Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing

Hussain, Mehboob; Wei, L. F.; Lakhan, Abdullah; Wali, Samad; Ali, Soragga; Hussain, Abid

doi:10.1016/j.suscom.2021.100517

Cited by 73 publications

(64 citation statements)

References 28 publications

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“…However, they did not consider the security mechanism in the study. Eivy et al [3], Adzic et al [7], Adzic et al [7] and Lynn et al [8] and van et al [9] suggested serverless based fog-cloud where instead of virtual machines they run functions inside containers. The objective is to minimize the execution and offloading cost of applications.…”

Section: Related Workmentioning

confidence: 99%

“…The Internet of Medical Things (IoMT) system is an emerging healthcare monitor paradigm that consists of devices, sensors, wireless network, and fog-cloud computing [1,2]. The sensors could be mobile devices, heartbeat sensors, blood pressure IoT sensors, ECG sensors, and many sensors connected with mobile devices [3]. The invention of the 5G communication technology encourages more and more devices to intercommunicate with external resources.…”

Section: Introductionmentioning

confidence: 99%

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Smart-Contract Aware Ethereum and Client-Fog-Cloud Healthcare System

Lakhan

Mohammed

Rashid

et al. 2021

Sensors

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The Internet of Medical Things (IoMT) is increasingly being used for healthcare purposes. IoMT enables many sensors to collect patient data from various locations and send it to a distributed hospital for further study. IoMT provides patients with a variety of paid programmes to help them keep track of their health problems. However, the current system services are expensive, and offloaded data in the healthcare network are insecure. The research develops a new, cost-effective and stable IoMT framework based on a blockchain-enabled fog cloud. The study aims to reduce the cost of healthcare application services as they are processing in the system. The study devises an IoMT system based on different algorithm techniques, such as Blockchain-Enable Smart-Contract Cost-Efficient Scheduling Algorithm Framework (BECSAF) schemes. Smart-Contract Blockchain schemes ensure data consistency and validation with symmetric cryptography. However, due to the different workflow tasks scheduled on other nodes, the heterogeneous, earliest finish, time-based scheduling deals with execution under their deadlines. Simulation results show that the proposed algorithm schemes outperform all existing baseline approaches in terms of the implementation of applications.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart-Contract Aware Ethereum and Client-Fog-Cloud Healthcare System

Lakhan

Mohammed

Rashid

et al. 2021

Sensors

Self Cite

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show abstract

“…In this subpart, the benchmark datasets provided by [11] are used to compare EHEFT-R, algorithms proposed in reference [12], and HEFT. According to [12], the problem cases are classified into 12 categories in the benchmark, and 100 different cases are included in each category. Each problem case in dataset records the makespan and energy consumption for the 512_16 data, i.e.…”

Section: Large-scale Benchmarkmentioning

confidence: 99%

EHEFT-R: multi-objective task scheduling scheme in cloud computing

Zhang

Sun

2021

Complex Intell. Syst.

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In cloud computing, task scheduling and resource allocation are the two core issues of the IaaS layer. Efficient task scheduling algorithm can improve the matching efficiency between tasks and resources. In this paper, an enhanced heterogeneous earliest finish time based on rule (EHEFT-R) task scheduling algorithm is proposed to optimize task execution efficiency, quality of service (QoS) and energy consumption. In EHEFT-R, ordering rules based on priority constraints are used to optimize the quality of the initial solution, and the enhanced heterogeneous earliest finish time (HEFT) algorithm is used to ensure the global performance of the solution space. Simulation experiments verify the effectiveness and superiority of EHEFT-R.

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“…The IoMT is a network that is composed of medical sensors, wireless technology and distributed cloud computing technologies [2]. Therefore, the combination of IoMT and healthcare devices can improve the quality of human life and provide better care services and create a more cost-effective system [3]. Recently, many IoMT-based applications have been developed by different shareholders to deal with other diseases, such as E-healthcare sensor-based applications and E-real-time-healthcare applications [4].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, developers of serverless applications are not concerned with the container, VM, or physical server capacity planning, configuration, management, maintenance, fault tolerance, or scaling. In the literature, many studies [2,3,5,7,8,11,12] proposed different systems, architectures, and heuristicsbased IoMT network to solve the offloading and scheduling problem of workflow and fine-grained applications. These studies improved devices' battery lives, offloading cost and the obtained Service Level Agreement (SLA) and Quality of Service (QoS) applications during their problem formulation.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

et al. 2021

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The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan.

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Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing

Cited by 73 publications

References 28 publications

Smart-Contract Aware Ethereum and Client-Fog-Cloud Healthcare System

Smart-Contract Aware Ethereum and Client-Fog-Cloud Healthcare System

EHEFT-R: multi-objective task scheduling scheme in cloud computing

Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

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