Paper Info
Title
Scalable Content-Based Publish/Subscribe Services over Structured Peer-to-Peer Networks
Abstract
The scalability has remained a challenge in the design of distributed publish/subscribe systems. In this paper we propose a novel solution to address this problem in content-based pubsystems on top of distributed hash table. The main objective is to ensure an appropriate amount of rendezvous point nodes in the system, as well as maintain an even load distribution among them. An attribute-vector based publishsubscribe scheme and related load balancing mechanisms (ID space partitioning, attribute grouping, dynamic ID space split-merge) are proposed to achieve this goal. The experimental results show that our approaches can achieve a good scalability by efficiently distribute/balance load among an adaptive quantity of rendezvous point nodes, while retaining very small overhead and latency
Year
DOI
Venue
2007
10.1109/PDP.2007.71
PDP
Keywords
Field
DocType
structured peer-to-peer networks,subscribe services,related load,dynamic id space split-merge,adaptive quantity,distributed publish/subscribe system,appropriate amount,resource allocation,good scalability,content management,publish/subscribe service,content-based publish/subscribe system,id space partitioning,distributed hash table,scalable content-based publish,contentbased pub,file organisation,hash table,balance load,load distribution,scalable content,peer-to-peer computing,rendezvous point node,load balancing,structured peer-to-peer network,publish subscribe,load balance
Space partitioning,Peer-to-peer,Load balancing (computing),Computer science,Computer network,Resource allocation,Rendezvous,Content management,Distributed hash table,Distributed computing,Scalability
Conference
ISSN
ISBN
Citations 
1066-6192
0-7695-2784-1
4
PageRank 
References 
Authors
0.45
13
3
Name
Order
Citations
PageRank
Xiaoyu Yang1555.21
Yingwu Zhu236223.69
Yiming Hu363944.91