Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading
University of Hong Kong · LG (South Korea)
Abstract
Mobile-edge computation offloading (MECO) off-loads intensive mobile computation to clouds located at the edges of cellular networks. Thereby, MECO is envisioned as a promising technique for prolonging the battery lives and enhancing the computation capacities of mobiles. In this paper, we study resource allocation for a multiuser MECO system based on time-division multiple access (TDMA) and orthogonal frequency-division multiple access (OFDMA). First, for the TDMA MECO system with infinite or finite cloud computation capacity, the optimal resource allocation is formulated as a convex optimization problem for minimizing the weighted sum mobile energy consumption under the constraint on computation latency. The…
Citation impact
- FWCI
- 131.11
- Percentile
- 100%
- References
- 33
Authors
4Topics & keywords
- Computer science
- Computation offloading
- Time division multiple access
- Resource allocation
- Mobile edge computing
- Mathematical optimization
- Energy consumption
- Orthogonal frequency-division multiple access
- Affordable and clean energy