A comprehensive survey for scheduling techniques in cloud computing

被引:188
|
作者
Kumar, Mohit [1 ]
Sharma, S. C. [2 ]
Goel, Anubhav [2 ]
Singh, S. P. [3 ]
机构
[1] SIT Sitamarhi, Paroha, India
[2] IIT Roorkee, Roorkee, Uttar Pradesh, India
[3] Galgotias Univ, Greater Noida, India
关键词
Resource scheduling; Resource provisioning; Virtual machines; Cloud computing; Heuristic; meta-Heuristic; PARTICLE SWARM OPTIMIZATION; LOAD BALANCING ALGORITHM; RESOURCE-ALLOCATION; VIRTUAL MACHINES; GENETIC ALGORITHM; DEADLINE; COST; PERFORMANCE; ENVIRONMENT; WORKLOAD;
D O I
10.1016/j.jnca.2019.06.006
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Resource scheduling becomes the prominent issue in cloud computing due to rapid growth of on demand request and heterogeneous nature of cloud resources. Cloud provides dynamism, uncertainty and elasticity based services to users in pay-as-you-go fashion over the intemet. In recent decade, increase in requests (diverse and complex applications) for cloud services is raising the workload in cloud environment. Inefficient scheduling techniques face the challenges of resources being over utilized and underutilized (imbalanced) which leads to either degradation in service performance (in case of over utilized) or wastage of cloud resources (in case of underutilized). The basic idea behind the scheduling is to distribute tasks (diverse and complex nature) among the cloud resources in such a manner that scheduling algorithm avoids the problem of imbalance. Scheduling algorithm should also optimize the key performance indicator parameters like response time, makespan time, reliability, availability, energy consumption, cost, resource utilization etc. To fulfill the above-mentioned objective, many state of art scheduling algorithms have been proposed based upon heuristic, meta-heuristic and hybrid, reported in the literature. This paper provides the systematic review as well as classification of proposed scheduling techniques along with their advantages and limitations. We hope that our systematic and comprehensive survey work as a stepping stone for new researchers in the field of cloud computing and will be helpful for further development of scheduling technique.
引用
收藏
页码:1 / 33
页数:33
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