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  • Open Access


    Edge Computing Task Scheduling with Joint Blockchain and Task Caching in Industrial Internet

    Yanping Chen1,2,3, Xuyang Bai1,2,3,*, Xiaomin Jin1,2,3, Zhongmin Wang1,2,3, Fengwei Wang4, Li Ling4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2101-2117, 2023, DOI:10.32604/cmc.2023.035530

    Abstract Deploying task caching at edge servers has become an effective way to handle compute-intensive and latency-sensitive tasks on the industrial internet. However, how to select the task scheduling location to reduce task delay and cost while ensuring the data security and reliable communication of edge computing remains a challenge. To solve this problem, this paper establishes a task scheduling model with joint blockchain and task caching in the industrial internet and designs a novel blockchain-assisted caching mechanism to enhance system security. In this paper, the task scheduling problem, which couples the task scheduling decision, task… More >

  • Open Access


    TRS Scheduling for Improved QoS Performance in Cloud System

    G. John Samuel Babu1, M. Baskar2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1547-1559, 2023, DOI:10.32604/cmc.2023.033300

    Abstract Numerous methods are analysed in detail to improve task scheduling and data security performance in the cloud environment. The methods involve scheduling according to the factors like makespan, waiting time, cost, deadline, and popularity. However, the methods are inappropriate for achieving higher scheduling performance. Regarding data security, existing methods use various encryption schemes but introduce significant service interruption. This article sketches a practical Real-time Application Centric TRS (Throughput-Resource utilization–Success) Scheduling with Data Security (RATRSDS) model by considering all these issues in task scheduling and data security. The method identifies the required resource and their claim… More >

  • Open Access


    A Broker-Based Task-Scheduling Mechanism Using Replication Approach for Cloud Systems

    Abdulelah Alwabel*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2217-2232, 2023, DOI:10.32604/iasc.2023.033703

    Abstract The reliability and availability of cloud systems have become major concerns of service providers, brokers, and end-users. Therefore, studying fault-tolerance mechanisms in cloud computing attracts intense attention in industry and academia. The task-scheduling mechanisms can improve the fault-tolerance level of cloud systems. A task-scheduling mechanism distributes tasks to a group of instances to be executed. Much work has been undertaken in this direction to improve the overall outcome of cloud computing, such as improving service quality and reducing power consumption. However, little work on task scheduling has studied the problem of lost tasks from the… More >

  • Open Access


    Adaptive Resource Planning for AI Workloads with Variable Real-Time Tasks

    Sunhwa Annie Nam1, Kyungwoon Cho2, Hyokyung Bahn3,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6823-6833, 2023, DOI:10.32604/cmc.2023.035481

    Abstract AI (Artificial Intelligence) workloads are proliferating in modern real-time systems. As the tasks of AI workloads fluctuate over time, resource planning policies used for traditional fixed real-time tasks should be re-examined. In particular, it is difficult to immediately handle changes in real-time tasks without violating the deadline constraints. To cope with this situation, this paper analyzes the task situations of AI workloads and finds the following two observations. First, resource planning for AI workloads is a complicated search problem that requires much time for optimization. Second, although the task set of an AI workload may… More >

  • Open Access


    A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

    Abdulaziz Alhubaishy1,*, Abdulmajeed Aljuhani2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2461-2481, 2023, DOI:10.32604/csse.2023.032217

    Abstract In a cloud environment, consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost. On the other hand, Cloud Service Providers (CSPs) seek to maximize their profits by attracting and serving more consumers based on their resource capabilities. The literature has discussed the problem by considering either consumers’ needs or CSPs’ capabilities. A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task… More >

  • Open Access


    Remote Sensing Data Processing Process Scheduling Based on Reinforcement Learning in Cloud Environment

    Ying Du1,2, Shuo Zhang1,2, Pu Cheng3,*, Rita Yi Man Li4, Xiao-Guang Yue5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1965-1979, 2023, DOI:10.32604/cmes.2023.024871

    Abstract Task scheduling plays a crucial role in cloud computing and is a key factor determining cloud computing performance. To solve the task scheduling problem for remote sensing data processing in cloud computing, this paper proposes a workflow task scheduling algorithm---Workflow Task Scheduling Algorithm based on Deep Reinforcement Learning (WDRL). The remote sensing data process modeling is transformed into a directed acyclic graph scheduling problem. Then, the algorithm is designed by establishing a Markov decision model and adopting a fitness calculation method. Finally, combine the advantages of reinforcement learning and deep neural networks to minimize make-time More >

  • Open Access


    Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

    Qiqi Zhang1, Shaojin Geng2, Xingjuan Cai1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1863-1900, 2023, DOI:10.32604/cmes.2023.022287

    Abstract Cloud computing technology is favored by users because of its strong computing power and convenient services. At the same time, scheduling performance has an extremely efficient impact on promoting carbon neutrality. Currently, scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak hours. Therefore, the scheduling problem has promising application prospects under the multi-cloud environment. This paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between tasks. More > Graphic Abstract

    Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

  • Open Access


    Improvised Seagull Optimization Algorithm for Scheduling Tasks in Heterogeneous Cloud Environment

    Pradeep Krishnadoss*, Vijayakumar Kedalu Poornachary, Parkavi Krishnamoorthy, Leninisha Shanmugam

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2461-2478, 2023, DOI:10.32604/cmc.2023.031614

    Abstract Well organized datacentres with interconnected servers constitute the cloud computing infrastructure. User requests are submitted through an interface to these servers that provide service to them in an on-demand basis. The scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem category. Task scheduling in cloud poses numerous challenges impacting the cloud performance. If not handled properly, user satisfaction becomes questionable. More recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling… More >

  • Open Access


    IoMT-Cloud Task Scheduling Using AI

    Adedoyin A. Hussain1,2,*, Fadi Al-Turjman3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1345-1369, 2023, DOI:10.32604/cmes.2023.022783

    Abstract The internet of medical things (IoMT) empowers patients to get adaptable, and virtualized gear over the internet. Task scheduling is the most fundamental problem in the IoMT-cloud since cloud execution commonly relies on it. Thus, a proposition is being made for a distinct scheduling technique to suitably meet these solicitations. To manage the scheduling issue, an artificial intelligence (AI) method known as a hybrid genetic algorithm (HGA) is proposed. The proposed AI method will be justified by contrasting it with other traditional optimization and AI scheduling approaches. The CloudSim is utilized to quantify its effect More >

  • Open Access


    An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

    Hamayun Khan1,*, Irfan Ud Din2, Arshad Ali3, Mohammad Husain3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2097-2113, 2023, DOI:10.32604/cmc.2023.032999

    Abstract Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip (MPSoC) has become an integral chip design issue for multiprocessor systems. The performance measurement of computational systems is changing with the advancement in technology. Due to shrinking and smaller chip size power densities on-chip are increasing rapidly that increasing chip temperature in multi-core embedded technologies. The operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor (CMOS) circuits because high on-chip temperature adversely affects the life span of… More >

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