A Survey on Optimizing the QoS during Service Level Agreement in Cloud

Resource Reservation is one of the major aspect in parallel and distributed environment like cloud. While reserving the services in cloud we need to establish Service Level Agreements through negotiation. The negotiation between consumers and cloud Service providers will basically include parameters like price, time and Quality of Service(QoS). There are many existing approaches which solve the problem of price and time slot negotiation mechanism without taking into account the important aspect QoS. In our proposed work this can be solved by the Cloud Monitoring System(CMS) which enhances the QoS. Monitoring can be performed by a global predicate is defined as a conjunction of the local properties of different network elements. In the system if it contains N distributed network elements coordinated by a central monitoring station. Each network element monitors a set of local properties and the central station is responsible for identifying the status of global parameters registered in the system . After detecting the local changes, each network element has to emit alarms in order to ensure that global parameters are not violated. With monitoring, the failed nodes can be noticed and it gradually increases the efficiency of the cloud environment and attract the consumers to consumer the services.

[1]  Luiz Fernando Bittencourt,et al.  HCOC: a cost optimization algorithm for workflow scheduling in hybrid clouds , 2011, Journal of Internet Services and Applications.

[2]  J. Wilkes Utility Functions, Prices, and Negotiation , 2009 .

[3]  Luiz Fernando Bittencourt,et al.  Workflow scheduling for SaaS / PaaS cloud providers considering two SLA levels , 2012, 2012 IEEE Network Operations and Management Symposium.

[4]  Danny Raz,et al.  Efficient reactive monitoring , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[5]  Kwang Mong Sim,et al.  A Price- and-Time-Slot-Negotiation Mechanism for Cloud Service Reservations , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  Yash Patel,et al.  A Novel Stochastic Algorithm for Scheduling QoS-Constrained Workflows in a Web Service-Oriented Grid , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops.

[7]  Byung-Kwen Song,et al.  Dynamic Service Scheduling for Workflow Applications in Service Oriented Grid , 2007 .

[8]  Luqun Li,et al.  An Optimistic Differentiated Service Job Scheduling System for Cloud Computing Service Users and Providers , 2009, 2009 Third International Conference on Multimedia and Ubiquitous Engineering.

[9]  Jean-Marc Petit,et al.  Web Intelligence and Intelligent Agent Technology , 2011 .

[10]  Marios D. Dikaiakos,et al.  Cloud Computing: Distributed Internet Computing for IT and Scientific Research , 2009, IEEE Internet Computing.