arrow
Return

RBTP: Low-Power Mobile Discovery Protocol through Recursive Binary Time Partitioning

delete2014-02-01
delete20
PRE
AI
李东 (Dong Li) *
P
Prasun Sinha
DOI:10.1109/TMC.2012.240delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
With increasing prevalence of mobile wireless devices with WiFi and Bluetooth capability, new applications that can make use of limited contact opportunities when the devices are physically close are emerging. Proximity-based social networking, and location specific dissemination of advertisements and events, are some such applications. Discovering such services is a challenging problem due to energy budget limitations, user mobility, and nonuniformity and the time-varying nature of energy budgets across users. It is important to rapidly discover such mobile services to make use of limited contact opportunities. To support such applications, we seek to design a localized discovery scheme that can minimize the expected contact latency between mobile phones with limited energy budgets. All the existing neighbor discovery schemes assume lack of any time synchronization. However, in practice sufficiently accurate time synchronization can be achieved with existing time synchronization techniques. We propose Recursive Binary Time Partitioning (RBTP), a scheme that determines how the devices should wake up and sleep to achieve minimal contact latency with other nearby devices. RBTP achieves provable performance bound and outperforms state-of-the-art asynchronous protocols for smartphones. When compared with the optimum scheme, the contact latency is shown to be within a factor of 9/8 in the expected case and 2 in the worst case.
Keywords:
Neighbor discovery
mobile devices
energy management in smartphones
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Mobile Computing cover
IEEE Transactions on Mobile Computing
IF:
9.2
Papers:
5.6K
Citations:
1.8W

Organization

U
University System of Ohio
Scholars:
15.4W
Papers: 13.0W
Citations: 200