A framework for measurement of end-to-end QoS requirements in loosely coupled systems

Pervasive computing aims at providing computation ubiquitously and a means of realizing anytime, anywhere computing. Pervasive computing is characterized by an infrastructure that enables execution of task (application) that demand automated, continual and multiple unobtrusive services in heterogeneous environments. They use invisible and ubiquitously distributed computational devices. Therefore pervasive computing requires a common single integrated programming solution that would facilitate proactive real-time collaborations among devices, software agents and execution of task. Such systems often termed as loosely coupled systems greatly benefit from service oriented architecture that allows software systems to provide services to end-user applications or other services through published and discoverable interfaces. One of the main issues in loosely coupled systems is the QoS. It is defined as how well a service is satisfied. QoS in such systems is application specific and is multidimensional. We identify two important issues in guaranteeing QoS in such systems: i) The infrastructure should decompose the application specific QoS parameters of multiple tasks (applications) executing in pervasive computing environment into set of QoS parameters and map them to distinct components of task execution, ii) Guaranteeing the QoS parameters with constraints in resource limited pervasive environments. In this paper we propose a framework for guaranteeing QoS by identifying two levels of agreement (service level and resource level) by the middleware entity. This entity identifies the QoS parameters from applications and forms distinct sets applicable to components involved in execution of task. Our aim is develop a generalized architecture that provides a platform for identifying QoS requirements of the applications, mapping these requirements in terms of service level agreements and resource level agreements. Finally , we propose a framework for monitoring and using system level parameters.