  As a result of the phenomenal proliferation of modern mobile Internet-enabled
devices and the widespread utilization of wireless and cellular data networks,
mobile users are increasingly requiring services tailored to their current
context. High-level context information is typically obtained from context
services that aggregate raw context information sensed by various sensors and
mobile devices. Given the massive amount of sensed data, traditional context
services are lacking the necessary resources to store and process these data,
as well as to disseminate high-level context information to a variety of
potential context consumers. In this paper, we propose a novel framework for
context information provisioning, which relies on deploying context services on
the cloud and using context brokers to mediate between context consumers and
context services using a publish/subscribe model. Moreover, we describe a
multi-attributes decision algorithm for the selection of potential context
services that can fulfill context consumers' requests for context information.
The algorithm calculates the score of each context service, per context
information type, based on the quality-of-service (QoS) and quality-of-context
information (QoC) requirements expressed by the context consumer. One of the
benefits of the approach is that context providers can scale up and down, in
terms of cloud resources they use, depending on current demand for context
information. Besides, the selection algorithm allows ranking context services
by matching their QoS and QoC offers against the QoS and QoC requirements of
the context consumer.
