Large scale dense Wireless Sensor Networks (WSNs) will be increasingly deployed in different classes of applications for accurate monitoring. Due to the high density of nodes in these networks, it is likely that redundant data will be detected by nearby nodes when sensing an event. Since energy conservation is a key issue in WSNs, data fusion and aggregation should be exploited in order to save energy. In this case, redundant data can be aggregated at intermediate nodes reducing the size and number of exchanged messages and, thus, decreasing communication costs and energy consumption. In this work, we propose a novel Data Routing for In-Network Aggregation, called DRINA, that has some key aspects such as a reduced number of messages for setting up a routing tree, maximized number of overlapping routes, high aggregation rate, and reliable data aggregation and transmission. The proposed DRINA algorithm was extensively compared to two other known solutions: the Information Fusion-based Role Assignment (InFRA) and Shortest Path Tree (SPT) algorithms. Our results indicate clearly that the routing tree built by DRINA provides the best aggregation quality when compared to these other algorithms. The obtained results show that our proposed solution outperforms these solutions in different scenarios and in different key aspects required by WSNs.

Location is a fundamental service for mobile computing. Typical GPS receivers, although widely available, consume too much energy to be useful for many applications. Observing that in many sensing scenarios, the location information can be post-processed when the data is uploaded to a server, we design a Cloud-Offloaded GPS (CO-GPS) solution that allows a sensing device to aggressively duty-cycle its GPS receiver and log just enough raw GPS signal for post-processing. Leveraging publicly available information such as GNSS satellite ephemeris and an Earth elevation database, a cloud service can derive good quality GPS locations from a few milliseconds of raw data. Using our design of a portable sensing device platform called CLEO, we evaluate the accuracy and efficiency of the solution. Compared to more than 30 seconds of heavy signal processing on standalone GPS receivers, we can achieve three orders of magnitude lower energy consumption per location tagging.

Vehicular Ad Hoc Networks (VANETs) have emerged as an exciting research and application area. The envisioned applications, as well as some inherent VANET characteristics such as highly dynamic topology, frequently disconnected network, and different and dynamic network density, make data dissemination a challenging task in these networks. Several approaches for data dissemination in VANETs have been recently proposed in the literature. However, more work needs to be done since most of the proposed solutions do not effectively address some or all of the main challenges in these scenarios such as the broadcast storm, network partition and temporal network fragmentation. In this work we consider the broadcast storm problem. To tackle this challenge we propose a novel GEographical Data Dissemination for Alert Information (GEDDAI), which eliminates the broadcast storm and maximizes the capability of performing data dissemination across zones of relevance with low overhead, short delays and high coverage. Simulation results show that the data dissemination performed by GEDDAI provides the best efficiency compared with other algorithms, outperforming them for different scenarios in all performed evaluations.

Vehicular ad hoc networks (VANETs) are no longer a futuristic promise but rather an attainable technology. The majority of services envisioned for VANETs either require the provisioning of multimedia support or have this support as an extremely beneficial feature. However, the highly dynamic topology of VANETs poses a demanding challenge for the fulfillment of the stringent requirements for video streaming. In this paper, we provide a deep understanding of the issue of unicast video streaming over VANETs and propose a novel protocol, VIRTUS. In video streaming, many packets are transmitted consecutively in a short period of time. VIRTUS takes this into consideration and extend the duration of the decision of nodes to forward packets from a single transmission to a time window. Furthermore, VIRTUS calculates the suitability of a node to relay packets based on a balance between geographic advancement and link stability. We also propose an extension, that separates the process of relay node selection from the transmission of video content and adopts a density-aware mechanism that adapts its behavior according to local density. Consequently, VIRTUS makes use of the reactive aspect of receiver-based solutions while remaining scalable to increases in transmission rates and density. We report through extensive realistic experiments the benefits of using VIRTUS towards delivering video at a higher quality, in a timely fashion, with lower overhead and fewer collisions.