Computing while charging: building a distributed computing infrastructure using smartphones

  • Authors:

  • Mustafa Y. Arslan;Indrajeet Singh;Shailendra Singh;Harsha V. Madhyastha;Karthikeyan Sundaresan;Srikanth V. Krishnamurthy

  • Affiliations:

  • NEC Laboratories America Inc. & UC Riverside, Princeton, NJ, USA;UC Riverside, Riverside, CA, USA;UC Riverside, RIVERSIDE, CA, USA;UC Riverside, RIVERSIDE, CA, USA;NEC Laboratories America Inc., Princeton, NJ, USA;UC Riverside, RIVERSIDE, CA, USA

  • Venue:
  • Proceedings of the 8th international conference on Emerging networking experiments and technologies
  • Year:
  • 2012

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Abstract

Every night, a large number of idle smartphones are plugged into a power source for recharging the battery. Given the increasing computing capabilities of smartphones, these idle phones constitute a sizeable computing infrastructure. Therefore, for an enterprise which supplies its employees with smartphones, we argue that a computing infrastructure that leverages idle smartphones being charged overnight is an energy-efficient and cost-effective alternative to running tasks on traditional server infrastructure. While parallel execution and scheduling models exist for servers (e.g., MapReduce), smartphones present a unique set of technical challenges due to the heterogeneity in CPU clock speed, variability in network bandwidth, and lower availability compared to servers. In this paper, we address many of these challenges to develop CWC---a distributed computing infrastructure using smartphones. Specifically, our contributions are: (i) we profile the charging behaviors of real phone owners to show the viability of our approach, (ii) we enable programmers to execute parallelizable tasks on smartphones with little effort, (iii) we develop a simple task migration model to resume interrupted task executions, and (iv) we implement and evaluate a prototype of CWC (with 18 Android smartphones) that employs an underlying novel scheduling algorithm to minimize the makespan of a set of tasks. Our extensive evaluations demonstrate that the performance of our approach makes our vision viable. Further, we explicitly evaluate the performance of CWC's scheduling component to demonstrate its efficacy compared to other possible approaches.