The use of parallel computing is increasing with the need to solve ever more complex problems. Unfortunately, while the cost of parallel systems (including clusters and small-scale shared memory machines) has decreased, such machines are still not within the reach of many users. This is particularly true if large numbers of processors are needed. A largely untapped resource for doing some, simpler, types of parallel computing
are temporarily idle machines in distributed environments. Such environments range from the simple (identical machines connected via a LAN) to the complex (heterogeneous machines connected via the Internet).
In this thesis I describe a system for dynamically clustering together similar machines distributed across the Internet. This is done in a peer-to-peer (P2P) fashion with the goal of ultimately forming useful compute clusters without the need for a heavily centralized software system overseeing the process. In this sense my work builds on so-called
"volunteer computing" efforts, such as SETI@Home but with the goal of supporting a #11;different class of compute problems.
I #12;first consider the characteristics that are necessary to form good clusters of shared machines that can be used together effectively. Second, I exploit simple clustering algorithms to group together appropriate machines using the identified#12;ed characteristics. My system assembles workstations into clusters which are, in some sense, "close" in terms
of bandwidth, latency and/or number of network hops and that are also computationally similar in terms of processor speed, memory capacity and available hard disk space. Finally, I assess the conditions under which my proposed system might be effective via simulation using generated network topologies that are intended to reflect real-world characteristics. The results of these simulations suggest that my system is tunable to different conditions and that the algorithms presented can #11;effectively group together appropriate machines to form clusters and can also manage those clusters #11;effectively as the constituent machines join and leave the system.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/3857 |
| Date | 13 January 2010 |
| Creators | Kadaru, Pranith Reddy |
| Contributors | Graham, Peter (Computer Science), Card, Paul (Electrical and Computer Engineering) Eskicioglu, Rasit (Computer Science) |
| Source Sets | University of Manitoba Canada |
| Language | en_US |
| Detected Language | English |
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