Abstract
With rapid
technological advancements, cloud marketplace witnessed frequent emergence of
new service providers with similar offerings. However, service level agreements
(SLAs), which document guaranteed quality of service levels, have not been
found to be consistent among providers, even though they offer services with
similar functionality. In service outsourcing environments, like cloud, the
quality of service levels are of prime importance to customers, as they use
third-party cloud services to store and process their clients’ data. If loss of
data occurs due to an outage, the customer’s business gets affected. Therefore,
the major challenge for a customer is to select an appropriate service provider
to ensure guaranteed service quality. To support customers in reliably
identifying ideal service provider, this work proposes a framework, SelCSP,
which combines trustworthiness and competence to estimate risk of interaction.
Trustworthiness is computed from personal experiences gained through direct
interactions or from feedbacks related to reputations of vendors. Competence is
assessed based on transparency in provider’s SLA guarantees. A case study has
been presented to demonstrate the application of our approach. Experimental
results validate the practicability of the proposed estimating mechanisms
Aim
The aim of this
paper proposes a framework, SelCSP, which combines trustworthiness and
competence to estimate risk of interaction.
Scope:
The scope of this paper tends to validate
the practicability of the proposed estimating the risk of interaction.
Existing
System
In most cases, it has been observed that
the failover time is quite long and customers’ businesses were hugely affected
owing to lack of recovery strategy on vendor side. Moreover, in some instances,
customers were not even intimated about the outage by providers. Cloud
providers may use the high-quality first replication (HQFR) strategy proposed
in to model their recovery mechanism. In this work, authors propose algorithms
to minimize replication cost and the number of QoS-violated data replicas.
Hence, it is desirable from customer’s point of- view to avoid such loss,
rather than getting guarantees of service credits following a cloud outage.
Avoidance of data loss requires reliable identification of competent service
provider. As customer does not have control over its data deployed in cloud,
there is a need to estimate risk prior to outsourcing any business onto a
cloud. This motivated us to propose a risk estimation scheme which makes a
quantitative assessment of risk involved while interacting with a given service
provider.
Disadvantages
- Lack of assurances and violations for SLA guarantees
- Multi-tenancy, lack of customer’s control over their data and application
- Non-transparency with respect to security profiles of remote datacenter locations
Proposed
System
In this paper estimation
of risk of interaction in cloud environment has not been addressed. Hence, in
this respect, the current work is significant as it proposes a framework,
SelCSP , which attempts to compute risk involved in interacting with a given
cloud service provider. The framework estimates perceived level of interaction
risk by combining trustworthiness and competence of cloud provider. Trustworthiness
is computed from ratings obtained through either direct interaction or
feedback.
Advantages
- The framework estimates trustworthiness in terms of context-specific, dynamic trust and reputation feedbacks.
- Both these entities are combined to model interaction risk, which gives an estimate of risk level involved in an interaction
System
Architecture
System
Configuration
Hardware Requirements
- Speed - 1.1 Ghz
- Processor - Pentium IV
- RAM - 512 MB (min)
- Hard Disk - 40 GB
- Key Board - Standard Windows Keyboard
- Mouse - Two or Three Button Mouse
- Monitor - LCD/LED
Software
requirements
- Operating System : Windows 7
- Front End : ASP.Net and C#
- Database : MSSQL
- Tool : Microsoft Visual studio
References
Ghosh, N.,Ghosh, S.K., Das, S.K. “SelCSP: A Framework to Facilitate
Selection of Cloud Service Providers” IEEE Transactions on Cloud Computing,
Volume 3 , Issue 1 JULY 2014.
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