Joint Computing and Communication Resource Allocation for TDMA-Based Binary Computation Offloading

Mobile edge computing systems provide computational resources at the network access point that can be shared among the attached devices. Effective utilization of these resources requires careful selection of the offloading devices and joint allocation of the computing and communication resources. We...

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Bibliographic Details
Published in:Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 9136 - 9140
Main Authors: Manouchehrpour, M. Amin, Davidson, Timothy N.
Format: Conference Proceeding
Language:English
Published: IEEE 14.04.2024
Subjects:
computation offloading
Computational modeling
Computer architecture
Convex functions
mobile edge computing
Multi-access edge computing
Numerical models
Signal processing
Signal processing algorithms
ISSN:2379-190X
Online Access:Get full text
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Summary:Mobile edge computing systems provide computational resources at the network access point that can be shared among the attached devices. Effective utilization of these resources requires careful selection of the offloading devices and joint allocation of the computing and communication resources. We develop an efficient resource allocation technique that exploits the temporal structure of computation offloading. Our initial formulation is combinatoric, but insight into the energy required to communicate a given message reveals effective heuristics for the allocation of computing resources, and a reduced-dimension convex formulation for the communication resources. Our numerical results demonstrate that the proposed approach provides performance that is close to that of the jointly optimal solution.
ISSN:2379-190X
DOI:10.1109/ICASSP48485.2024.10448508