000139007 001__ 139007
000139007 005__ 20181203021627.0
000139007 0247_ $$2doi$$a10.1109/TC.2009.111
000139007 02470 $$2ISI$$a000270031000002
000139007 037__ $$aARTICLE
000139007 245__ $$aSlicing Distributed Systems
000139007 269__ $$a2009
000139007 260__ $$c2009
000139007 336__ $$aJournal Articles
000139007 520__ $$aPeer-to-peer (P2P) architectures are popular for tasks such as collaborative download, VoIP telephony, and backup. To maximize performance in the face of widely variable storage capacities and bandwidths, such systems typically need to shift work from poor nodes to richer ones. Similar requirements are seen in today's large data centers, where machines may have widely variable configurations, loads and performance. In this paper, we consider the slicing problem, which involves partitioning the participating nodes into k subsets using a one-dimensional attribute, and updating the partition as the set of nodes and their associated attributes change. The mechanism thus facilitates the development of adaptive systems. We begin by motivating this problem statement and reviewing prior work. Existing algorithms are shown to have problems with convergence, manifesting as inaccurate slice assignments, and to adapt slowly as conditions change. Our protocol, Sliver, has provably rapid convergence, is robust under stress, and is simple to implement. We present both theoretical and experimental evaluations of the protocol.
000139007 6531_ $$aHeterogeneity
000139007 6531_ $$aP2P
000139007 6531_ $$aDynamism
000139007 700__ $$0242987$$g183046$$aGramoli, Vincent
000139007 700__ $$aVigfusson, Ymir
000139007 700__ $$aBirman, Ken
000139007 700__ $$aKermarrec, Anne-Marie
000139007 700__ $$avan Renesse, Robbert
000139007 773__ $$j58$$tIEEE Transactions on Computers$$k11$$q1444-1455
000139007 909C0 $$xU10407$$0252114$$pDCL
000139007 909CO $$pIC$$particle$$ooai:infoscience.tind.io:139007
000139007 917Z8 $$x148230
000139007 937__ $$aLPD-ARTICLE-2009-005
000139007 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000139007 980__ $$aARTICLE