Self-Adaptive and Time-Constrained Data Distribution Paths for Emergency Response Scenarios

Emergency response scenarios where team members coordinate impromptu towards the common human rescue goal are pushing to the extreme the demand for novel services fully aware of any (dynamically collected) relevant information describing the disaster areas, namely context-aware services. Unfortunately, the real-world realization of emergency response context-aware services poses several and still unsolved issues. Timeliness is crucial when dealing with safe critical data, such as medical records of injured people, while efficiency and reliability are necessary to guarantee services provisioning in densely populated and highly mobile disaster areas. This paper proposes an original solution to increase context data distribution scalability and reliability with agreed quality levels, mainly focusing on data retrieval time. The primary design guideline is to execute management operations to monitor and self-adapt the data distribution task by dynamically reorganizing (a limited number of) data distribution paths. The reported experimental simulation results point out that our solution can significantly reduce exchanged messages number and fulfill agreed quality levels