Information Technology Reference
In-Depth Information
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Define the Cloud services like Software as a service (SaaS), Platform as a
Service(PaaS) and Infrastructure as a service (IaaS). Also define the architecture
of cloud computing.[2]
In 2010 Zhang Yu Hua, Zhang Jian ,Zhang Wei Hua present argumentation about
the
intelligent cloud computing system and Data warehouse that record the inside and
outside data of Cloud Computing System for data analysis and data mining.
Management problem of CCS are: balance between capacity and demand, capacity
development planning, performance optimization, system safety management.
Architecture of the Intelligence cloud computing system is defined with Data source,
data warehouse and Cloud computing management information system. [3]
In 2008 discussed about the Phoenix by Jianfeng Zhan, Lei Wang, Bipo Tu, Yong
Li, Peng Wang, Wei Zhou and Dan Meng.
In this paper discuss the designed and
implemented cloud management system software Phoenix Cloud. Different
department of large organization often maintain dedicate cluster system for different
computing loads. The department from big organization have operated cluster system
with independent administration staffs and found many problems. So here designed
and implemented cloud management system software Phoenix Cloud to consolidate
high performance computing jobs and Web service application on shared cluster
system. Also imposed cooperative resources provisioning and management policies of
large organization and their departments to share the consolidated cluster systems.
Phoenix Cloud decreases the scale of required cluster system for a large organization,
improve the benefit of scientific computing department, and provisions resources [4].
In 2010 Shu-Ching Wang, Kuo-Qin Yan, Wen-Pin Liao and Shun-Sheng Wang
discussed about Load Balancing in Three-Level Cloud Computing Network. Cloud
computing use low power host to achieve high reliability. In this Cloud computing is
to utilize the computing resources on the network to facilitate the execution of
complicated tasks that require large-scale computation. In this paper use the OLB
scheduling algorithm is used to attempt each node keep busy and goal of load balance.
Proposed LBMM scheduling algorithm can make the minimum execution time of
each task on cloud computing environment and this will improve the load unbalance
of the Min-Min. In order to reach load balance and decrease execution time for each
node in the three-level cloud computing network, the OLB and LBMM scheduling
algorithm are integrated. The agent collects related information of each node
participating in this cloud computing system. In the proposed Method, services
manager that passes the “threshold of services manager” considered effective and will
be the candidate of effective nodes by manager. The Threshold of service node is used
choose the better service node. The load balancing of three-level cloud computing
network is utilized, all calculating result could be integrated first by the second-level
node before sending back to the management[5].
In resource provisioning resource are allocated to applications with service level
agreement (SLA). The Ye Hu, Johnny Wong, Gabriel Iszlai and Marin Litoiu
discussed resource allocation to an application mix is done such that SLA of all
application is met. Here two server strategies namely shared allocation (SA) and
dedicated allocation (DA) are considered for the resource allocation. The allocation
