The research paper titled "Exploiting Location and Contextual Information to Develop a Comprehensive Framework for Proactive Handover in Heterogeneous Environments" presents a comprehensive framework that leverages location and contextual information to facilitate proactive handover in heterogeneous environments.

The paper begins by acknowledging the increasing demand for seamless connectivity and high$-$quality service in wireless networks. This demand necessitates the development of efficient handover strategies that can maintain service continuity and quality.

The authors propose a framework that uses location and contextual information to predict the need for handover and initiate the process proactively. The framework is designed to work in heterogeneous environments, which means it can handle different types of networks and technologies.

The proposed framework consists of three main components: the location prediction module, the context$-$aware decision$-$making module, and the handover execution module. The location prediction module uses historical data and current location information to predict the future location of a user. The context$-$aware decision$-$making module uses this predicted location and other contextual information $($like network conditions, user preferences, etc.$)$ to decide whether a handover is necessary and which network to handover to$.$ The handover execution module then carries out the handover process.

The authors also present a mathematical model to evaluate the performance of the proposed framework. They use parameters like handover latency, service disruption time, and handover success rate to measure the performance.

The paper concludes by stating that the proposed framework can significantly improve the handover performance in heterogeneous environments. It can reduce service disruptions, ensure service continuity, and enhance the overall user experience. However, the authors also acknowledge that further research is needed to refine the framework and make it more efficient.