Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing

Ali, Abid; Iqbal, M. Tariq; Jamil, Harun; Akbar, Haji; Muthanna, Ammar; Ammi, Meryem; Althobaiti, Maha M.

doi:10.3390/s22010108

Cited by 21 publications

(12 citation statements)

References 57 publications

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“…Several studies have discussed about trust and authentication issues in fog but, there is no complete solution to the trust and authentication problems in the fog computing 117 . Some recent studies have stated that trust platform mechanism (TPM) and secure element (SE) can be used in fog computing applications to provide trust utility 118 …”

Section: Open Issues In Fog Computingmentioning

confidence: 99%

A systematic review of task scheduling approaches in fog computing

Bansal

Aggarwal

2022

Trans Emerging Tel Tech

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Due to increased use of IoT devices and data sensors a huge amount of data is being produced for processing in real-time. Fog computing has evolved as a solution for fast processing of data. To complete the data processing as per requirement of user, it is processed at fog nodes which are near the user. To complete work in a specified time with limited resources, task scheduling is performed. With the increased amount of data to be processed, the completion of task within given time in fog computing is a major challenge. So, scheduling of tasks and resources is a very important issue. A lot of research has been undertaken in recent years. In this survey, authors have reviewed various task scheduling algorithms suggested by researchers to meet the user requirements.The focus of this article is on diverse scheduling techniques being deployed in fog computing. An effort has been made to classify existing approaches, research issues and determine significant issues existing in this field. There are four major scheduling categories that are used by researchers namely, static, dynamic, heuristic, and hybrid. As per this study, 17% researchers deployed static, 23% dynamic, 47% heuristic, and 13% hybrid approaches, respectively.Analysis shows that for QoS (Quality of Service) parameters 19% researchers are focused on response time, 18% on cost and energy consumption, and 16% on makespan. For QoS parameter other factors have much smaller contribution in comparison to the above factors. In the tools used, researchers observed that 40% of the researches have used iFogSim, according to literature. Besides, this research article also discusses open issues and future work in the field of fog computing. This article also underlines various open issues and future directions in the field of fog computing.

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Section: Open Issues In Fog Computingmentioning

confidence: 99%

A systematic review of task scheduling approaches in fog computing

Bansal

Aggarwal

2022

Trans Emerging Tel Tech

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“…These task offloading is improved but with limited knowledge about task microservices. [13]. The battery and mobile device performance could be improved by offloading mobile tasks.…”

Section: Literature Reviewmentioning

confidence: 99%

“…MCC allows people to perform resource-intensive tasks on the cloud near mobile devices. Although tasks scheduling is part of the Mobile Devices, based on the modern application's size processing power they consume, tasks scheduling is one of the main concerns for mobile applications [1]. The mobile applications are somewhat like Augmented Reality, E-Transport, E-Healthcare, 2D/3D E-Gaming, and many more features needed to extract and process intelligent devices [2], [3].…”

Section: Introductionmentioning

confidence: 99%

A Cost and Energy Efficient Task Scheduling Technique to Offload Microservices Based Applications in Mobile Cloud Computing

Ali

Iqbal²

2022

IEEE Access

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The number of smartphone users and mobile devices has increased significantly. The Mobile Cloud Applications based on cloud computing have also been increased. The mobile apps can be used in Augmented Reality, E-Transportation, 2D/3-D Games, E-Healthcare, and Education. The modern cloudbased frameworks provide such services on Virtual Machines. The existing frameworks worked well, but these suffered the problems such as overhead, resource utilization, lengthy boot-time, and cost of running Mobile Applications. This study addresses these problems by proposing a Dynamic Decision-Based Task Scheduling Technique for Microservice-based Mobile Cloud Computing Applications (MSCMCC). The MSCMCC runs delay-sensitive applications and mobility with less cost than existing approaches. The study focused on Task Scheduling problems on heterogeneous Mobile Cloud servers. We further propose Task Scheduling and Microservices based Computational Offloading (TSMCO) framework to solve the Task Scheduling in steps, such as Resource Matching, Task Sequencing, and Task Scheduling. Furthermore, the experimental results elaborate that the proposed MSCMCC and TSMCO enhance the Mobile Server Utilization. The proposed system effectively minimizes the cost of healthcare applications by 25%, augmented reality by 23%, E-Transport tasks by 21%, and 3-D games tasks by 19%, the average boot-time of microservices applications by 17%, resource utilization by 36%, and tasks arrival time by 16%.INDEX TERMS Cloud computing, mobile cloud computing, task offloading, task sequencing, task scheduling, microservices.

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“…In mobile cloud environments, a new method for multilevel trust improvement for effective task scheduling was proposed [ 41 ].…”

Section: The Iot Applications Organizationmentioning

confidence: 99%

Real-Time Scheduling in IoT Applications: A Systematic Review

Khajeh

Saberikamarposhti

Rahmani

2022

Sensors

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The Internet of Things (IoT) is a telecommunication network in the next generation of applications with the rapid progress of wireless sensor network techniques that have touched many spheres of life today. Hardware, telephony, communications, storage, secure platforms, software and services, and data processing platforms are all part of the IoT environment. IoT sensors collect data from their environment and share it by connecting to the Internet gateway. These sensors often perform tasks without human intervention. This article aims to review real-time scheduling in the IoT to fully understand the issues raised in this area published from 2018 to 2022. A classification for IoT applications based on practical application is provided for selected studies. Selected studies include healthcare, infrastructure, industrial applications, smart city, commercial applications, environmental protection, and general IoT applications. Studies are sorted into groups based on related applications and compared based on indicators such as performance time, energy consumption, makespan, and assessment environments depending on the provided classification. Finally, this paper discusses all reviewed studies’ main concepts, disadvantages, advantages, and future work.

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Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing

Cited by 21 publications

References 57 publications

A systematic review of task scheduling approaches in fog computing

A systematic review of task scheduling approaches in fog computing

A Cost and Energy Efficient Task Scheduling Technique to Offload Microservices Based Applications in Mobile Cloud Computing

Real-Time Scheduling in IoT Applications: A Systematic Review

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