  Internet of Things (IoT) has seen a prolific rise in recent times and
provides the ability to solve several key challenges faced by our societies and
environment. Data produced by IoT provides a significant opportunity to infer
context that is key for IoT applications to make decisions/actuations. Context
Management Platform (CMP) is a middleware to facilitate the exchange and
management of such context information among IoT applications. In this paper,
we propose a novel approach to monitoring context freshness as a key metric, to
improving the CMP's caching performance to support the real-time context needs
of IoT applications. Our proposed hybrid algorithm uses Analytic Hierarchy
Process (AHP) and Sliding Window technique to ensure the most relevant (as
needed by the IoT applications) context information is cached. By continuously
monitoring and prioritizing context attributes, the strategy adapts to IoT
environment changes, keeping cached context fresh and reliable. Through
experimental evaluation and using mock data obtained from a real-world mobile
IoT scenario in section~\ref{use case}, we demonstrate that the proposed
algorithm can substantially enhance context cache performance, by monitoring
the context attributes in real time.
