Resource allocation strategy for cloud computing environment

The crowd-creation space is a manifestation of the development of innovation theory to a certain stage. With the creation of the crowd-creation space, the problem of optimizing the resource allocation of the crowd-creation space has become a research hotspot. The emergence of cloud computing provides a new idea for solving the problem of resource allocation. Common cloud computing resource allocation algorithms include genetic algorithms, simulated annealing algorithms, and ant colony algorithms. These algorithms have their obvious shortcomings, which are not conducive to solving the problem of optimal resource allocation for crowd-creation space computing. Based on this, this paper proposes an In the cloud computing environment, the algorithm for optimizing resource allocation for crowd-creation space computing adopts a combination of genetic algorithm and ant colony algorithm and optimizes it by citing some mechanisms of simulated annealing algorithm. The algorithm in this paper is an improved genetic ant colony algorithm (HGAACO). In this paper, the feasibility of the algorithm is verified through experiments. The experimental results show that with 20 tasks, the ant colony algorithm task allocation time is 93ms, the genetic ant colony algorithm time is 90ms, and the improved algorithm task allocation time proposed in this paper is 74ms, obviously superior. The algorithm proposed in this paper has a certain reference value for solving the creative space computing optimization resource allocation.

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Energy-Efficient Resource Allocation for Virtual Service in Cloud Computing Environment

Advances in Intelligent Systems and Computing - Information Systems Design and Intelligent Applications ◽

10.1007/978-981-10-7512-4_13 ◽

2018 ◽

pp. 126-136

Author(s):

Nguyen Minh Nhut Pham ◽

Van Son Le ◽

Ha Huy Cuong Nguyen

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Energy Efficient ◽

Computing Environment ◽

Cloud Computing Environment ◽

Efficient Resource ◽

Energy Efficient Resource Allocation

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Resource Allocation Policies in Cloud Computing Environment

Advances in Data Mining and Database Management - Advancing Cloud Database Systems and Capacity Planning With Dynamic Applications ◽

10.4018/978-1-5225-2013-9.ch005 ◽

2017 ◽

pp. 115-132 ◽

Cited By ~ 1

Author(s):

Suvendu Chandan Nayak ◽

Sasmita Parida ◽

Chitaranjan Tripathy ◽

Prasant Kumar Pattnaik

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Resource Utilization ◽

Service Level Agreement ◽

Service Level ◽

Computing Environment ◽

Cloud Computing Environment ◽

On Demand ◽

Different Types ◽

Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

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