Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 64, Issue 10, Pages 4738-4755Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2014.2372852
Keywords
Battery savings; energy efficiency; energy-latency tradeoff; femto-cloud; multiple-input multiple-output (MIMO); offloading
Categories
Funding
- European Commission (FP7) through Project TROPIC [INFSO-ICT-318784]
- Network of Excellence NEWCOM# [318306]
- Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competitividad) through Project (DISNET) [TEC2013-41315-R]
- Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competitividad) through Project (GRE3N-LINK-MAC) [TEC2011-29006-C03-02]
- Catalan Government [2014 SGR 60]
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Providing femto access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smartphones to the so-called femto-cloud. Such offloading promises to be beneficial in terms of battery savings at the mobile terminal (MT) and/or in latency reduction in the execution of applications. However, for this promise to become a reality, the energy and/or the time required for the communication process must be compensated by the energy and/or the time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency. Multiple antennas are assumed to be available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, and precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. This paper also establishes the conditions under which total or no offloading is optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes, as a particular case, the minimization of the total consumed energy without latency constraints.
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