Abstract
Mobile cloud computing enables the offloading of computationally heavy applications, such as for gaming, object recognition or video processing, from mobile users (MUs) to cloudlet or cloud servers, which are connected to wireless access points, either directly or through finite-capacity backhaul links. In this paper, the design of a mobile cloud computing system is investigated by proposing the joint optimization of computing and communication resources with the aim of minimizing the energy required for offloading across all MUs under latency constraints at the application layer. The proposed design accounts for multiantenna uplink and downlink interfering transmissions, with or without cooperation on the downlink, along with the allocation of backhaul and computational resources and user selection. The resulting design optimization problems are nonconvex, and stationary solutions are computed by means of successive convex approximation techniques. Numerical results illustrate the advantages in terms of energy-latency tradeoff of the joint optimization of computing and communication resources, as well as the impact of system parameters, such as backhaul capacity, and of the network architecture.
Original language | English (US) |
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Article number | 7850968 |
Pages (from-to) | 787-802 |
Number of pages | 16 |
Journal | IEEE Transactions on Signal and Information Processing over Networks |
Volume | 3 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2017 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Computer Networks and Communications
Keywords
- 5G
- Application offloading
- backhaul
- cloudlet
- latency
- mobile cloud computing
- network MIMO
- successive convex approximation
- user selection