QoS aware productive and resourceful service allocation in fog for multimedia applications

被引:0
作者
Saroja, S. [1 ]
Madavan, R. [2 ]
Revathi, T. [3 ]
Hu, Yu-Chen [4 ,5 ]
机构
[1] Natl Inst Technol, Dept Comp Applicat, Trichy, India
[2] K Ramakrishnan Coll Technol Autonomous, Dept Elect & Elect Engn, Trichy, Tamil Nadu, India
[3] Mepco Schlenk Engn Coll, Dept Informat Technol, Sivakasi, India
[4] TungHai Univ, Dept Comp Sci, 1727,Sec 4,Taiwan Blvd, Taichung 407224, Taiwan
[5] Providence Univ, Dept Comp Sci & Informat Management, 200,Sec 7,Taiwan Blvd, Taichung 43301, Taiwan
关键词
Resource allocation; Makespan; Fog computing; League championship algorithm; QoS; ALGORITHM; CLOUD;
D O I
10.1007/s11042-023-17387-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fog computing is a computer architecture consisting of fog nodes, a collection of near-user edge devices. These fog nodes collaborate to perform computational services like data retrieval, processing, storage, etc. Resource allocation is one of the most critical and challenging problems in the fog environment for industrial applications. The significant aspects to consider while allocating resources are response time, throughput, and energy consumption. The proposed work formulated the resource allocation problem as a bi-objective minimization problem. The main aim of the work is to reduce energy consumption and makespan while allocating service requests to virtual machines. The proposed technique uses the league championship algorithm to select an efficient resource for productive and resourceful service allocation of tasks in fog computing. The proposed algorithm's performance is assessed by comparing it to three well-known metaheuristic algorithms. Finally, the simulation results show that the proposed algorithm is superior in terms of makespan and energy consumption.
引用
收藏
页码:44379 / 44396
页数:18
相关论文
共 39 条
  • [1] A checkpointed league championship algorithm-based cloud scheduling scheme with secure fault tolerance responsiveness
    Abdulhamid, Shafi'i Muhammad
    Abd Latiff, Muhammad Shafie
    [J]. APPLIED SOFT COMPUTING, 2017, 61 : 670 - 680
  • [2] A Resources Representation For Resource Allocation In Fog Computing Networks
    Abouaomar, Amine
    Cherkaoui, Soumaya
    Kobbane, Abdellatif
    Dambri, Oussama Abderrahmane
    [J]. 2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [3] A data aggregation based approach to exploit dynamic spatio-temporal correlations for citywide crowd flows prediction in fog computing
    Ali, Ahmad
    Zhu, Yanmin
    Zakarya, Muhammad
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (20) : 31401 - 31433
  • [4] Enhanced grouping league championship and optics inspired optimization algorithms for scheduling a batch processing machine with job conflicts and non-identical job sizes
    Alizadeh, Nasrin
    Kashan, Ali Husseinzadeh
    [J]. APPLIED SOFT COMPUTING, 2019, 83
  • [5] Souza VB, 2016, IEEE GLOB COMM CONF
  • [6] Barbulescu M, 2013, ROEDUNET INT C NETW, DOI [10.1109/RoEduNet.2013.6714197, DOI 10.1109/ROEDUNET.2013.6714197]
  • [7] Ben Lahmar I, 2020, 2020 FIFTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC), P86, DOI [10.1109/fmec49853.2020.9144705, 10.1109/FMEC49853.2020.9144705]
  • [8] da Silva RAC, 2018, IEEE ICC
  • [9] Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption
    Deng, Ruilong
    Lu, Rongxing
    Lai, Chengzhe
    Luan, Tom H.
    Liang, Hao
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2016, 3 (06): : 1171 - 1181
  • [10] Fault tolerant resource allocation in fog environment using game theory-based reinforcement learning
    Divya, V
    Sri, Leena R.
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (16)