Abstract
In this paper, we study the priority-aware task data offloading in edge computing-assisted healthcare service provisioning. The edge server aims to provide additional computing resources to the end-users for processing the delay-sensitive tasks. However, at the same time, it becomes a challenging issue when some of the tasks demand lower response time compared to the other tasks. We present a priority-aware task offloading and scheduling strategy that allocates the computing resources to the high-priority tasks. The hard-deadline tasks are processed first. Later, the remaining computing resources are used to tolerate longer average response time for the soft-deadline tasks. Moreover, we derive a lower bound of the average response time for all hard- and soft-deadline tasks. Through extensive simulations, we show that the proposed task scheduling manages to allocate the computing resources of both end-users and edge server to the hard-deadline tasks while scheduling the soft-deadline tasks with low priority.
| Original language | English |
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| Publication date | Dec 2020 |
| Publication status | Published - Dec 2020 |
| Event | 2020 IEEE Global Communications Conference - Taipei, Taiwan + Online (Hybrid), Taipei, Taiwan Duration: 7 Dec 2020 → 11 Dec 2020 https://globecom2020.ieee-globecom.org/ |
Conference
| Conference | 2020 IEEE Global Communications Conference |
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| Location | Taipei, Taiwan + Online (Hybrid) |
| Country/Territory | Taiwan |
| City | Taipei |
| Period | 07/12/2020 → 11/12/2020 |
| Internet address |
Keywords
- Delay-sensitive tasks
- E-Health
- Edge Computing
- Fog computing
- Task offloading