Implementing WS-Agreement in a Globus Toolkit 4.0 Environment

2014

SOCA

WS-Agreement is a language and protocol designed for creating Service Level Agreements (SLAs) based on initial offers, and for monitoring those offers at runtime. The definition of WS-Agreement protocol is very general and does not contemplate the possibility of changing an agreement at runtime. This paper presents extensions of the WS-Agreement specification to support the dynamic nature of SLAs by allowing the possibility of SLA renegotiation at run time. The extended WS-Agreement specification have been implemented and tested. Within this implementation, the concept of renegotiation is demonstrated through the ability to create more than one SLA at runtime. An evaluation is conducted to examine the profits a service provider may gain through renegotiation, as well the savings resulting from rescuing the SLA from violations as a consequence of avoiding paying penalties. The results show that making the SLA terms adaptable and changeable is a viable mechanism that provides flexibility to the service provider and service consumer.

Section: Negotiation Managermentioning

confidence: 99%

Enabling service-level agreement renegotiation through extending WS-Agreement specification

Sharaf

2014

SOCA

“…If no quotes are received up to this point, the thread is killed. Provider's can respond either with an SLA quote or an exception if the request is rejected [6].…”

Section: Brokering and Confidencementioning

confidence: 99%

“…Without a means of formally evaluating the probability and expected impact of such negative events, a provider faces serious difficulties and potential risk in deciding upon which SLA requests to accept. Fortunately, other aspects of the research within AssessGrid have focussed considerable effort in addressing the issue of risk assessment [5] and a risk aware WS-Agreement based SLA negotiation service for providers [6].…”

Section: Introductionmentioning

confidence: 99%

Risk-Aware SLA Brokering Using WS-Agreement

Padgett

2009 International Conference on Advanced Information Networking and Applications Workshops

Gourlay

et al. 2009

Service Level Agreements (SLAs) are facilitators for widening the commercial uptake of Grid technology. They provide explicit statements of expectation and obligation between service consumers and providers. However, without the ability to assess the probability that an SLA might fail, commercial uptake will be restricted, since neither party will be willing to agree. Therefore, risk assessment mechanisms are critical to increase confidence in Grid technology usage within the commercial sector. This paper presents an SLA brokering mechanism including risk assessment techniques which evaluate the probability of SLA failure. WS-Agreement and risk metrics are used to facilitate SLA creation between service consumers and providers within a typical Grid resource usage scenario.

“…Interactions between a provider and an end-user (a service consumer or a broker acting on their behalf) can then be governed through a Service Level Agreement (SLA), contractually defining the resource provider's obligations, the price the end-user must pay and the penalty the provider needs to pay in the event that it fails to fulfil its obligations. The use of SLAs to govern such interactions in Grid computing is gaining momentum [4,5,6]. However, such agreements represent a business risk to the parties involved.…”

Section: Introductionmentioning

confidence: 99%

Resource failures risk assessment modelling in distributed environments

Alsoghayer

Journal of Systems and Software

2014

Service providers offer access to resources and services in distributed environments such as Grids and Clouds through formal Service level Agreements (SLA), and need well-balanced infrastructures so that they can maximise the Quality of Service (QoS) they offer and minimise the number of SLA violations. We propose a mathematical model to predict the risk of failure of resources in such environments using a discrete-time analytical model driven by reliability functions fitted to observed data. The model relies on the resource historical data so as to predict the risk of failure for a given time interval. The model is evaluated by comparing the predicted risk of failure with the observed risk of failure, and is shown to accurately predict the resources risk of failure, allowing a service provider to selectively choose which SLA request to accept.