2006
DOI: 10.1109/lcn.2006.322078
|View full text |Cite
|
Sign up to set email alerts
|

Computing Real Time Jobs in P2P Networks

Abstract: Abstract-In this paper, we present a distributed computing framework designed to support higher quality of service and fault tolerance for processing deadline-driven tasks in a P2P environment. Our proposed strategy strives to build an open infrastructure that is accessible by ordinary users for both cycle donation and consumption. For jobs that fail to be locally accommodated, the proposed scheduler MET (Maximum Efficiency Tree) builds a dynamic multi-level resource tree with minimal yet sufficient power to p… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2012
2012
2012
2012

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 15 publications
0
2
0
Order By: Relevance
“…al. in [9] proposed an load sharing mechanism for computing real time jobs in P2P networks. The proposed mechanism identifies most efficient resource pool with an optimized load scheduling.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…al. in [9] proposed an load sharing mechanism for computing real time jobs in P2P networks. The proposed mechanism identifies most efficient resource pool with an optimized load scheduling.…”
Section: Related Workmentioning
confidence: 99%
“…Due to the ad-hoc and dynamic nature of the P2P network paradigm, varying resource availability and unpredictable latencies are present which causes number of challenges in managing the computing resources and scheduling task execution across the systems [8]. Moreover the tasks in real time applications have deadline to be met which requires the predictable performance of the computing system [9]. The P2P computing systems have lack of scheduling schemes which clearly analyze the resource requirement and predict total execution time.…”
Section: Introductionmentioning
confidence: 99%