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

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