عنوان

VM allocation in cloud datacenters based on the multi-agent system :

Number

TLets742760

Title Proper

VM allocation in cloud datacenters based on the multi-agent system :

General Material Designation

[Thesis]

First Statement of Responsibility

Al-ou'n, Ashraf M. S.

Title Proper by Another Author

an investigation into the design and response time analysis of a multi-agent-based virtual machine (VM) allocation/placement policy in cloud datacenters

Name of Publisher, Distributor, etc.

University of Bradford

Date of Publication, Distribution, etc.

2017

Dissertation or thesis details and type of degree

Thesis (Ph.D.)

Text preceding or following the note

2017

Text of Note

Recent years have witnessed a surge in demand for infrastructure and services to cover high demands on processing big chunks of data and applications resulting in a mega Cloud Datacenter. A datacenter is of high complexity with increasing difficulties to identify, allocate efficiently and fast an appropriate host for the requested virtual machine (VM). Establishing a good awareness of all datacenter's resources enables the allocation "placement" policies to make the best decision in reducing the time that is needed to allocate and create the VM(s) at the appropriate host(s). However, current algorithms and policies of placement "allocation" do not focus efficiently on awareness of the resources of the datacenter, and moreover, they are based on conventional static techniques. Which are adversely impacting on the allocation progress of the policies. This thesis proposes a new Agent-based allocation/placement policy that employs some of the Multi-Agent system features to get a good awareness of Cloud Datacenter resources and also provide an efficient allocation decision for the requested VMs. Specifically, (a) The Multi-Agent concept is used as a part of the placement policy (b) A Contract Net Protocol is devised to establish good awareness and (c) A verification process is developed to fully dimensional VM specifications during allocation. These new results show a reduction in response time of VM allocation and the usage improvement of occupied resources. The proposed Agent-based policy was implemented using the CloudSim toolkit and consequently was compared, based on a series of typical numerical experiments, with the toolkit's default policy. The comparative study was carried out in terms of the time duration of VM allocation and other aspects such as the number of available VM types and the amount of occupied resources. Moreover, a two-stage comparative study was introduced through this thesis. Firstly, the proposed policy is compared with four state of the art algorithms, namely the Random algorithm and three one-dimensional Bin-Packing algorithms. Secondly, the three Bin-Packing algorithms were enhanced to have a two-dimensional verification structure and were compared against the proposed new algorithm of the Agent-based policy. Following a rigorous comparative study, it was shown that, through the typical numerical experiments of all stages, the proposed new Agent-based policy had superior performance in terms of the allocation times. Finally, avenues arising from this thesis are included.

Virtual machine (VM) ; Allocation ; Response time ; Agent-based ; Cloud computing ; Virtualisation ; Multi-agent system ; Host ; Physical machine (PM) ; Processing element (PE) ; Data center

Al-ou'n, Ashraf M. S.

University of Bradford

Electronic name

p

[Thesis]

276903

a

Y