André L. L. de Aquino

A reactive role assignment for data routing in event-based wireless sensor networks

In this work, we show how we can design a routing protocol for wireless sensor networks (WSNs) to support an information-fusion application. Regarding the application, we consider that WSNs apply information fusion techniques to detect events in the sensor field. Particularly, in event-driven scenarios there might be long intervals of inactivity. However, at a given instant, multiple sensor nodes might detect one or more events, resulting in high traffic. To save energy, the network should be able to remain in a latent state until an event occurs, then the network should organize itself to properly detect and notify the event. Based on the premise that we have an information-fusion application for event detection, we propose a role assignment algorithm, called Information-Fusion-based Role Assignment (InFRA), to organize the network by assigning roles to nodes only when events are detected. The InFRA algorithm is a distributed heuristic to the minimal Steiner tree, and it is suitable for networks with severe resource constraints, such as WSNs. Theoretical analysis shows that, in some cases, our algorithm has a O(1)-approximation ratio. Simulation results show that the InFRA algorithm can use only 70% of the communication resources spent by a reactive version of the Centered-at-Nearest-Source algorithm.

Roadside unit deployment for information dissemination in a VANET: an evolutionary approach

A VANET is a network where each node represents a vehicle equipped with wireless communication technology. This type of network enhances road safety, traffic efficiency, Internet access and many others applications to minimize environmental impact and in general maximize the benefits for the road users. This paper studies a relevant problem in VANETs, known as the deployment of RSUs. A RSU is an access points, used together with the vehicles, to allow information dissemination in the roads. Knowing where to place these RSUs so that a maximum number of vehicles circulating is covered is a challenge. We model the problem as a Maximum Coverage with Time Threshold Problem (MCTTP), and use a genetic algorithm to solve it. The algorithm is tested in four real-world datasets, and compared to a greedy approach previously proposed in the literature. The results show that our approach finds better results than the greedy in all scenarios, with gains up to 11 percentage points.

Deployment of roadside units based on partial mobility information

This work presents an algorithm for deployment of roadside units based on partial mobility information. We propose the partition of the road network into same size urban cells, and we use the migration ratios between adjacent urban cells in order to infer the better locations for the deployment of the roadside units. Our goal is to identify those α locations maximizing the number of distinct vehicles experiencing at least one V2I contact opportunity. We compare our strategy to two deployment algorithms: MCP-g relies on full mobility information (full knowledge of the vehicles trajectories), while MCP-kp does not assume any mobility information at all. Results demonstrate that our strategy increases the number of distinct vehicles contacting the infrastructure in 6.8% when compared to MCP-kp. On the other hand, MCP-g overcomes our strategy by 8.5%. We must evaluate whether the 8.5% improvement worthies tracking the trajectories of vehicles. Complementary, the marginal contribution of adding a new roadside unit becomes much more assertive when employing our strategy, enabling a better evaluation of the return on investments by network designers. Such guarantees are not provided by MCP-kp, and they are too weak in MCP-g.

HyDi: a hybrid data dissemination protocol for highway scenarios in vehicular ad hoc networks

In this paper we tackle the problem of data dissemination under both well-connected and intermittent connected vehicular ad hoc networks. For such a purpose, we propose HyDi, a data dissemination protocol suited for highway scenarios. HyDi can seamless operate under well-connected networks by applying broadcast suppression techniques in order to avoid contention at the link layer, and also at intermittent connected networks by applying store-carry-forward techniques, thus delivering messages even when there is no end-to-end path. By means of simulation using the recently defined IEEE 802.11p standard, we compare HyDi against the only two existing solutions in the literature --- DV-CAST and SRD --- and we show that HyDi has an overhead as good as DV-CAST, outperforms both protocols when considering the average delay under heavy traffic scenarios, decreases the average number of hops to deliver messages and can deliver data to almost all nodes in a given region of interest.

Traffic aware video dissemination over vehicular ad hoc networks

Video dissemination to a group of vehicles is one of the many fundamental services envisioned for Vehicular Ad hoc Networks. For this purpose, in this paper we describe VoV, a video dissemination protocol that operates under extreme traffic conditions. Contrary to most existing approaches that focus exclusively on always-connected networks and tackle the broadcast storm problem inherent to them, VoV is designed to operate under any kind of traffic condition. We propose a new geographic-based broadcast suppression mechanism that gives higher priority to broadcast to vehicles inside especial forwarding zones. Furthermore, vehicles store and carry received messages in a local buffer in order to forward them to vehicles that were not covered by the first dissemination process, probably as a result of collisions or intermittent disconnections. Finally, VoV employs a rate control mechanism that sets the pace at which messages must be transmitted in an attempt to avoid channel overloading and to overcome the synchronization effects introduced by the channel hopping mechanism employed by IEEE 802.11p. When compared to two well-known solutions -- UV-CAST and AID -- we show that our proposal is more efficient in terms of message delivery, delay and overhead.

Data dissemination in urban Vehicular Ad hoc Networks with diverse traffic conditions

Envisioned applications for VANETs will rely extensively on the exchange of broadcast messages to deliver data to vehicles located in a region of interest. Many data dissemination protocols have been proposed in the literature to suppress this need. Surprisingly, most of them were designed to operate exclusively under dense or sparse networks. However, it is reasonable to assume that diverse traffic conditions will coexist in realistic scenarios. Therefore, data dissemination protocols for VANETs should be designed to perceive the traffic condition at hand and adapt accordingly. With this in mind, in this paper we propose HyDiAck, a data dissemination protocol for urban VANETs that relies exclusively on local one-hop neighbor information to deliver messages under dense and sparse networks. In dense scenarios, HyDiAck selects vehicles inside a forwarding zone to rebroadcast messages to further vehicles. Moreover, the protocol employs implicit acknowledgements to guarantee robustness in message delivery under sparse scenarios. When compared to two related protocols - UV-CAST and slotted-1-persistence - simulation results for both Manhattan grid and real city street scenarios show that HyDiAck decreases both the latency to disseminate messages and the network overhead, and also guarantees message delivery to all vehicles in the region of interest.

Evolutionary design of wireless sensor networks based on complex networks

This work proposes a genetic algorithm for designing a wireless sensor network based on complex network theory. We develop an heuristic approach based on genetic algorithms for finding a network configuration such that its communication structure presents complex network characteristics, e.g. a small value for the average shortest path length and high cluster coefficient. The work begins with the mathematical model of the hub location problem, developed to determine the nodes which will be configured as hubs. This model was adopted within the genetic algorithm. The results reveal that our methodology allows the configuration of networks with more than a hundred nodes with complex network characteristics, thus reducing the energy consumption and the data transmission delay.

Multivariate reduction in wireless sensor networks

In wireless sensor networks, energy consumption is generally associated with the amount of sent data once communication is the activity of the network that consumes more energy. This work proposes an algorithm based on “Principal Component Analysis” to perform multivariate data reduction. It is considered air quality monitoring scenario as case study. The results show that, using the proposed technique, we can reduce the data sent preserving its representativeness. Moreover, we show that the energy consumption and delay are reduced proportionally to the amount of reduced data.

Design of roadside infrastructure for information dissemination in vehicular networks

This work presents a probabilistic constructive heuristic to design the roadside infrastructure for information dissemination in vehicular networks. We formulate the problem as a Probabilistic Maximum Coverage Problem (PMCP) and we use them to maximize the number of vehicles in contact with the infrastructure. We compare our approach to a non-probabilistic MCP in simulated urban areas considering Manhattan-style topology with variable traffic conditions. The results reveal that our approach (Probabilistic MCP) increases the number of contacts between vehicles and dissemination points, optimizes the allocation of dissemination points, distributes the dissemination points in a layout that better fits the traffic flow and provides more regularity in the number of contacts experienced by vehicles.

A rate control video dissemination solution for extremely dynamic vehicular ad hoc networks

Video dissemination to a group of vehicles is one of the many fundamental services envisioned for Vehicular Ad hoc Networks, especially as a building block for entertainment applications. For this purpose, in this paper we describe VoV, a video dissemination protocol that operates under extremely dynamic road traffic conditions. Contrary to most existing approaches that focus exclusively on always-connected networks and tackle the broadcast storm problem inherent to them, VoV is designed to operate under any kind of road traffic condition. We propose a new geographic-based broadcast suppression mechanism that gives a higher priority to rebroadcast to vehicles inside especial forwarding zones. Furthermore, vehicles store and carry received messages in a local buffer in order to forward them to vehicles that were not covered by the first dissemination process, probably as a result of collisions or intermittent disconnections. Finally, VoV employs a rate control mechanism that sets the pace at which messages must be transmitted according to the perceived network data traffic, thus avoiding channel overloading. Therefore, VoV adapts not only to the perceived road traffic condition, but also to the perceived channel quality. When compared to two related and well-accepted solutions–ABSM and AID–under Manhattan grid and real city scenarios, we show that, overall, our proposal is more efficient in terms of message delivery, delay and overhead.