data computation and distribution of results at the same time. The input task is divided into blocks, which are then sent to system participants that offer their resources in order to perform calculations. Next, a partial result is sent back by the participants to the task manager (usually one central node). In the case when system participants want to get the final result, the central node may become overloaded, especially if many nodes request the result at the same time. In this paper we propose a novel distributed computation system, which does not use the central node as the source of the final result, but assumes that partial results are sent between system participants. This way we avoid overloading the central node, as well as network congestion. There are two major types of distributed computing systems: grids and Peer-to-Peer (P2P) computing systems. In this work we focus on the latter case. Consequently, we assume that the computing system works on the top of an overlay network. We present a complete description of the P2P computing system, considering both computation and result distribution. To verify the proposed architecture we develop our own simulator. The obtained results show the system performance expressed by the operation cost for various types of network flows: unicast, anycast and Peer-to-Peer. Moreover, the simulations prove that our computing system provides about 66% lower cost compared to a centralized computing system

Master/worker parallel discrete event simulation

The execution of parallel discrete event simulation across metacomputing infrastructures is examined. A master/worker architecture for parallel discrete event simulation is proposed providing robust executions under a dynamic set of services with system-level support for fault tolerance, semi-automated client-directed load balancing, portability across heterogeneous machines, and the ability to run codes on idle or time-sharing clients without significant interaction by users. Research questions and challenges associated with issues and limitations with the work distribution paradigm, targeted computational domain, performance metrics, and the intended class of applications to be used in this context are analyzed and discussed. A portable web services approach to master/worker parallel discrete event simulation is proposed and evaluated with subsequent optimizations to increase the efficiency of large-scale simulation execution through distributed master service design and intrinsic overhead reduction. New techniques for addressing challenges associated with optimistic parallel discrete event simulation across metacomputing such as rollbacks and message unsending with an inherently different computation paradigm utilizing master services and time windows are proposed and examined. Results indicate that a master/worker approach utilizing loosely coupled resources is a viable means for high throughput parallel discrete event simulation by enhancing existing computational capacity or providing alternate execution capability for less time-critical codes.Ph.D.Committee Chair: Fujimoto, Richard; Committee Member: Bader, David; Committee Member: Perumalla, Kalyan; Committee Member: Riley, George; Committee Member: Vuduc, Richar