Transparent Scheduling of Composite Web Services

Composite Web Services (CWS) aggregate multiple Web Services in one logical unit to accomplish a complex task (e.g. business process). This aggregation is achieved by defining a workflow that orchestrates the underlying Web Services in a manner consistent with the desired functionality. Since CWS can aggregate atomic and other CWS they foster the development of service layers and reuse of already existing functionality. An important issue in the deployment of services is their run-time performance under various loads. Due to the complex interactions of the underlying services, a CWS they can exhibit problematic and often difficult to predict behaviours in overload situations. This paper focuses on the use of request scheduling for improving CWS performance in overload situations. Different scheduling policies are investigated in regards to their effectiveness in helping with bulk arrivals

The Runtime Behavior of Composite SOAP Web Services under Transient Loads

Services are computational elements that expose functionality in a platform independent manner. They are the basic building blocks of the service-oriented (SO) design/integration paradigm. Composite Web Services (CWS) aggregate multiple Web Services (WSs), which is typically achieved by use of a workflow language. A workflow coordinates services in a manner that is consistent with the desired overall functionality (e.g. business process). When the atomic and composite services are exposed to various users, the performance and runtime behavior of WSs becomes important. To ensure wide deployment of CWS, the performance issues must be studied. This research focuses on the performance of atomic and composite SOAP (Simple Object Access Protocol) WSs under transient overloads. This research includes conducting experiments with WSs, studying the runtime behavior, and building simulation models of WSs workflow patterns. Simulation models of different WSs workflow patterns are built to study different situations. Timeout and network latency are added to the model to better simulate real systems. The simulation models are used to predict the runtime behavior of WSs and CWS, as well as to improve the performance with existing, limited resources

Ensuring Service Level Agreements for Composite Services by Means of Request Scheduling

Building distributed systems according to the Service-Oriented Architecture (SOA) allows simplifying the integration process, reducing development costs and increasing scalability, interoperability and openness. SOA endorses the reusability of existing services and aggregating them into new service layers for future recycling. At the same time, the complexity of large service-oriented systems negatively reflects on their behavior in terms of the exhibited Quality of Service. To address this problem this thesis focuses on using request scheduling for meeting Service Level Agreements (SLAs). The special focus is given to composite services specified by means of workflow languages. The proposed solution suggests using two level scheduling: global and local. The global policies assign the response time requirements for component service invocations. The local scheduling policies are responsible for performing request scheduling in order to meet these requirements. The proposed scheduling approach can be deployed without altering the code of the scheduled services, does not require a central point of control and is platform independent. The experiments, conducted using a simulation, were used to study the effectiveness and the feasibility of the proposed scheduling schemes in respect to various deployment requirements. The validity of the simulation was confirmed by comparing its results to the results obtained in experiments with a real-world service. The proposed approach was shown to work well under different traffic conditions and with different types of SLAs

Towards achieving execution time predictability in web services middleware

Web services middleware are typically designed optimised for throughput. Requests are accepted unconditionally and no differentiation is made in processing. Many use the thread-pool pattern to execute requests in parallel using processor sharing. Clusters hosting web services dispatch requests only to balance out the load among the executors. Such optimisations for throughput work out negatively on the predictability of execution. Processor sharing results in the increase of execution time with the number of concurrent requests, making it impossible to predict or control the execution of a request. Existing works fail to address the need for predictability in web service execution. Some achieve a level of differentiated processing, but fail to consider predictability as their main quality attribute. Some give a probabilistic guarantee on service levels. However, from a predictability perspective they are inconsistent. A few achieve predictable execution times, though only in closed systems where request properties are known at system design time. Web services operate on the Internet, where request properties are relatively unknown. This thesis investigates the problem of achieving predictable times in web service executions. We introduce the notion of a processing deadline for service execution, which the web services engine must adhere to in completing the request in a repeatable and a consistent manner. Reaching such execution deadlines by the services engine is made possible by three main features. Firstly a deadline based scheduling algorithm introduced, ensures the processing deadlines are followed. A laxity based analytical model and an admission control algorithm it is based on, selects requests for execution, resulting in a wider range of laxities to enable more requests with overlapping executions to be scheduled together. Finally, a real-time scheduler component introduced in to the server uses a priority model to schedule the execution of requests by controlling the execution of individual worker threads in custom-made thread pools. Predictability of execution in cluster based deployments is further facilitated by four dispatching algorithms that consider the request deadlines and laxity property in the dispatching process. A performance model derived for a similar system approximates the waiting time where requests with smaller deadlines (having higher priority) experience smaller waiting times than requests with longer deadlines. These techniques are implemented in web services middleware in standalone and cluster-based configurations. They are evaluated against their unmodified versions and techniques such as round-robin and class based dispatching, to measure their predictability gain. Empirical evidence indicate the enhancements enable the middleware to achieve more than 90% of the deadlines, while accepting at least 20% of the requests in high traffic conditions. The enhancements additionally prevent the middleware from reaching overloaded conditions in heavy traffic, while maintaining comparable throughput rates to the unmodified versions of the middleware. Analytical and simulation results for the performance model confirms that deadline based preemptive scheduling results in a better balance of waiting times where high priority requests experience lower waiting times while lower priority requests are not over-starved compared to other techniques such as static priority ordering, First-Come-First-Served, Round-Robin and non-preemptive deadline based scheduling