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 sublocations 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 Mhealth.
The sudden increase in the number of traffic flow in recent times is a pointer for the network engineers regarding the need for suitable mechanism that would take care of the network QoS demands. Such demands include the smooth running of big data, D2D video exchange, Voice over-IP and real-time multimedia which needed certain QoS requirements for optimal service. However, fewer research articles have reported on this challenges. We propose a multi-criteria routing algorithm that is based on deterministic Adaptive rendering technique called DART_MCP. Our DART_MCP algorithm deployed Dijkstra's algorithm to simplify the topology of the network before using multiple-criteria energy functions. The proposal was tested using a network simulator in comparison with other existing algorithms like, SA_MCP, H_MCOP and HSA_MCP. The experimental results show that our proposed algorithm recorded lower running time, higher success ratio rates and network interference reduction by 42.9%, thus achieving a faster network stability.
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