Service Level Agreement Aware Workflow Scheduling Dmytro Dyachuk, Ralph Deters Department of Computer Science University of Saskatchewan
[email protected],
[email protected]
Abstract Specifying and monitoring Service Level Agreements (SLA) has been the subject of intensive research. However methods for enforcing SLA have not addressed the specific issues of Composite Web Services. Our work focuses on the problem of ensuring prearranged SLAs for service workflow via SLA Aware Workflow Scheduling (SLAAWS). The novel scheduling algorithm takes into account the workflow structure, utilization of component services and Quality of Service (QoS) obligations defined in SLA.
be used. If however composite services are used different approaches must be used. Within composite services, it is important to ensure that each SLA of an underlying service is not violated or in case of overloads that the penalties for violations are minimized. This paper proposes the scheduling of component service invocations as means for achieving an appropriate QoS for clients contacting the composite service via various SLA.
1. Introduction Service Oriented Architecture is build upon the notion of services that can be aggregated into composite services. Usually this aggregation is achieved by defining a workflow that orchestrates the underlying services in a manner consistent with the desired functionality. Defining service compositions as workflows significantly reduces maintenance and development costs. Within service-oriented systems, it is necessary to establish a contract between consumer and provider that defines the functional and non-functional requirements. The latter should include description of the obligations from a service side in terms of performance, availability, reliability etc. A Service Level Agreement (SLA) represents such a contract. The usage of SLA for SOA resulted in the emergence of the WSLA [1]
2. SLA Aware Workflow Scheduling It a common practice that a (composite) service is offered with various levels of QoS, e.g. gold, silver, etc. For atomic services, scheduling policies like Lottery Scheduling [2] Earliest Deadline First [3] can
Figure 1. SLAAWS The first step of SLA Aware Workflow Scheduling (SLAAWS) [fig. 1] consists in parsing a workflow and transforming it into an acyclic directed graph that describes the workflow component services requests interdependencies. Then the Critical Path Method [4] is used to determine the components that form a Critical Path. The most important property of the Critical Path is that its processing time is equal to the overall composite request processing time. An implication of this property is that delays in processing times of non critical elements will not affect the overall performance. Therefore the non critical requests can be postponed for a certain time meanwhile giving ability for more critical requests to be processed faster.
3. Results A series of experiments were conducted with a Web Service model to investigate the efficiency of SLAAWS compared to the regular EDF scheduling policy. Each service composition is offered with ten different levels of QoS(maximum response time). .
1000000
SLAAW S EDF
800000 600000 400000 200000 0 1
1.625
2.25
2.875
3.5
4.125
4.75
Arrival rate, req/s
Figure 3. SLAAWS vs. EDF (5 services, 2 compositions) Within the experiment the service compositions are gradually exposed to an increasing load. Cumulative Penalty (CuP) represents the sum of all penalties charged for agreements violations is chosen as the main metrics. The high performance of SLAAWS compared to EDF is achieved by means of more rational resources management.[fig. 2,3]. The bigger environment brings better possibilities for optimizations. Thus with the increase of the number of the service and compositions spanning them the performance of SLAAWS in compare to EDF increases as well .
4. Future Work The next step in this research is augmenting SLAAWS by adding automated support of other complex metrics with the semantics described in a machine readable format. Also in the near future we plan to extend SLAAWS by adding a consideration of services dependability.
5. References
800000 700000
EDF
600000
SLAAW S
[1] A. Keller and H. Ludwig, "The WSLA Framework: Specifying and Monitoring Service Level Agreements for Web Services," IBM Research Report, May. 2002.
500000 CuP, $
1200000
CuP, $
Then the QoS parameters estimated by the Critical Path methods are compared to QoS obligation from the contracting Service Level Agreement and the necessary adjustments in component requests scheduling (Latest Start Times) are made, to ensure that the QoS requirements are meet. Depending on the semantics of the QoS constraint (maximum response time, mean response time) the latest start time is translated into a priority. The contract between the clients and the service also can contain certain commercial regulations, e.g. customer is charged a fee for each service invocation, or the service is obligated to pay the client a penalty if the defined QoS obligation is not met. Therefore we also include this type of information in the priority. After the priorities were assigned the component requests are executed. After each completion of component service request the execution times are recorded for the future estimating needs. Besides the current processing schedule is compared to the estimated schedule and if it is necessary it is refined. In this way we ensure that sudden changes in the component service loads resulting in changes of processing times are compensated. By placing proxies in front of component services and adding additional elements to workflow engines a transparent scheduling can be achieved
400000 300000 200000 100000 0 1.7
1.8
1.9
2
2.1
2.2 2.3
2.4
2.5
Arrival Rate, req/s
Figure 2. SLAAWS vs. EDF (3 services, 2 compositions)
[2] S. P. Abdelkarim Erradi and Niranjan Varadharajan, "Differential QoS support in Web Services Management," ICWS, vol. 0, pp. 781-788, 2006. [3] Conway R. W.,Maxwell W.L. and Miller L. W., Theory of Scheduling. Addison-Wesley, 1967. [4] M. Pinedo, Planning and Scheduling in Manufacturing and Services. New York, USA: Springer, 2005.
