Task Offloading for Scientific Workflow Application in Mobile Cloud

Zhang, Feifei; Ge, Jidong; Li, Zhongjin; Li, Chuanyi; Huang, Zifeng; Kong, Lingqi; Luo, Bin

doi:10.5220/0006364501360148

Cited by 4 publications

(3 citation statements)

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“…The proposed algorithm is implemented in RDA. Using Equations ( 1) to (3), a fitness function is introduced, and the constraints are enforced on Equations ( 4) to (13). The best resource for a request is discovered using the function that is defined based on these equations.…”

Section: Rdmom Algorithmmentioning

confidence: 99%

“…Furthermore, the workload may be suddenly increased, so the fog resources are reduced and extra unexpected delay is incurred during the execution of requests 12 . Data or applications always need high processing speeds, and limited bandwidth to process data and costs of data transmission are the issues that should be considered in fog computing 13,14 …”

Section: Introductionmentioning

confidence: 99%

“…12 Data or applications always need high processing speeds, and limited bandwidth to process data and costs of data transmission are the issues that should be considered in fog computing. 13,14 In the last few years, many studies have focused on the discovery and allocation of resources. These studies can be divided into four groups (conducted on IoT, fog/edge, cloud computing, and combined IoT-fog/edge) based on the used platforms for which resource discovery is provided.…”

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confidence: 99%

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A mathematical optimization model using red deer algorithm for resource discovery in CloudIoT

Goudarzi

Rahmani

Mosleh

2022

Trans Emerging Tel Tech

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The Internet of Things (IoT) and cloud computing are new concepts in revolutionized communication and information technologies. Different technologies, for example, transportation and healthcare, can benefit from Cloud of Things (CloudIoT) for mobile and fixed resource applications with great promises. Fixed and mobile resources are very important items in the CloudIoT paradigm because of the need for an appropriate discovery mechanism. In the present study, a mathematical optimization model is proposed for the minimization of bandwidth, cost, and response time of CloudIoT platforms with a special focus on the role of mobile and fixed resources in resource discovery. Additionally, this study presents a heuristic resource discovery algorithm using a mathematical optimization model (RDMOM). The mixed‐integer non‐linear programming is used to design the discovery mechanism. Furthermore, the optimization problem is solved using the red deer algorithm. Finally, the simulation results show a significant reduction in the latency, resource efficiency, and energy consumption, as well as an improvement in availability and success ratio, compared to previous algorithms. The RDMOM algorithm significantly improves the success ratio, energy consumption, resource efficiency, availability, and latency, respectively, by 18%, 21%, 24%, 17%, and 21% in comparison to other algorithms.

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Section: Rdmom Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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