Abstract
Energy is a vital resource in pervasive computing. Remote execution, a static approach to energy saving of mobile devices, is not applicable to the constantly varying environment in pervasive computing. This paper presents a dynamic software configuration approach to minimizing energy consumption by moving or/and replicating the appropriate components of an application among the machines. After analyzing three types of energy costs of the distributed applications, we set up a math optimization model of energy consumption. Based on the graph theory, the optimization problem of energy cost can be transformed into the Min-cut problem of a cost graph. Then, we propose two novel optimal software allocation algorithms for saving power. The first makes use of component migration to reasonably allocate the components among the machines at runtime, and the second is to replicate some components among machines to further save more energy than component migration. The simulations reveal that the two proposed algorithms can effectively save energy of mobile devices, and obtain better performance than the previous approaches in most of cases.
This work is supported by grants 05SN07114 and 03DZ19320, all from the Shanghai Commission of Science and Technology.
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Han, S., Zhang, S., Zhang, Y. (2006). Energy Saving of Mobile Devices Based on Component Migration and Replication in Pervasive Computing. In: Ma, J., Jin, H., Yang, L.T., Tsai, J.JP. (eds) Ubiquitous Intelligence and Computing. UIC 2006. Lecture Notes in Computer Science, vol 4159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11833529_65
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DOI: https://doi.org/10.1007/11833529_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38091-7
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