Evaluating connectivity and quality in Ad-Hoc networks through clustering and trellis algorithms

Recently, wireless networks have become increasingly popular in the computing industry. These networks provide mobile users with ubiquitous computing capability and information access regardless of the location. There are currently two variations of mobile wireless networks- infrastructured (e.g., cellular network) and "infrastructureless" networks, called Mobile Ad-Hoc Networks, where the entire network is mobile, and the individual terminals are allowed to move at will, relative to each other, then they are self-creating, self-organizing, and self-administerig. In order to improve the users service, there exist some measures as connectivity, quality, throughput, and others, to permit evaluate the performance in the network. In this work, we evaluate connectivity and quality using clustering algorithms, DDCA (Distributed Dynamic Clustering Algorithm), and Trellis Method to find k-paths to the different users. Therefore, we simulate an ad-Hoc network, define clusters and parameters as in the DDCA algorithm, and apply concepts about connectivity and quality, depending on parameters defined in the network simulation, such as amount of users and clusters, link availability probabilities, and others