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QoC-based Optimization of End-to-End M-Health Data Delivery Services

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Abstract—This paper addresses how Quality of Context (QoC) can be used to optimize end-to-end mobile healthcare (m-health) data delivery services in the presence of alternative delivery paths, which is quite common in a pervasive computing and communication environment. We propose min-max-plus based algebraic QoC models for computing the quality of delivered data impeded by the QoS of the resources along the alternative delivery paths. The constructed algebraic structures in those models directly relate to the resource configurations represented as directed graphs. The properties of the applied algebras correspond to the properties of the operations of the addressed QoS dimensions. To rank all the possible resource configurations and therewith select from those the most optimal one(s) we introduce a workflow management metric based on the quality dimensions like freshness and availability. We focus on the pre-establishment phase of m-health data delivery services; dynamic QoC issues existing during service execution are not considered. Index Terms—algebraic computational models, mobile healthcare, QoC, QoS, service composition. I. INTRODUCTIONNTERNET Service Providers (ISPs) do not only bring ubiquitous interconnectivity to (users of) networked applications, but also offer alternative network connections of different (wireless) technologies and qualities. Advancement in pervasive computing further enables discovery and selection of computational nodes and (wireless) connections of required quality. Together, these developments enable services or applications to adapt to the operational contexts to meet the needs or preferences of the users [1]. In the application domain of mobile healthcare (m-health), for example, Electrocardiogram (ECG), oxygen saturation and physical activity signals of a patient enrolled in a rehabilitation care program may be monitored in real-time by a physiotherapist during an indoor or an outdoor exercise of the patient [2], [3]. The supervising physiotherapist may use these This work is part of the Freeband AWARENESS project (http://awareness.freeband.nl). Freeband is sponsored by the Dutch government under contract BSIK 03025. Ing Widya is with the Centre for Telematics and Information Technology, University of Twente, P.O.Box 217, 7500 AE Enschede, the Netherlands (e-mail: [email protected]). Bert-Jan van Beijnum is with the Centre for Telematics and Information Technology, University of Twente, P.O.Box 217, 7500 AE Enschede, the Netherlands (e-mail: [email protected]). Alfons Salden is with the Telematica Instituut, the Netherlands (e-mail: [email protected]). signs, typically together with the patient’s medical history (e.g. health record), as context data to remotely control the exercise by providing advices to increase or decrease the level of intensity of the exercise or to stop the exercise. Rendering the vital signs timely and reliably improves the loop of control of the remotely guided exercise. In a pervasive computing and communication environment, the quality of the context data (QoC) [4] as required by the therapist to control the exercise optimally, depends on the discovered and selected resources used to realize the delivery and the rendering of the data. For example, it depends on the technology of the available (wireless) network links discovered and their quality of services (QoS), cf. [4]. The above m-health example illustrates the need for a robust methodology to select the right configuration of resources amongst alternatives aiming to optimize the provisioning of services in meeting the user’s requirements. The example also indicates the prospect of QoC to improve context data delivery services and, in particular, to adapt the operational behavior of the context using applications. In this paper, we investigate how quality of context can be computed to enable selection of resource configurations for end-to-end m-health context data delivery, such that the delivered QoC meets the quality requirements of the context applying applications or the context-aware services. Accordingly, we also investigate how QoC depends on the QoS of the computational and communication services expected from or realized by the resources along the context data delivery chain. We propose algebraic computational models for several quality dimensions, each of them based on the configuration of the system’s resources (i.e. the processing units and (wireless) communication links) along the end-to-end context data delivery chain. In this way, the applied algebras provide a common computational technique for the concerned quality dimensions. That is, the properties of the applied algebra correspond in an isomorphic sense to the properties of the operations of the addressed quality dimensions. Additionally, we propose a workflow management based method to solve the problem of optimizing the multidimensional metric of computed quality dimensions brought by the independent use of the computational models for the concerned QoC dimensions. To illustrate the computational models we elaborate on the freshness, availability and cost QoC dimensions for a sensor-based m-health data delivery service. Herein we focus on the pre-establishment phase of the end-to-end data delivery QoC-based Optimization of End-to-End M-Health Data Delivery Services Ing Widya, Bert-Jan van Beijnum, Alfons SaldenI1-4244-0476-2/06/$20.00 ©2006 IEEE. 252service; that is, we focus on the set-up of a service. As such, QoC computation during service execution to adapt to changing context quality is beyond our scope. The problem of optimizing chains of resources with specific QoS or quality of device (QoD) measures [4] is a well studied shortest path problem in network routing. An algebra for network routing has been proposed in [5]. The constructed algebra is based on the weights of the edges of the underlying directed graph of routing nodes. It also applies operations of a min-plus algebra, which itself is often used for solving minimum path problems [6], [7]. Max-plus algebras, on the other hand, are also used for synchronization of path routes, such as in (train) transportation networks [7]. Relations between these (dioid) algebras can be found in [8]. Similar to the approach applied in [5], reliability analysis and evaluation techniques have evolved around the concept of constructing a reliability model from the system under consideration, and then formulate, define


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