Delay Sensitive Application Partitioning and Task Scheduling in Mobile Edge Cloud Prototyping

Lakhan, Abdullah; Sajnani, Dileep Kumar; Tahir, Muhammad Faizan; Aamir, Muhammad; Lodhi, Rakhshanda

doi:10.1007/978-3-030-22316-8_6

Cited by 17 publications

(24 citation statements)

References 14 publications

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“…Lakhan et al [100]- [102] propose a task offloading strategy for optimizing the energy consumed by the mobile device and the edge-cloud resources (i.e., VMs) for a user. The proposed strategy first employs the min-cut algorithm [144] to partition the workflow application into two kinds of tasks, i.e., local execution and remote execution, for minimize the mobile energy consumption.…”

Section: B: Energy Optimizationmentioning

confidence: 99%

A Survey and Taxonomy on Task Offloading for Edge-Cloud Computing

Wang

Huang

et al. 2020

IEEE Access

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Edge-cloud computing, combining the benefits of both edge computing and cloud computing, is one of the most promising ways to address the resource insufficiency of smart devices. Task offloading is an important challenge must be addressed for edge-cloud computing in practice, which decides the place and the time for performing each task. Even though there is existing research focusing on the task offloading in edge-cloud computing, a lot of problems should be solved before the application of these offloading technologies. Thus, in this article, we first propose a taxonomy of task offloading in edge-cloud environments to investigate and classify related research articles, and then summarize several challenges which have not been addressed for future research directions on this area to promote the development of edge-cloud market.

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Section: B: Energy Optimizationmentioning

confidence: 99%

A Survey and Taxonomy on Task Offloading for Edge-Cloud Computing

Wang

Huang

et al. 2020

IEEE Access

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“…According to [36,37,38,79] it is an extension of blended scope learning, an enquiry supported by learning instruction and tools, with multiple factors as flexibility, active engagements often in learning as compare to blended passive concepts [36,37,38]. The concept of "Flipped classroom" was also expressed as "Inverted Classrooms" coined by some researchers [5] in 2000.…”

Section: Flipped Learning and Tertiary Educationmentioning

confidence: 99%

A Review on State of the Art in Flipped Classroom Technology A Blended E-Learning

2021

IJETER

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Flipped is an emerging mode of blended e-learning, as blended is mix mode of learning to enhance the skills of students, saving the time and cost either sides (students and educators). Flipped classroom is such as an e-learning blended approach in which instructions can be hovered into individual and groups, interactively to exchange and solving the assigned problems. Flipped classroom approach presents the dynamic, interactive and user’s friendly environments for in class and online blended learning. This kind of mode leads students to enhance their interpersonal skills, collaborate the experiences, and innovate new horizons by mutual activities for the given problems. The flipped mode has at least four dimensions; friendly easy environment, supporting culture for learning, contents availability when offline, minimizing time cost, trained educators/professionals and reducing repetition of learning content’s cost. In Flipped model of learning, first students go to seeking the exposure of problems by visiting the contents, materials, videos and other materials before getting in the classroom in person, fully aware to share or inquire the problem related matters in the class, its inverse approach against traditional institutional learning model. This is very effective mode of learningfor activity based and assignment-based learning strategies prior commencing class, fruitfulfeedback can be shared and reducing the tutorial part.

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“…The paper [12] investigates the offloaded tasks of mobile devices at heterogeneous cloudlets while improving the total cost-efficiency. The communication time and computation time, along with costs under deadline, are taken into consideration by the study.…”

Section: Related Workmentioning

confidence: 99%

“…• Baseline 1: We implement the virtual machines based computation offloading framework for the testing. These studies adopted aforementioned framework [12]- [14]. The goal was to offload the entire mobile application to the cloud server.…”

Section: A Baseline Framework and Algorithmic Approachesmentioning

confidence: 99%

Microservice Based Computational Offloading Framework and Cost Efficient Task Scheduling Algorithm in Heterogeneous Fog Cloud Network

Zhao

Huang

2020

IEEE Access

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Nowadays, the usage of the fog cloud-based Internet of Things (IoT) applications among users has been growing progressively. These applications may be E-Transport, E-Healthcare, Augmented Reality, and 3D-Game. Generally, contemporary cloud frameworks offer services based on virtual machines. These frameworks incurred with following issues such as long boot-time, overhead and unnecessary cost to run the IoT applications. We propose a new Microservice container fog system (MSCFS) based framework to run the mobility and delay-sensitive applications with minimum cost. The study the cost-efficient task scheduling problem in the heterogeneous fog servers. Furthermore, the study introduces the Cost Aware Computational Offloading and task scheduling (CACOTS)framework, which solves the task scheduling into multiple steps. Such as task sequencing step, resource matching step and scheduling step. The experimental results prove that the proposed MSCFS and CACOTS schemes can enhance server utilization. As decrease the services latency and average services bootup time more effectively, and minimize costs. INDEX TERMS Task scheduling, fog servers, boot-up time, microservices, container.

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Delay Sensitive Application Partitioning and Task Scheduling in Mobile Edge Cloud Prototyping

Cited by 17 publications

References 14 publications

A Survey and Taxonomy on Task Offloading for Edge-Cloud Computing

A Survey and Taxonomy on Task Offloading for Edge-Cloud Computing

A Review on State of the Art in Flipped Classroom Technology A Blended E-Learning

Microservice Based Computational Offloading Framework and Cost Efficient Task Scheduling Algorithm in Heterogeneous Fog Cloud Network

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