All your network are belong to us: A transport framework for mobile network selection

Shuo Deng, Anirudh Sivaraman, Hari Balakrishnan

Research output: Contribution to conferencePaperpeer-review

Abstract

Mobile devices come with an assortment of networks: WiFi in two different frequency bands, each of which can run in infrastructuremode, WiFi-Direct mode, or ad hoc mode; cellular radios, which can run in LTE/4G, 3G, or EDGE modes; and Bluetooth. But how should an app choose which network to use? There is no systematic solution to this problem today: in current practice the choice is almost always left to the user, who usually has no idea what's best. In fact, what's best for a user depends on the app's performance objectives (throughput, delay, object load time, etc.) and the user's constraints on cost and battery life. Besides, what's best for a single user or app must be balanced with what's best for the wireless network as a whole (individual optimality vs. social utility). This paper introduces Delphi, a transport-layer module to resolve these issues. Delphi has three noteworthy components: "local learning", in which a mobile device estimates or infers useful properties of different networks efficiently, "property sharing", in which mobile devices share what they learn with other nearby devices, and "selection", in which each node selects a network using what it has observed locally and/or from its neighbors.

Original languageEnglish (US)
DOIs
StatePublished - 2014
Event15th Workshop on Mobile Computing Systems and Applications, HotMobile 2014 - Santa Barbara, CA, United States
Duration: Feb 26 2014Feb 27 2014

Other

Other15th Workshop on Mobile Computing Systems and Applications, HotMobile 2014
CountryUnited States
CitySanta Barbara, CA
Period2/26/142/27/14

Keywords

  • Mobile Device
  • Multi-Network

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

Fingerprint Dive into the research topics of 'All your network are belong to us: A transport framework for mobile network selection'. Together they form a unique fingerprint.

Cite this