, Volume 96, Issue 2, pp 87–117 | Cite as

Energy-efficient job stealing for CPU-intensive processing in mobile devices

  • Juan Manuel Rodriguez
  • Cristian Mateos
  • Alejandro Zunino


Mobile devices have evolved from simple electronic agendas and mobile phones to small computers with great computational capabilities. In addition, there are more than 2 billion mobile devices around the world. Taking these facts into account, mobile devices are a potential source of computational resources for clusters and computational Grids. In this work, we present an analysis of different schedulers based on job stealing for mobile computational Grids. These job stealing techniques have been designed to consider energy consumption and battery status. As a result of this work, we present empirical evidence showing that energy-aware job stealing is more efficient than traditional random stealing in this context. In particular, our results show that mobile Grids using energy-aware job stealing might finish up to 11 % more jobs than when using random stealing, and up to 24 % more jobs than when not using any job stealing technique. This means that using energy-aware job stealing increases the energy efficiency of mobile computational Grids because it increases the number of jobs that can be executed using the same amount of energy.


Mobile Grid Mobile devices Job stealing CPU intensive application Job scheduling 

Mathematics Subject Classification

68M14 Distributed systems 68M20 Performance evaluation; queueing; scheduling  68U99 None of the above, but in this section 


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Copyright information

© Springer-Verlag Wien 2012

Authors and Affiliations

  • Juan Manuel Rodriguez
    • 1
    • 2
  • Cristian Mateos
    • 1
    • 2
  • Alejandro Zunino
    • 1
    • 2
  1. 1.ISISTAN Research Institute, UNICEN UniversityBuenos AiresArgentina
  2. 2.Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Buenos AiresArgentina

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