Section: New Results
Technology specific solutions
Participants: I. Augé-Blum, W. Bechkit, J. Cui, A. Mouradian, T. Lin, H. Rivano, R. Stanica, F. Valois
Medium Access Control in Wireless Sensor Networks
Protocols developed during the last years for Wireless Sensor Networks (WSNs) are mainly focused on energy efficiency and autonomous mechanisms (e.g. self-organization, self-configuration, etc.). Nevertheless, with new WSN applications, new QoS requirements appear, such as time constraints. Real-time applications require the packets to be delivered before a known time bound which depends on the application requirements. We particularly focus on applications which consist in alarms sent to the sink node. We propose Real-Time X-layer Protocol (RTXP)  , a real-time communication protocol. RTXP is a MAC and routing real-time communication protocol that is not centralized, but instead relies only on local information. To the best of our knowledge, it is the first real-time protocol for WSNs using an opportunistic routing scheme in order to increase the packet delivery ratio. In the paper above, we describe the protocol mechanisms. We give theoretical bounds on the end-to-end delay and the capacity of the protocol. Intensive simulation results confirm the theoretical predictions and allow to compare RTXP with a real-time scheduled solution. RTXP is also simulated under harsh radio channel, in which case the radio link introduces probabilistic behavior. Nevertheless, we show that RTXP performs better than a non-deterministic solution. It thus advocates for the usefulness of designing real-time (deterministic) protocols even for highly unreliable networks such as WSNs.
Continuing on the idea of WSN applications with strict temporal constraints, these critical applications require correct behavior, reliability, and, of course, the respect of time constraints. Otherwise, if they fail, consequences on human life and the environment could be catastrophic. For this reason, we argue that the WSN protocols used in these applications must be formally verified. Unfortunately the radio link is unreliable, it is thus difficult to give hard guarantees on the temporal behavior of the protocols (on wired systems the link error probability is very low, so they are considered reliable). Indeed, in WSN a message may experience a very high number of retransmissions. The temporal guarantee has thus to be given with a probability that it is achieved. This probability must meet the requirements of the application. Network protocols have been successfully verified on a given network topology without taking into account unreliable links. Nevertheless, the probabilistic nature of radio links may change the topology (links which appear and disappear). Thus, instead of a single topology we have a set of possible topologies, each topology having a probability to exist. In this paper, we propose a method that produces the set of topologies, checks the property on every topology, and gives the probability that the property is verified. This technique is independent from the verification technique, i.e. each topology can be verified using any formal method which can give a “yes” or “no” answer to the question: “Does the model of the protocol respect the property?”. In  , we apply this method on the previously proposed f-MAC protocol, a real-time medium access protocol for WSNs. We use UPPAAL model checker as verification tool, and we perform simulations to observe the difference between average and worst case behaviors.
One WSN application gaining a lot of importance in the team in the last few years targets Intelligent Transportation Systems (ITS), as also explained in the previous section. In this ITS field, parking sensor networks are rapidly deploying around the world and are also regarded as one of the first implemented urban services in smart cities. To provide the best network performance in this context, the MAC protocol shall be adaptive enough in order to satisfy the traffic intensity and variation of parking sensors. In this sense, in  and  , we compare the performance of two off-the-shelf medium access control protocols on two different kinds of traffic models, and then evaluate their application-end information delay and energy consumption while varying traffic parameters and network density. From the simulation results, we highlight some limits induced by network density and occurrence frequency of event-driven applications. When it comes to real-time urban services, a protocol selection shall be taken into account - even dynamically - with a special attention to the energy-delay trade-off. In a follow-up study  , we use real world data, more precisely the heavy-tailed parking and vacant time models from the SmartSantander platform, and then we apply the traffic model in the simulation with four different kinds of MAC protocols, that is, contention-based, schedule-based and two hybrid versions of these. The result shows that the packet inter-arrival time is no longer heavy-tailed while collecting a group of parking sensors, and then choosing an appropriate MAC protocol highly depends on the network configuration. Also, the information delay is bounded by traffic and MAC parameters which are important criteria while the timely message is required.
Routing in Wireless Sensor Networks
Routing represents another major challenging issue in WSN, because of the application diversity and energy efficiency constraints. Gradient broadcast routing is a robust scheme for data gathering in WSNs. At each hop, the sender broadcasts the packet to its neighbors and one or more nodes among its neighbors closer to the sink forward it. As long as a node has at least one neighbor with a smaller hop-count, it can route packets. Nevertheless, nodes can disappear because of energy depletion, hardware failure, etc. In this case, it cannot be ensured that a packet reaches the sink. Usually this issue is addressed by updating the gradient with a periodical flooding. Nevertheless, it consumes an important amount of energy, moreover, parts of the network may not need to be updated. In  , we propose GRABUP (GRAdient Broadcast UPdate), a traffic-based gradient maintenance algorithm which updates the gradient thanks to the data packets. We simulate the proposition and compare it with the classic gradient broadcast routing.
Another specific application that we target is smart metering, which heavily rely on the communication network for efficient data gathering, thus eliminating manual meter reading. Smart electronic devices are deployed in open, unattended and possibly hostile environment such as consumer's home and office areas, making them particularly vulnerable to physical attacks. Resilience is needed in this case to mitigate such inherent vulnerabilities and risks related to security and reliability. In  , a general overview of the resilience including definition, metric and resilient techniques relevant for smart metering is presented. A quantitative metric, visual and meaningful, based on the graphical representation is adopted to compare routing protocols in the sense of resilience against active insider attacks. Five well-known routing protocols from the main categories have been studied through simulations and their resilience is evaluated according to the given metric. Resilient techniques introduced to these protocols have enhanced significantly the resilience against attacks providing route diversification.
Other Research Issues Related to Wireless Sensor Networks
Important features of WSNs, such as low battery consumption, changing topology awareness, open environment, non reliable radio links, raise other research issues than classical MAC and routing problems. For example, in  , we investigate the benefits of Network Coding in WSN, especially with respect to resiliency. We have seen in our previous work that resiliency could be described as a multi dimensional metric, taking parameters such as Average Delivery Ratio, Delay Efficiency, Energy Efficiency, Average Throughput and Delivery Fairness into account. Resiliency can then be graphically represented as a kiviat diagram created by the previous weighted parameters. In order to introduce these metrics, previous works have been leaded on the Random Gradient Based Routing, which proved good resiliency in malicious environment. We look for seeing the improvements in term of resiliency, when adding network coding in the Random Gradient Based Routing with malicious nodes.
Another challenge is represented by the deployment of sensor nodes, which can take into account the impact of multiple parameters. For example, temperature variations have a significant effect on low power WSNs as wireless communication links drastically deteriorate when temperature increases. A reliable deployment should take temperature into account to avoid network connectivity problems resulting from poor wireless links when temperature increases. A good deployment needs also to adapt its operation and save resources when temperature decreases and wireless links improve. Taking into account the probabilistic nature of the wireless communication channel, we develop  a mathematical model that provides the most energy efficient deployment in function of temperature without compromising the correct operation of the network by preserving both connectivity and coverage. We use our model to design three temperature-aware algorithms that seek to save energy (i) by putting some nodes in hibernate mode as in the SO (Stop-Operate) algorithm, or (ii) by using transmission power control as in PC (Power-Control), or (iii) by doing both techniques as in SOPC (Stop-Operate Power-Control). All proposed algorithms are fully distributed and solely rely on temperature readings without any information exchange between neighbors, which makes them low overhead and robust. Our results identify the optimal operation of each algorithm and show that a significant amount of energy can be saved by taking temperature into account.
Finally, the notion of Shared Risk Link Groups (SRLG) captures survivability issues when a set of links of a network may fail simultaneously, such as a WSN where link conditions are extremely dynamic. The theory of survivable network design relies on basic combinatorial objects that are rather easy to compute in the classical graph models: shortest paths, minimum cuts, or pairs of disjoint paths. In the SRLG context, the optimization criterion for these objects is no longer the number of edges they use, but the number of SRLGs involved. Unfortunately, computing these combinatorial objects is NP-hard and hard to approximate with this objective in general. Nevertheless some objects can be computed in polynomial time when the SRLGs satisfy certain structural properties of locality which correspond to practical ones, namely the star property (all links affected by a given SRLG are incident to a unique node, for example a battery depleted sensor) and the span property (the links affected by a given SRLG form a connected component of the network). The star property is defined in a multi-colored model where a link can be affected by several SRLGs while the span property is defined only in a mono-colored model where a link can be affected by at most one SRLG. In  , we extend these notions to characterize new cases in which these optimization problems can be solved in polynomial time or are fixed parameter tractable. We also investigate on the computational impact of the transformation from the multi-colored model to the mono-colored one. Experimental results are presented to validate the proposed algorithms and principles.
Data Aggregation and Gathering
In the data gathering problem, a particular network node, the base station or the sink, aims at receiving messages from some other network nodes. In  , we model this network as a graph, and we consider that, at each step, a node can send one message to one of its neighbors (such an action is called a call). However, a node cannot send and receive a message during the same step. Moreover, the communication is subject to interference constraints, more precisely, two calls interfere in a step, if one sender is at distance below a certain threshold from the other receiver. Given a graph with a base station and a set of nodes having some messages, the goal of the gathering problem is to compute a schedule of calls for the base station to receive all messages as fast as possible, i.e., minimizing the number of steps (called makespan). The gathering problem is equivalent in this case to the personalized broadcasting problem where the base station has to send messages to some nodes in the graph, with same transmission constraints. We focus on the gathering and personalized broadcasting problem in grids (regular networks, with nodes deployed in a grid-like shape, e.g. parking or intersection monitoring WSNs). Moreover, we consider the non-buffering model: when a node receives a message at some step, it must transmit it during the next step. In this setting, though the problem of determining the complexity of computing the optimal makespan in a grid is still open, we present linear (in the number of messages) algorithms that compute optimal schedules for data gathering.
Data aggregation is a particular solution for the data gathering problem, which reduces the amount of data sent to the base station. In  , we show that data aggregation can effectively reduce the energy consumption and improve the network capacity. Moreover, we present the state-of-the-art aggregation functions, including compressing-based and forecasting-based method; compressing-based aggregation focuses on compressing the data packets accompanied with transmitting based on spatial correlation, while forecasting aggregation tends to use mathematical models to fit the time series and predict the new value due to highly temporal correlation. We detail these two methods and characterize them respectively. We propose comparison between A-ARMA and Compressing Sensing, which are noteworthy examples of forecasting aggregation and compressing aggregation respectively.
Safety Vehicular Ad Hoc Networks
Vehicular ad hoc networks can play an important role in enhancing transportation efficiency and improving road safety. Therefore, direct vehicle-to-vehicle communications are considered as one of the main building blocks of a future Intelligent Transportation System. The success and availability of IEEE 802.11 radios made this technology the most probable choice for the medium access control layer in vehicular networks. However, IEEE 802.11 was originally designed in a wireless local area network context and it is not optimized for a dynamic, ad hoc vehicular scenario. In  , we investigate the compatibility of the IEEE 802.11 medium access control protocol with the requirements of safety vehicular applications. As the protocols in this family are well-known for their scalability problems, we are especially interested in high density scenarios, quite frequent on today’s roads. Using an analytical framework, we study the performance of the back-off mechanism and the role of the contention window on the control channel of a vehicular network. Based on these findings, we propose a reverse back-off mechanism, specifically designed with road safety applications in mind. Extensive simulations are carried out to prove the efficiency of the proposed enhancement scheme and to better understand the characteristics of vehicular communications.
One of the major roles of vehicular communication is the dissemination of information on the road in order to increase the awareness of the drivers. The facilities layer is a recently standardized component in the vehicular communication architecture, with an important role to play in the process of information dissemination. In  , we propose facilities layer-based mechanisms for information propagation and we show they outperform classical network layer solutions. We also demonstrate that previous studies that do not consider the cohabitation of different types of safety messages on the vehicular control channel highly under-estimate the dissemination delay, which can lead to unrealistic assumptions in the design of safety applications.