Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer

Abstract

Achieving long battery lives or even self sustainability has been a long standing challenge for designing mobile devices. This paper presents a novel solution that seamlessly integrates two technologies, mobile cloud computing and microwave power transfer (MPT), to enable computation in passive lowcomplexity devices such as sensors and wearable computing devices. Specifically, considering a single-user system, a base station (BS) either transfers power to or offloads computation from a mobile to the cloud; the mobile uses harvested energy to compute given data either locally or by offloading. A framework for energy efficient computing is proposed that comprises a set of policies for controlling CPU cycles for the mode of local computing, time division between MPT and offloading for the other mode of offloading, and mode selection. Given the CPU-cycle statistics information and channel state information (CSI), the policies aim at maximizing the probability of successfully computing given data, called computing probability, under the energy harvesting and deadline constraints. The policy optimization is translated into the equivalent problems of minimizing the mobile energy consumption for local computing and maximizing the mobile energy savings for offloading which are solved using convex optimization theory. The structures of the resultant policies are characterized in closed form. Furthermore, given non-causal CSI, the said analytical framework is further developed to support computation load allocation over multiple channel realizations, which further increases the computing probability. Last, simulation demonstrates the feasibility of wirelessly powered mobile cloud computing and the gain of its optimal control.

Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey

“…MEC devices may also be energized through wireless power transfer (WPT) [39,40], when the renewable energy is insufficient. WPT may be exploited for computational offloading in mobile devices [41] or data offloading for MEC in future networks [42,43]. We stress, however, that the energy transfer efficiency of current WPT techniques is still very low, and that new methods are required to increase it and make WPT appealing in practice; see [44].…”

“…The obtained numerical results demonstrate that the approach increases the energy efficiency of the MEC system. A centralized twostage resource allocation optimization scheme is proposed in [41] with the objective of minimizing the mobile energy consumption in a MEC offloading system using TDMA and OFDMA. The MEC server is assumed to have knowledge of the local computation energy consumption, of channel gains and fairness indices for all users.…”

“…Optimization technique EE computation offloading under tasks delay constraints [43] Maximum cardinality bin packing problem EE multiuser resource allocation [41] Dual decomposition, partial Lagrange Joint computation and communication cooperation [48] Lagrange duality, ellipsoid method Optimal offloading and autoscaling decision making in EH powered MEC systems [46] Markov decision processes and reinforcement learning…”

Survey of Energy-Efficient Techniques for the Cloud-Integrated Sensor Network

“…Customizable sensor information system model is used to modify data transmission and frequency of data collection to make it energy efficient, and this approach also reduces CO 2 emissions [21]. A framework for wirelessly powered based on mobile computing under the constraints of deadlines and energy harvesting is proposed to minimize the energy consumption of local computing and maximizing the energy saving for offloading computing [22]. The sensor-cloud integrated platform is used to perform pushpull communication among the three layers of the system architecture for energy-efficient data transmission.…”

Stochastic modelling of wireless energy transfer

“…Technologies, such as microwave power transfer (MPT) and mobile communication offloading are designed to extend the mobile device's battery life [2]. The simultaneous wireless information and power transfer (SWIPT) field is a combination of two technologies with a goal of increasing the efficiency of the MPT.…”