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A new category of intelligent sensor network applications emerges where motion is a fundamental characteristic of the system under consideration. In such applications, sensors are attached to vehicles, or people that move around large geographic areas. For instance, in mission critical applications of wireless sensor networks (WSNs), sinks can be associated to first responders. In such scenarios, reliable data dissemination of events is very important, as well as the efficiency in handling the mobility of both sinks and event sources. For this kind of applications, reliability means real-time data delivery with a high data delivery ratio. In this article, we propose a virtual infrastructure and a data dissemination protocol exploiting this infrastructure, which considers dynamic conditions of multiple sinks and sources. The architecture consists of 'highways' in a honeycomb tessellation, which are the three main diagonals of the honeycomb where the data flow is directed and event data is cached. The highways act as rendezvous regions of the events and queries. Our protocol, namely hexagonal cell-based data dissemination (HexDD), is fault-tolerant, meaning it can bypass routing holes created by imperfect conditions of wireless communication in the network. We analytically evaluate the communication cost and hot region traffic cost of HexDD and compare it with other approaches. Additionally, with extensive simulations, we evaluate the performance of HexDD in terms of data delivery ratio, latency, and energy consumption. We also analyze the hot spot zones of HexDD and other virtual infrastructure based protocols. To overcome the hot region problem in HexDD, we propose to resize the hot regions and evaluate the performance of this method. Simulation results show that our study significantly reduces overall energy consumption while maintaining comparably high data delivery ratio and low latency.

One of the fundamental operations in sensor networks is convergecast which refers to the communication pattern in which data is collected from a set of sensor nodes and forwarded to a common end-point gateway, namely sink node, in the network. In case of multiple sinks within the network, the total load of the network has to be balanced among these sinks to minimize the problem of packet loss in the convergecast process in wireless sensor networks (WSNs) due to congestion and collisions near the sinks. In this paper, we present a novel cross-layered communication protocol for efficient data dissemination in multi-sink WSNs which is under consideration of SENSEI project. It basically combines network wide load balancing, clustering techniques and local routing optimizations with SENSEI architecture which make it efficient on both global and local level. The performance evaluation of the proposed technique shows how our routing protocol can balance the network load without additional control packets for routing tree maintenance.

Wireless sensor networks have the promise of revolutionizing the capture, processing, and communication of mission-critical data for the use of first operational forces. Their low cost, low power, and size make it feasible to embed them into environment monitoring tags in critical care regions, first responders uniform gear, and data collector sinks attached to unmanned aerial vehicles. The ability to actively change the location of sensors can be used to mitigate some of the traditional problems associated with static sensor networks. On the other hand, sensor mobility brings its own challenges. These include challenges associated with in-network aggregation of sensor data, routing, and activity monitoring of responders. Moreover, all different mobility patterns (e.g., sink mobility, sensor mobility) have their special properties, so that each mobile device class needs its own approach. In this article, we present a platform which benefits from both static and mobile sensors and addresses these challenges. The system integrates WSNs, UAVs, and actuators into a disaster response setting, and provides facilities for event detection, autonomous network repair by UAVs, and quick response by integrated operational forces.