An allocation of resources to a virtual machine
specifies the maximum amount of each individual element of
each resource type that will be utilized, as well as the aggregate
amount of each resource of each type. An allocation is thus
represented by two vectors, a maximum elementary allocation
vector and an aggregate allocation vector. There are more
general types of resource allocation problems than those we
consider here. In this paper, we present an approach for
improving the deadlock prevention algorithm, to schedule the
policies of resource supply for resource allocation on
heterogeneous. The deadlock prevention algorithm has a run
time complexity of O (min (m, n)), where m is the number of
resources and n is the number of processes. We propose the
algorithm for allocating multiple resources to competing
services running in virtual machines on a heterogeneous
distributed platform. The experiments also compare the
performance of the proposed approach with other related work.
Ha Huy Cuong Nguyen : received the
M.S degrees in Danang University in
2010. From 2011 until now, he
studied at the center DATIC,
University of Science and Technology
- The University of Da Nang. At the
center of this research, he doctoral
thesis "Studies deadlock prevention
solutions in resource allocation for
distributed virtual systems".
Cloud Computing
Resource Allocation
Heterogeneous Distributed Platforms
Prevention Detection
The proposed virtualization mechanism is used by the
cloud service providers to group the appropriate cloud
service providers and to distribute the cloud services
within the number of the group. In providing a scalable
sharing of resources, a group method for cloud service
providers is supported in the proposed cloud system.
Moreover, the task distribution from the resource
management layer IaaS is improved by performing the
proposed service assignment. In this paper, the service
assign is the main algorithm for the virtualization
mechanism which improves the resource allocation and
task distribution throughout the hardware resource.
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