Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river’s course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.

Internet access can improve people's life quality by helping them to reduce and overcome the poverty and educational gaps. However, most rural communities in the world, specially in underdeveloped countries, do not have access to the Internet. Delay/Disruption Tolerant Networking (DTN) is a recent low-cost technology now being used to provide connectivity to rural towns were some transportation means periodically arrive. DTNs can be implemented to connect communities to Internet, since this technology takes advantage of the existing people's transportation infrastructure using it to move packets and messages to and from Internet. This paper proposes a DTN mathematical optimization model that maximizes the availability probabilities of the paths from sources to destinations. We also present an opportunistic forwarding algorithm that takes into account the availability probability of a node's neighbors to decide if a node should forward a message or store the message until a node with a higher availability probability contacts it. This algorithm was tested in five different scenarios and in all of them it found a path to the destination.

Abstract:The Mobile Wireless Sensor Networks (MWSN), classified within MANETS, have multiple applications for critical situations management such as target monitoring and tracking in conflict zones, supporting urban security, critical infrastructure monitoring, remote locations exploration (i.e. aerospace exploration), and patients monitoring and care in health facilities, among others. All of these applications have requirements of certain intelligence in the network that can be used for network's self-configuration in order to find targets, guarantee connectivity and information availability until its reception. This paper proposes a MWSN architecture with an initial random distribution in a specific work area, and a centralized management to perform autonomous decision making about the movement and connectivity of the sensors. The work area presents mobile targets with interesting events which must be covered by the mobile sensors, and thus, send the collected information through the network to any base station available. Our work shows a dynamic mathematical model used to maximize targets' coverage and send its sensed information to the base stations available, while minimizing system's power consumption and maximizing operation time. The heuristic algorithm we used to construct and find a feasible solution is also shown.

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