Optimal service selection in Ad-Hoc mobile market based on multi-dynamic decision algorithms

The ad-hoc mobile markets are increasing daily with providers and consumers ready to participate in these markets. Issues like service discovery and selection are major challenges in these markets. As these markets grow, researchers are working on discovery while little is done on selection. Most scholars have developed different selection mechanisms considering only consumer's quality of service. As members increase and most services are offering the same functionality, one major challenge is when the numbers of producers that meet that requirement are more than one. This is because, in certain operations, time is precious and the selection must be as fast as possible for example, in emergency situation. To tackle this, we propose Multi-Dynamic Decision algorithms as a solution approach. We consider a typical M-Health scenario in our GUISET project. We use the Multi-Criteria Decision (MCD) for selection purpose and the Dynamic Programming to search for the optimal route when there are tie in services. We use hypothetical data to run this experiment by considering 15 sub-locations under the M-health scenario. Our results prove to have a better performance on time based on the shortest route. This research will be useful in a time critical situations like the M-health.