Paper Title
Shortest Path Optimization Algorithms in Federated Cloud-Based Wireless Sensor Networks

Shortest path routing is very effective as it saves time and remains economically beneficial in terms of cost. One of the most important characteristics in federated cloud-based wireless sensor networks is the topology dynamics, that is, the network topology changes over time due to energy conservation and node mobility. The cloud server considered asthe final destination node can change over time along with the path towards it. In recent years, the routing problem has been well addressed using intelligent optimization techniques, e.g., Artificial Neural Networks (ANNs), Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), etc. In this paper we compare the effectiveness of these existingalgorithms on various wireless sensor networks and build up a novel hybrid algorithm suitable for federated cloud-based environment. Finally, an implementation using clouds like Pachube, ThingSpeak, and Amazon EC2 constitutes the very future extension of this research work.