Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/3581
Title: | LETO: An Efficient Load Balanced Strategy for Task Offloading in IoT-Fog Systems |
Authors: | Swain, Chittaranjan Sahoo, Manmath Narayan Satpathy, Anurag |
Keywords: | Load Balancing, , Matching Theory, Max-Min Quota IoT, Fog Systems, Task Offloading |
Issue Date: | Sep-2021 |
Citation: | International Conference on Web Services (ICWS), Sept 5-11, 2021, USA |
Abstract: | The resource-constrained IoT devices often offload tasks to Fog nodes (FNs) owing to the intermittent WAN delays and multi-hopping by executing at remote cloud servers. An efficient allocation strategy satisfies the users’ requirements by ensuring minimum offloading delays and provides a balanced assignment from the service providers’ (SPs) viewpoint. This paper presents a model called LETO that reduces the total offloading delay for real-time tasks and achieves a balanced assignment across FNs. The overall problem is modeled as a one-to-many matching game with maximum and minimum quotas. Owing to the deferred acceptance algorithm (DAA) inapplicability, we use a proficient version of the DAA called multi-stage deferred acceptance algorithm (MSDA) to obtain a fair and Pareto-optimal assignment of tasks to FNs. Extensive simulations confirm that LETO can achieve a more balanced assignment compared to the baseline algorithms. |
Description: | Copyright of this paper is with proceedings publisher |
URI: | http://hdl.handle.net/2080/3581 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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MS_ICWS2021.pdf | 328.12 kB | Adobe PDF | View/Open |
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