Evaluation of an Approach for Distributed Cooperative Reasoning of Global Context States

In many occasions of our daily lives, we are willing to spontaneously interact or collaborate with nearby people for sharing ideas, chatting, saving time/money, or helping each other. For that purpose, it is often necessary to identify and reason about shared context situations that are based on distributed sources of local contexts. So far, most of the work that investigates mechanisms to support spontaneous discovery and interaction among mobile users has not thoroughly explored means of automatic detection of common Global Context States (GCS). In this paper, we discuss a distributed reasoning approach and algorithm that determines a distributed Global Context State among potentially interacting agents. We also evaluate the complexity of the algorithm - through simulation - and identify how the convergence of the algorithm is influenced by users' mobility patterns, the requested minimum number of contributing agents required to conclude a reasoning process and the volatility of each agent's local context.