Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations


CSCC (2012) The CSCC Practical Guide to Cloud Service Level Agreements v1.0. Cloud Standards Customer Council.

has been cited by the following article:

  • TITLE: An Automated Semantic Negotiation for Cloud Service Level Agreements

    AUTHORS: Dr. K. Saravanan, Dr. S. Silas Sargunam, Dr. M. Rajaram

    KEYWORDS: Service Level Agreements, Semantic Web, SLA Life Cycle, Negotiation

    JOURNAL NAME: Circuits and Systems, Vol.7 No.9, July 20, 2016

    ABSTRACT: Mostly, cloud agreements are signed between the consumer and the provider using online click-through agreements. Several issues and conflicts exist in the negotiation of cloud agreement terms due to the legal and ambiguous terms in Service Level Agreements (SLA). Semantic knowledge applied during the formation and negotiation of SLA can overcome these issues. Cloud SLA negotiation consists of numerous activities such as formation of SLA templates, publishing it in registry, verification and validation of SLA, monitoring for violation, logging and reporting and termination. Though these activities are interleaved with each other, semantic synchronization is still lacking. To overcome this, a novel SLA life cycle using semantic knowledge to automate the cloud negotiation has been formulated. Semantic web platform using ontologies is designed, developed and evaluated. The resultant platform increases the task efficiency of the consumer and the provider during negotiation. Precision and recall scores for Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) SLAs were calculated. And it reveals that applying semantic knowledge helps the extraction of meaningful answers from the cloud actors.