1.Abstract: relevant cloud service and it plays multiple

1.Abstract:

 In this project, we proposed reliable agents
authentication based cloud search engine. In our proposed method the agent
client requires service with specific functional and technical requirements.
For privacy concern, we provide authentication for each agent in cloud by using
Elliptic Curve Cryptography (ECC).By using authentication id agents discover
the cloud service based on service engine. Focused Selection Contract Net
Protocol is performed to find the relevant cloud service and it plays multiple
roles in cloud search engine. The similarity between the agent’s request and
cloud service is computed based on service specifications and consumer service
using Cloud ontology. Each legitimate agent provides reliable cloud services
for agent clients (users).Service capability Table records the list of cloud
service and their corresponding ID and services for reliable cloud discovery.

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2.
Introduction:

Cloud
computing is a collection of interconnected virtual machines and it is a
collection of networks and virtual systems.Cloud computing defined by NIST,
such as cloud computing is a paper use model for enabiling available,
convinent, on-demand network access to a shared collection of configurable
computing resources (Examples: Networks, servers, storage, application, service)that
can be rapidly provisioned and release with minimal management effect (or)
service provided intraction. The characteristics of cloud computing are
on-demand service, pay-per-use model, elastic capacity, self-service interface,
resources are abstracted. The roots of cloud computing are Hardware
virtualization, internet technologies, distributed computing, system
management.

 

 

 

Open
virtualization format is providing some standards there are so many hypervisors
where each one supports a different VM image format and the formats are
incompartable withone another and creating interoperability issues in order to
fessillitate packing distribution of software to be run on Vm’s. Several
vendors including Vware, IBM, CISCO, MISROSOFT, Dell, HP have deviced the open
virtualization format(OVF). It aims at begin open, secure, portable, efficient
and extensable.

Service
Capability Table records the service capability of the agents and state of the
agents. The states of the agents are changed dynamically, when it interacted
with other agents. The state of the agent is addressed as available,
unreachable, failed and busy. Each Consumer Agent (CA) maintains the SCT of
Broker Agent (BA). This is due to the request acceptance by broker agent from
consumer agent then the BA subcontracts the service request to other BA. Each
broker agent maintains the SCT of other BA with its state and location and also
maintains the SCT of Service Provider Agent. Service agent provider maintains
two SCTs such as, SCT of other service provider agent and the SCT of resource
agent under its administration.

In
existing method, Cloudle is designed for an agent based search engine for
supporting cloud service discovery. If an agent requested for cloud service to
cloud service provider, the similarity between the agent and service provider
is compute using cloud ontology by using service specification and consumer
service. If the service is not available in the provider leads to loss of
information.In our proposed method, we provide authentication for each agent in
cloud by using Elliptic Curve Cryptography (ECC).By using authentication id
agents discover the cloud service based on service engine. The relevant cloud
service is finding by the multiple role performance of the Focused Selection
Contract Net Protocol (FSCNP). The similarity between the agent’s request and
cloud service is computed based on service specifications and consumer service
using Cloud ontology. Service Capability Table is used for records the cloud
service information such as list of cloud agents, service provided by cloud
agent and their corresponding ID.Each legitimate agent provides reliable cloud
services for agent clients (users).

 

 

 

3.Problem Definition:

In cloud service
discovery, an agent requested for cloud service to cloud service provider, the
similarity between the agent and service provider is compute using cloud
ontology by using service specification and consumer service .If the service is
not available in the provider leads to loss of information. It leads to lack of
security in the cloud service system and take more time for discovering the
cloud service.

4.Methodologies:

4.1.Authentication:

Authentication
of each agent in the cloud service system is performed by Elliptic Curve
Cryptography (ECC).Elliptic Curve Cryptography is based on thealgebraic
structure of elliptic curves over finite fieldand approach to public key
cryptography. ECC requires smaller keys than other
encryption, but provides equivalent security.

4.2.Focused Selection Contract Net
Protocol:

Focused
Selection Contract Net Protocol is performed for satisfying consumer service
requirements by selecting and subcontracting cloud resources. FSCNP performed
service selection by interacting with agents who provide relevant services to
the requirement service by playing multiple roles such as contractor and
manager.

4.3.Service Capability Table:

Service
Capability table in the cloud service system records the service capability of
agents in the cloud system and states of cloud agents such as available,
unreachable, failed and busy. In agent based cloud computing, the states of
agents dynamically change when it is interact with other agents..

4.4. Cloud Ontology:

Cloud
Ontology is a database of cloud services which consist of set of concepts about
services of agents. Cloud ontology mainly used for determining the similarities
between consumer’s service requirements and provider’s service specifications.
Service Discovery Agents consults the cloud ontology and collect the
information about similarity reasoning, compatibility reasoning and numerical
reasoning.

 

 

 

 

 

 

5.Architecture:

Fig.1.cloud service discovery

 

 

 

 

 

 

 

 

6. Algorithm Description:

6.1. Elliptic Curve Cryptography
(ECC):

Authentication
is one of the most important security mechanism used to ensure the security of
the system. In our project, we propose Elliptic Curve Cryptography for
authentication that ensures the reliability, efficiency and resistance to a
large range of attackers. In ECC, the session key is shared between the agent
and the platform to encrypt and decrypt the message. There are three phases in
ECC such as initialization phase, registration phase and authentication and key
agreement phase. In initialization phase, agent chooses two random numbers and
elliptic curve E (FP) over FP. Then agent generate
multiplicative group by bilinear pairing, G1×G1?G2.Next
the agent chooses the hash function and generate random number as a secret key.
In registration phase the ID is submitted with secret key. Then the ID is
verified by agent, if it is valid corresponding timestamp and ephemeral keys
are generated by agent. In last phase the key is authenticated by key agreement
process.

In
our project, service reasoning is determined by cloud ontology. The degree of
similarity between y and z is measure the number of common features between y
and z from the perspective of y as follows,

The
degree of similarity between y and z is measure the number of common features
between y and z from the perspective of z as follows,

Focused
Selection Contract Protocol mainly used to specify the interaction of cloud
agents. The working process of FSCNP is summarized as follows,

Focused
selection
Playing
multiple roles
Integrating
results and dealing with failures
To
provide empirical results.

In
focused selection an agent sends message to only relevant capability agents.
The interaction among the cloud agents in FSCNP is used to reduce the number of
exchanged messages and focuses on interacting with relevant capability agent
only.

Results:

7.Conclusion:

 In cloud
environment, each client needs the cloud service for satisfies their
requirements. In this way, we proposed cloud cloud search
engine with improved
security by using Elliptic Curve Cryptography. In our proposed method, each
agents send cloud service requirements to cloud server. Focused Selection
Contract Net Protocol is used to find the relevant capacity agent for consumer
requirements. Cloud ontology measures the similarity between the consumer’s
requirements and provider’s requirements. Service Capability Table records the
cloud service information. Finally, the cloud service is discovered by agent
client using cloud service engine.

 

 

 

 

 

8. Future Work:

In
future, our proposed method focused on,

Increasing
the Privacy of the cloud service.
Improves
the energy efficiency of cloud service discovery process.

9. References

·        
1 KwangMongSim, Senior Member, IEEE.,
“Agent-Based Cloud Computing” IEEE
Transaction on Services Computing,Vol.5,No.4,October-December2012.

·        
2 K.M. Sim, “Complex and Concurrent
Negotiations for Multiple Interrelated E-Markets,” IEEE Trans. Systems, Man and Cybernetics, Part B, preprint, 2012,
doi:10.1109/TSMCB.2012.2204742.

·        
3J.O. Gutierrez-Garcia and K.M.
Sim,  “Self-Organizing Agents for Service
Composition in Cloud Computing,” Proc.
Second IEEE Int’l Conf. Cloud Computing Technology and Science, 2010.

·        
4K.M. Sim, “Towards Complex
Negotiation for Cloud Economy,” Proc.
Int’l Conf. Advances in Grid and Pervasive Computing (GPC ’10), R.S. Chang et
al., eds., pp. 395-406, 2010.

·        
5K.M. Sim,”Agent-Based Cloud
Commerce,” Proc. IEEE Int’l Conf.
.Industrial Eng. and Eng. Management, pp. 717-721, 2009.

·        
6K.P. Joshi, T. Finin, and Y. Yesha,
“Integrated Lifecycle of IT Services in a Cloud Environment,” Proc. Third Int’l Conf. Virtual Computing
Initiative (ICVCI ’09), pp. 475-478, 2009.

·        
7Foster “Cloud Computing and Grid
Computing 360-Degree Compared,” Proc.
Grid Computing Environments Workshop (GCE ’08), pp. 1-10, Nov. 2008.

·        
 8K.M. Sim, “Evolving Fuzzy Rules for
Relaxed-Criteria Negotiation,” IEEE
Trans. Systems, Man and Cybernetics, Part B, vol. 38,no. 6, pp. 1486-1500,
Dec. 2008.

·        
9K.M. Sim, “G-Commerce, Market-Driven
G-Negotiation Agents and Grid Resource Management,” IEEE Trans. Systems, Man and Cybernetics, Part B, vol. 36, no. 6, pp.
1381-1394, Dec. 2006.

·        
10K.M. Sim, “Equilibria, Prudent
Compromises, and the ‘Waiting’ Game,” IEEE
Trans. System, Man, Cybernetics B, vol. 35, no. 4, pp. 712-724, Aug. 2005.

·       
11K.M. Sim and S.Y. Wang, “Flexible Negotiation
Agent with Relaxed Decision Rules,” IEEE
Trans. Systems, Man and Cybernetics, Part B, vol. 34, no. 3, pp. 1602-1608,
June 2004.

·       
12K.M. Simand C.Y. Choi, “Agents that
React to Changing Market Situations,” IEEE
Trans. System, Man, Cybernetics B, vol. 33, no. 2,pp. 188-201, Apr. 2003.