A distributed ADMM approach for mobile data offloading in software defined network

Lanchao Liu, Xianfu Chen, Mehdi Bennis, Guoliang Xue, Zhu Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

Mobile data offloading has been introduced to alleviate the congestion of cellular networks and to improve the quality of service for mobile end users. This paper presents a distributed mechanism for mobile data offloading in software defined network (SDN) at the network edge. In SDN, the data traffic of base stations (BSs) can be dynamically offloaded to access points (APs), which is enabled by the SDN controller. The SDN controller formulates a revenue maximization problem to optimize the data offloading decision, and solves the problem in a fully distributed fashion. The proposed mechanism is based on the proximal Jacobian multi-block alternating direction method of multipliers (ADMM). BSs and APs perform the offloading decision update concurrently, and are coordinated by the SDN controller through dual variables to reach a consensus on the offloading demand and supply. Numerical simulations validate the effectiveness of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2015 IEEE Wireless Communications and Networking Conference, WCNC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1748-1752
Number of pages5
ISBN (Electronic)9781479984060
DOIs
StatePublished - Jun 17 2015
Event2015 IEEE Wireless Communications and Networking Conference, WCNC 2015 - New Orleans, United States
Duration: Mar 9 2015Mar 12 2015

Publication series

Name2015 IEEE Wireless Communications and Networking Conference, WCNC 2015

Other

Other2015 IEEE Wireless Communications and Networking Conference, WCNC 2015
Country/TerritoryUnited States
CityNew Orleans
Period3/9/153/12/15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing

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