Providing femto-access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smart-phones to the so called femto-cloud. Such offloading promises to be beneficial in terms of battery saving 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 are 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, 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 are 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. Femto-cloud, offloading, battery saving, energy-latency trade-off, energy efficiency, multi-input multioutput (MIMO). Address: c/ Jordi Girona 1-3, mòdul D5 -campus nord UPC,
Munoz et al. proposed a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency REF .
Optimization of Radio and Computational Resources for Energy Efficiency in Latency-Constrained Application Offloading
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