Name
Abstract | ||
|---|---|---|
With the notion of virtual servers, peers participating in a heterogeneous, structured peer-to-peer (P2P) network may host different numbers of virtual servers, and by migrating virtual servers, peers can balance their loads proportional to their capacities. The existing and decentralized load balance algorithms designed for the heterogeneous, structured P2P networks either explicitly construct auxiliary networks to manipulate global information or implicitly demand the P2P substrates organized in a hierarchical fashion. Without relying on any auxiliary networks and independent of the geometry of the P2P substrates, we present, in this paper, a novel load balancing algorithm that is unique in that each participating peer is based on the partial knowledge of the system to estimate the probability distributions of the capacities of peers and the loads of virtual servers, resulting in imperfect knowledge of the system state. With the imperfect system state, peers can compute their expected loads and reallocate their loads in parallel. Through extensive simulations, we compare our proposal to prior load balancing algorithms. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TPDS.2010.105 | IEEE Trans. Parallel Distrib. Syst. |
Keywords | Field | DocType |
imperfect information,peer-to-peer systems,p2p substrate,statistical distributions,virtual server,imperfect system state,load balance,virtual servers,auxiliary network,resource allocation,system state,novel load,p2p network,load balancing algorithm,probability distributions,structured peer-to-peer systems,heterogeneity.,peer-to-peer computing,expected load,p2p networks,decentralized load balance,prior load,probability distribution,algorithm design and analysis,algorithm design,computer model,network server,concurrent computing,heterogeneity,p2p,computational modeling,information geometry | Load management,Algorithm design,Peer-to-peer,Computer science,Load balancing (computing),Computer network,Capacity planning,Real-time computing,Resource allocation,Concurrent computing,Perfect information,Distributed computing | Journal |
Volume | Issue | ISSN |
22 | 4 | 1045-9219 |
Citations | PageRank | References |
11 | 0.62 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hung-Chang Hsiao | 1 | 256 | 32.34 |
| Hao Liao | 2 | 51 | 5.37 |
| Ssu-Ta Chen | 3 | 11 | 0.62 |
| Kuo-Chan Huang | 4 | 184 | 22.95 |