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  • Open Access

    ARTICLE

    TSLBS: A Time-Sensitive and Load Balanced Scheduling Approach to Wireless Sensor Actor Networks

    Morteza Okhovvat, Mohammad Reza Kangavari*

    Computer Systems Science and Engineering, Vol.34, No.1, pp. 13-21, 2019, DOI:10.32604/csse.2019.34.013

    Abstract Existing works on scheduling in Wireless Sensor Actor Networks (WSANs) are mostly concerned with energy savings and ignore time constraints and thus increase the make-span of the network. Moreover, these algorithms usually do not consider balance of workloads on the actor nodes and hence, sometimes some of the actors are busy when some others are idle. These problem causes the actors are not utilized properly and the actors’ lifetime is reduced. In this paper we take both time awareness and balance of workloads on the actor in WSANs into account and propose a convex optimization model (TAMMs) to minimize make-span.… More >

  • Open Access

    ARTICLE

    Virtual Machine Based on Genetic Algorithm Used in Time and Power Oriented Cloud Computing Task Scheduling

    Tongmao Ma1,2, Shanchen Pang1, Weiguang Zhang1, Shaohua Hao1

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115

    Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >

  • Open Access

    ARTICLE

    QoS-Aware Energy-Efficient Task Scheduling on HPC Cloud Infrastructures Using Swarm-Intelligence Meta-Heuristics

    Amit Chhabra1, *, Gurvinder Singh2, Karanjeet Singh Kahlon2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 813-834, 2020, DOI:10.32604/cmc.2020.010934

    Abstract Cloud computing infrastructure has been evolving as a cost-effective platform for providing computational resources in the form of high-performance computing as a service (HPCaaS) to users for executing HPC applications. However, the broader use of the Cloud services, the rapid increase in the size, and the capacity of Cloud data centers bring a remarkable rise in energy consumption leading to a significant rise in the system provider expenses and carbon emissions in the environment. Besides this, users have become more demanding in terms of Quality-of-service (QoS) expectations in terms of execution time, budget cost, utilization, and makespan. This situation calls… More >

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