A Novel Energy Saving Approach through Mobile Collaborative Computing Systems

A Novel Energy Saving Approach through Mobile Collaborative Computing Systems

Xiaoxin Wu, Huan Chen, Yaoda Liu, Wenwu Zhu
Copyright: © 2010 |Volume: 1 |Issue: 2 |Pages: 16
ISSN: 1947-9158|EISSN: 1947-9166|EISBN13: 9781609604400|DOI: 10.4018/jhcr.2010040101
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MLA

Wu, Xiaoxin, et al. "A Novel Energy Saving Approach through Mobile Collaborative Computing Systems." IJHCR vol.1, no.2 2010: pp.1-16. http://doi.org/10.4018/jhcr.2010040101

APA

Wu, X., Chen, H., Liu, Y., & Zhu, W. (2010). A Novel Energy Saving Approach through Mobile Collaborative Computing Systems. International Journal of Handheld Computing Research (IJHCR), 1(2), 1-16. http://doi.org/10.4018/jhcr.2010040101

Chicago

Wu, Xiaoxin, et al. "A Novel Energy Saving Approach through Mobile Collaborative Computing Systems," International Journal of Handheld Computing Research (IJHCR) 1, no.2: 1-16. http://doi.org/10.4018/jhcr.2010040101

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Abstract

Energy saving has been studied widely in both of computing and communication research communities. For handheld devices, energy is becoming a more and more critical issue because lots of applications running on handhelds today are computation or communication intensive and take a long time to finish. Unlike previous work that proposes computing or communication energy solutions alone, this paper proposes a novel energy savings approach through mobile collaborative systems, which jointly consider computing and communication energy cost. In this work, the authors use streaming video as investigated application scenario and propose multi-hop pipelined wireless collaborative system to decode video frames with a requirement for maximum inter-frame time. To finish a computing task with such a requirement, this paper proposes a control policy that can dynamically adapt processor frequency and communication transmission rate at the collaborative devices. The authors build a mathematical energy model for collaborative computing systems. Results show that the collaborative system helps save energy, and the transmission rate between collaborators is a key parameter for maximizing energy savings. The energy saving algorithm in computing devices is implemented and the experimental results show the same trend.

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