Rahman, AU and Ghatak, G and De Domenico, A (2020) An Online Algorithm for Computation Offloading in Non-Stationary Environments. In: IEEE Communications Letters, 24 (10). pp. 2167-2171.
|
PDF
IEEE_com_let_24-10_2167-2171_2020.pdf - Published Version Download (712kB) | Preview |
Abstract
We consider the latency minimization problem in a task-offloading scenario, where multiple servers are available to the user equipment for outsourcing computational tasks. To account for the temporally dynamic nature of the wireless links and the availability of the computing resources, we model the server selection as a multi-armed bandit (MAB) problem. In the considered MAB framework, rewards are characterized in terms of the end-to-end latency. We propose a novel online learning algorithm based on the principle of optimism in the face of uncertainty, which outperforms the state-of-the-art algorithms by up to 35 reduction in latency. Our results highlight the significance of heavily discounting the past rewards in dynamic environments. © 1997-2012 IEEE.
| Item Type: | Journal Article |
|---|---|
| Publication: | IEEE Communications Letters |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Additional Information: | The copyright for this article belongs to the Author(s). |
| Keywords: | Mobile telecommunication systems, Computation offloading; Computational task; Dynamic environments; End to end latencies; Minimization problems; Non-stationary environment; Online learning algorithms; State-of-the-art algorithms, Learning algorithms |
| Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
| Date Deposited: | 12 Jan 2023 08:40 |
| Last Modified: | 12 Jan 2023 08:40 |
| URI: | https://eprints.iisc.ac.in/id/eprint/79055 |
Actions (login required)
 |
View Item |
