By Topic

Locality-Aware and Churn-Resilient Load-Balancing Algorithms in Structured Peer-to-Peer Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Haiying Shen ; Dept. of Comput. Sci. & Comput. Eng., Arkansas Univ., Fayetteville, AR ; Cheng-Zhong Xu

Structured peer-to-peer overlay networks, like distributed hash tables (DHTs), map data items to the network based on a consistent hashing function. Such mapping for data distribution has an inherent load balance problem. Data redistribution algorithms based on randomized matching of heavily loaded nodes with light ones can deal with the dynamics of DHTs. However, they are unable to consider the proximity of the nodes simultaneously. There are other methods that rely on auxiliary networks to facilitate locality-aware load redistribution. Due to the cost of network construction and maintenance, the locality-aware algorithms can hardly work for DHTs with churn. This paper presents a locality-aware randomized load-balancing algorithm to deal with both the proximity and network churn at the same time. We introduce a factor of randomness in the probing of lightly loaded nodes in a range of proximity. We further improve the efficiency by allowing the probing of multiple candidates (d-way) at a time. Simulation results show the superiority of the locality-aware two-way randomized algorithm in comparison with other random or locality-aware algorithms. In DHTs with churn, it performs no worse than the best chum-resilient algorithm. It takes advantage of node capacity heterogeneity and achieves good load balance effectively even in a skewed distribution of items

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:18 ,  Issue: 6 )