Paper Info
Title
Cost-Aware Partitioning for Efficient Large Graph Processing in Geo-Distributed Datacenters.
Abstract
Graph processing is an emerging computation model for a wide range of applications and graph partitioning is important for optimizing the cost and performance of graph processing jobs. Recently, many graph applications store their data on geo-distributed datacenters (DCs) to provide services worldwide with low latency. This raises new challenges to existing graph partitioning methods, due to the m...
Year
DOI
Venue
2020
10.1109/TPDS.2019.2955494
IEEE Transactions on Parallel and Distributed Systems
Keywords
DocType
Volume
Bandwidth,Wide area networks,Data transfer,Downlink,Internet,Uplink
Journal
31
Issue
ISSN
Citations 
7
1045-9219
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Amelie Chi Zhou11039.11
Bingkun Shen200.34
Yao Xiao321.71
Shadi Ibrahim437127.43
Bingsheng He52810179.09