Acc: generic on-demand accelerations for neighbor discovery in mobile applications

  • Authors:
  • Desheng Zhang;Tian He;Yunhuai Liu;Yu Gu;Fan Ye;Raghu K. Ganti;Hui Lei

  • Affiliations:
  • University of Minnesota;University of Minnesota;Third Research Institute of Ministry of Public Security, China;Singapore University of Technology and Design, Singapore;IBM T.J. Watson Research Center;IBM T.J. Watson Research Center;IBM T.J. Watson Research Center

  • Venue:
  • Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
  • Year:
  • 2012

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Abstract

As a supporting primitive of many mobile device applications, neighbor discovery identifies nearby devices so that they can exchange information and collaborate in a peer-to-peer manner. To date, discovery schemes trade a long latency for energy efficiency and require a collaborative duty cycle pattern, and thus they are not suitable for interactive mobile applications where a user is unable to configure others' devices. In this paper, we propose Acc, which serves as an on-demand generic discovery accelerating middleware for many existing neighbor discovery schemes. Acc leverages the discovery capabilities of neighbor devices, supporting both direct and indirect neighbor discoveries. Our evaluations show that Acc-assisted discovery schemes reduce latency by a maximum of 51.8%, compared with the schemes consuming the same amount of energy. We further present and evaluate a Crowd-Alert application where Acc can be employed by taxi drivers to accelerate selection of a direction with fewer competing taxis and more potential passengers, based on a 10 GB dataset of more than 15,000 taxis in a metropolitan area.