SLA-WS: SLA-based workload scheduling technique in multi-cloud platform

被引：0
作者：
Arundhati Nelli
Rashmi Jogdand
机构：
[1] KLS Gogte Institute of Technology,Department of Computer Science and Engineering
来源：
Journal of Ambient Intelligence and Humanized Computing | 2023年 / 14卷
关键词：
Cloud computing; Heterogeneous computing environment; Multi-objective optimization problem; Resource provisioning; Work scheduling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Real-time workload execution resource provisioning with SLA prerequisite in multi-cloud platform is considered to a difficult job. Data intensive workload is composed direct acyclic graph (DAG); thus, there exist high dependency among different subtask with varying quality of service (QoS) prerequisite. The existing workload scheduling is designed using multi-objective parameter such as minimizing time and cost; however, reducing delay and energy overhead is not considered. This paper presents Service level agreement-based workload scheduling (SLA-WS) technique for execution of real-time workload on multi-cloud platform. The SLA-WS emphasizes multi-objective parameter such as processing efficiency with energy optimization and task offloading benefits using soft-computing based dragonfly algorithm (DA). The SLA-WS model reduces processing time and energy consumption for execution of different workload in comparison with existing WS-framework leveraging multi-cloud platform.
引用
收藏
页码：10001 / 10012
页数：11
相关论文
共 150 条
  • [1] Ahmad RW(2015)Survey on virtual machine migration and server consolidation frameworks for cloud data centers J Netw Comput Appl 52 1125-19
  • [2] Gani A(2019)Scheduling algorithms for efficient execution of stream workflow applications in multicloud environments IEEE Trans Serv Comput 28 1-1254
  • [3] Ab Hamid SH(2012)Energy-aware resource allocation heuristics for efcient management of data centers for cloud computing Future Gener Comput Syst 12 419-63003
  • [4] Shiraz M(2020)Self-weighted robust LDA for multiclass classification with edge classes ACM Trans Intell Syst Technol 17 7489-726
  • [5] Yousafzai A(2019)Hybrid cloud adaptive scheduling strategy for heterogeneous workload J Grid Comput 42 1239-6082
  • [6] Xia F(2015)Structure-aware online virtual machine consolidation for datacenter energy improvement in cloud computing Comput Elect Eng 31 62990-6332
  • [7] Barika M(2020)GRP-HEFT: a budget-constrained resource provisioning scheme for workflow scheduling in IaaS clouds IEEE Trans Parallel Distrib Syst 7 13-603
  • [8] Garg S(2019)Energy-aware VM consolidation in cloud data centers using utilization prediction model IEEE Trans Cloud Comput 8 11-200
  • [9] Chan A(2020)CPU and RAM energy-based SLA-aware workload consolidation techniques for clouds IEEE Access 98 713-2533
  • [10] Calheiros R(2016)A survey and taxonomy on energy efcient resource allocation techniques for cloud computing systems Computing 7 6073-2424
12345678910