Association control algorithms for handoff frequency minimization in mobile wireless networks

As mobile nodes roam in a wireless network, they continuously associate with different access points and perform handoff operations. Frequent handoffs performed by a mobile device may have undesirable consequences, as they can cause interruptions for interactive applications and increase the energy...

Full description

Saved in:
Bibliographic Details
Published in:Wireless networks 2012-07, Vol.18 (5), p.535-550
Main Authors: Kim, Minkyong, Liu, Zhen, Parthasarathy, Srinivasan, Pendarakis, Dimitrios, Yang, Hao
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Communications Engineering
Computer Communication Networks
Control algorithms
Electrical Engineering
Engineering
IT in Business
Minimization
Mobile communication systems
Networks
On-line systems
Online
Optimization
Research centers
Studies
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:As mobile nodes roam in a wireless network, they continuously associate with different access points and perform handoff operations. Frequent handoffs performed by a mobile device may have undesirable consequences, as they can cause interruptions for interactive applications and increase the energy usage of mobile devices. While existing approaches to this issue focus entirely on improving the latency incurred by individual handoffs, in this paper, we initiate a novel approach to association control of mobile devices with the goal of reducing the frequency of handoffs for mobile devices. We study the handoff minimization problem across multiple dimensions: offline versus online where the complete knowledge of mobility patterns of users is known in advance or unknown respectively; capacity constrained versus unconstrained access points, which imposes limits on the number of mobile devices which could be associated with a given access point at any given point in time; group mobility versus arbitrary mobility of users, which are contrasting ways to model the mobility patterns of the mobile users. We consider various combinations of the above dimensions and present the following: (1) optimal algorithms, (2) provably-good online and offline approximation algorithms, (3) complexity (NP-Completeness) results, and (4) a practical heuristic which is demonstrated to work well on real network traces.
ISSN:1022-0038
1572-8196
DOI:10.1007/s11276-012-0417-4