Dynamic collaborative task offloading for delay minimization in the heterogeneous fog computing systems

Fog computing systems have been widely integrated in IoT-based applications to improve quality of services (QoS) such as low response service delays. This improvement is enabled by task offloading schemes, which perform task computation near the task generation sources (i.e., IoT devices) on behalf...

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Vydané v:Journal of communications and networks Ročník 25; číslo 2; s. 244 - 252
Hlavní autori: Tran-Dang, Hoa, Kim, Dong-Seong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Seoul The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.04.2023
한국통신학회
Predmet:
Cloud computing
Collaboration
Computation offloading
Delay
Devices
Edge computing
Parallel processing
전자/정보통신공학
ISSN:1229-2370, 1976-5541
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Popis
Shrnutí:Fog computing systems have been widely integrated in IoT-based applications to improve quality of services (QoS) such as low response service delays. This improvement is enabled by task offloading schemes, which perform task computation near the task generation sources (i.e., IoT devices) on behalf of remote cloud servers. However, reducing delay remains challenging for offloading strategies owing to the resource limitations of fog devices. In addition, a high rate of task requests combined with heavy tasks (i.e., large task size) may cause a high imbalance of the workload distribution among the heterogeneous fog devices, which severely impacts the offloading performance in terms of delay. To address these issues, this paper proposes a dynamic collaborative task offloading (DCTO) approach, which is based on the resource states of fog devices, to dynamically derive the task offloading policy. Accordingly, a task can be executed by either a single fog or multiple fog devices through the parallel computation of subtasks to reduce the task execution delay. Through extensive simulation analysis, the proposed offloading solution showed potential advantages in reducing the average delay significantly in systems with a high rate of service requests and heterogeneous fog environment compared with the existing solutions. In addition, the proposed scheme can be implemented online owing to its low computational complexity compared with the algorithms proposed in related works.
Bibliografia:ObjectType-Article-1
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ISSN:1229-2370
1976-5541
DOI:10.23919/JCN.2023.000008