Software-Defined Networking paradigm has becoming one of the most studied network concept thanks to its main characteristics: open and programmable. SDN suggests a centralized approach of the network intelligence decoupling the packet forwarding process (Data Plane) from the routing process (Control Plane) in the network devices. Hence the switches only have packet forwarding capability and cannot make any routing decisions, while decision making is done by the controller. OpenFlow is the most popular protocol used to help the switches and the controller to communicate. So, the controller can instruct the forwarding devices through a flow table logic that differs from the traditional destination-based forwarding to a more efficient generalized-based forwarding. This paper want to present an example of software application that runs on the controller and instructs the network to find the shortest path between each node. An implementation of Dijkstra and Bellman-Ford algorithms on a Ryu SDN controller is presented and a comparison between these two approaches is provided.
KEYWORDS: Sensor networks, Sensors, Internet of things, Data communications, Social networks, Environmental sensing, Data acquisition, Unmanned aerial vehicles, Network architectures, Head
Drones can be a candidate technology to support on-demand connectivity in scenarios where networking infrastructure can be difficult to deploy or can be expensive. In a context where many terrestrial nodes such as IoT devices need to send data about environment, drones can move in the considered area to collect data sensed by IoT devices. In this case, Delay Tolerant Network is an architecture that can support the intermittent communication between drones and IoT devices and huge amount of data can be collected and forwarded to remote servers to be analyzed. At this purpose, social paradigm and opportunistic communication between IoT devices and Drones can improve the data collection process. Social rank in the IoT networks is considered as a metric to drive the Drone path planning for providing an efficient connectivity and coverage.
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