A semantic agglomerative traffic management framework for ubiquitous public safety networks

The continuing trend of large scale emergencies in last decades have emphasized on ubiquitous public safety services. The growth of mobile handheld devices have provided people with wide scale flexibility of on demand services and enjoyment of ubiquity. In addition, currently people are not only service consumers but also information providers to realize ubiquitous public safety networks. During and right after an emergency, people seek safety and more likely to explode the underlying mobile ad hoc network with numerous reports on the emergency. These human originated reports may not be syntactically identical so the traditional traffic management schemes are not adequate to handle such explosion. Yet, these reports are either semantically or conceptually similar. Therefore, we propose a semantic agglomerative traffic management framework to efficiently remove the aforementioned semantic information redundancy by employing the Agglomerative Clustering and Latent Semantic Analysis techniques. Simulation results are presented to further establish the worthiness of the proposed framework.