Resource Allocation in Cloud Computing Environment using AHP Technique

2014 ◽  
Vol 4 (1) ◽  
pp. 33-44 ◽  
Author(s):  
Anil Singh ◽  
Kamlesh Dutta ◽  
Avtar Singh
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Synthesis Methods ◽  
Computing Environment ◽  
Computing Technology ◽  
Method Error ◽  
Cloud Computing Environment ◽  
Mps Method ◽  
On Demand ◽  
Hierarchy Process

Cloud Computing has changed the strategy of the way of providing different services to business and government agent as well as to sole users. Cloud Computing provides scalable and on demand services to users irrespective of their physical area. But this computing technology has many challenges. One of them is on demand resource allocation. In this paper a resource allocation method is proposed based on Analytical Hierarchy Process (AHP) called Multicriteria Preference Synthesis (MPS) method. MPS method combines many AHP synthesis methods (Additive Normalization, EigenVector, Multicriteria Synthesis etc.) to assign the priorities to the users' tasks. In MPS method Error Criteria is used to provide the consistency in providing the priorities to users' tasks if any violation is there.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
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.

scholarly journals Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment

2021 ◽  
pp. 08-25
Author(s):  
Mustafa El .. ◽  
◽  
◽  
Aaras Y Y.Kraidi
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Simulated Annealing ◽  
Task Allocation ◽  
Ant Colony Algorithm ◽  
Simulated Annealing Algorithm ◽  
Ant Colony ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Resource Allocation Algorithm

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.

Analysis of Various Security Issues and Challenges in Cloud Computing Environment

2016 ◽  
pp. 221-247 ◽  
Author(s):  
Zhaolong Gou ◽  
Shingo Yamaguchi ◽  
B. B. Gupta
Keyword(s):  
Cloud Computing ◽  
Comparative Analysis ◽  
Solution Space ◽  
Future Research ◽  
Security Threats ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Security Issues ◽  
On Demand ◽  
Recent Developments

Cloud computing is a system, where the resources of a data center are shared using virtualization technology, such that it provides elastic, on demand and instant services to its customers and charges them based on the resources they use. In this chapter, we will discuss recent developments in cloud computing, various security issues and challenges associated with Cloud computing environment, various existing solutions provided for dealing with these security threats and will provide a comparative analysis these approaches. This will provide better understanding of the various security problems associated with the cloud, current solution space, and future research scope to deal with such attacks in better way.

Virtual Machine Placement Using Statistical Mechanism in Cloud Computing Environment

2018 ◽  
Vol 9 (3) ◽  
pp. 23-31
Author(s):  
Narander Kumar ◽  
Surendra Kumar
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Minimum Cost ◽  
Virtual Machine Placement ◽  
The Internet ◽  
Computing Environment ◽  
Assignment Problems ◽  
Cloud Computing Environment ◽  
Statistical Mechanism

The internet has become essential and is the basis of cloud computing and will continue to be in the future. Best resource allocation is a process of placing the resources at their minimum cost/time and minimizes the load to a virtual machine. In this article, the authors propose an algorithm to optimize assignment problems and get the best placements in the resources to maintain the load on the virtual machine. Further, they also make comparisons between various optimization mechanisms for assignment problems, which is formulated for the cloud in virtual machine placement.

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