ISSN 0253-2778

CN 34-1054/N

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Open AccessOpen Access JUSTC Original Paper

Cost optimization of request dispatching and container deployment in cloudlets

  • School of Computer Science and Technology,University of Science and Technology of China,hefei 230027,china

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2019.10.007
  • Received Date: 28 March 2019
  • Accepted Date: 28 May 2019
  • Rev Recd Date: 28 May 2019
  • Publish Date: 31 October 2019
    Abstract

  • Abstract

    With the development of the Internet of Things (IoT), cloudlet is serving more low-latency, high-bandwidth applications. The application request is dynamic in time and space. If a cloudlet only processes the surrounding requests, some cloudlets will be overloaded while others are underloaded. In addition, IoT applications vary in importance. Some unimportant services with large requests may preempt the cloudlet resources, resulting in critical services unable to be executed. Cloudlet load imbalance and critical service starvation will increase the cost of the cloud infrastructure provider. Cost optimization of request dispatching and container deployment in container-based cloudlets are investigated and a cost optimization greedy algorithm named CO-Greedy is proposed which optimizes cost by dispatching the request to the surrounding cloudlet. The experimental results show that the algorithm has better performance in all scenarios.

    Abstract

    With the development of the Internet of Things (IoT), cloudlet is serving more low-latency, high-bandwidth applications. The application request is dynamic in time and space. If a cloudlet only processes the surrounding requests, some cloudlets will be overloaded while others are underloaded. In addition, IoT applications vary in importance. Some unimportant services with large requests may preempt the cloudlet resources, resulting in critical services unable to be executed. Cloudlet load imbalance and critical service starvation will increase the cost of the cloud infrastructure provider. Cost optimization of request dispatching and container deployment in container-based cloudlets are investigated and a cost optimization greedy algorithm named CO-Greedy is proposed which optimizes cost by dispatching the request to the surrounding cloudlet. The experimental results show that the algorithm has better performance in all scenarios.
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    • References(11)
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    YANG L, CAO J N, LIANG G Q, et al. Cost aware service placement and load dispatching in mobile cloud systems[J]. IEEE Transactions on Computers, 2016, 65(5):1440-1452.
    [7]
    WANG W, ZHAO Y L, TORNATORE M, et al. Virtual machine placement and workload assignment for mobile edge computing[C]// IEEE 6th International Conference on Cloud Networking. Prague, Czech Republic: IEEE, 2017: 1-6.
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    BORGETTO D, MAURER M, DA-COSTA G, et al. Energy-efficient and SLA-aware management of IaaS clouds[C]// Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet. Madrid, Spanish: ACM, 2012, No.25:1-10.
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    WU L L, GARG S K, VERSTEEG S, et al. SLA-based resource provisioning for hosted software-as-a-service applications in cloud computing environments[J]. IEEE Transactions on services computing, 2014, 7(3):465-485.
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    ZHANG F F, GE J D, LI ZJ, et al. A load-aware resource allocation and task scheduling for the emerging cloudlet system[J]. Future Generation Computer Systems, 2018, 87:438-456.
    [11]
    YOUSEFPOUR A, PATIL A, ISHIGAKI G, et al. Fogplan: A lightweight QoS-aware dynamic fog service provisioning framework[J/E]. Internet of Things Journal /https://personal.utdallas.edu/~ashkan/papers/QDFSP.pdf, 2019.)
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    [1]
    SATYANARAYANAN M, BAHL P, CACERES R, et al. The case for VM-based cloudlets in mobile computing[J]. IEEE Pervasive Computing, 2009, 8(4):14-23.
    [2]
    TRAN T X, HAJISAMI A, PANDEY P, et al. Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges[J]. IEEE Communications Magazine, 2017, 55(4): 54-61.
    [3]
    ISMAIL B I, GOORTANI E M, AB KARIM M B, et al. Evaluation of docker as edge computing platform[C]// IEEE Conference on Open Systems. Bandar Melaka, Malaysia: IEEE, 2015: 130-135.
    [4]
    BELLAVISTA P, ZANNI A. Feasibility of fog computing deployment based on docker containerization over RaspberryPi[C]// Proceedings of the 18th International Conference on Distributed Computing and Networking. Hyderabad, India: ACM, 2017: 1-10.
    [5]
    FARRIS I, TALEB T, FLINCK H, et al. Providing ultra-short latency to user-centric 5G applications at the mobile network edge[J]. Transactions on Emerging Telecommunications Technologies, 2018, 29(4): e3169(1-13).
    [6]
    YANG L, CAO J N, LIANG G Q, et al. Cost aware service placement and load dispatching in mobile cloud systems[J]. IEEE Transactions on Computers, 2016, 65(5):1440-1452.
    [7]
    WANG W, ZHAO Y L, TORNATORE M, et al. Virtual machine placement and workload assignment for mobile edge computing[C]// IEEE 6th International Conference on Cloud Networking. Prague, Czech Republic: IEEE, 2017: 1-6.
    [8]
    BORGETTO D, MAURER M, DA-COSTA G, et al. Energy-efficient and SLA-aware management of IaaS clouds[C]// Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet. Madrid, Spanish: ACM, 2012, No.25:1-10.
    [9]
    WU L L, GARG S K, VERSTEEG S, et al. SLA-based resource provisioning for hosted software-as-a-service applications in cloud computing environments[J]. IEEE Transactions on services computing, 2014, 7(3):465-485.
    [10]
    ZHANG F F, GE J D, LI ZJ, et al. A load-aware resource allocation and task scheduling for the emerging cloudlet system[J]. Future Generation Computer Systems, 2018, 87:438-456.
    [11]
    YOUSEFPOUR A, PATIL A, ISHIGAKI G, et al. Fogplan: A lightweight QoS-aware dynamic fog service provisioning framework[J/E]. Internet of Things Journal /https://personal.utdallas.edu/~ashkan/papers/QDFSP.pdf, 2019.)
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