Given the sensitivity of the potential WSN applications and because of resource limitations, key management emerges as a challenging issue for WSNs. One of the main concerns when designing a key management scheme is the network scalability. Indeed, the protocol should support a large number of nodes to enable a large scale deployment of the network. In this paper, we propose a new highly scalable key management scheme for WSNs which provides a good secure connectivity coverage. For this purpose, we make use for the first time of the unital design theory. We show that the basic mapping from unitals to key pre-distribution allows to achieve an extremely high network scalability. Nonetheless, this naive mapping does not guarantee a high key sharing probability. Therefore, we propose an enhanced unital-based key pre-distribution scheme providing high network scalability and good key sharing probability lower bounded by 1 − e −1 ≈ 0.632. We conduct analytical analysis and simulations to compare our solution to main existing ones regarding different criteria including storage overhead, network scalability, network connectivity, average secure path length and network resiliency. The obtained results show that our approach enhances considerably the network scalability while providing high secure connectivity coverage and good overall performances. Moreover, the obtained results show that at equal network size, our solution reduces significantly the storage overhead compared to main existing solutions.

Air pollution has become a major issue of modern megalopolis because of industrial emissions and increasing urbanization along with traffic jams and heating/cooling of buildings. Monitoring urban air quality is therefore required by municipalities and by the civil society. Current monitoring systems rely on reference sensing stations that are precise but massive, costly and therefore seldom. In this paper, we focus on an alternative or complementary approach, with a network of low cost and autonomic wireless sensors, aiming at a finer spatiotemporal granularity of sensing. Generic deployment models of the literature are not adapted to the stochastic nature of pollution sensing. Our main contribution is to design integer linear programming models that compute sensor deployments capturing both the coverage of pollution under time-varying weather conditions and the connectivity of the infrastructure. We evaluate our deployment models on a real data set of Greater London. We analyze the performance of the proposed models and show that our joint coverage and connectivity formulation is tight and compact, with a reasonable enough execution time. We also conduct extensive simulations to derive engineering insights for effective deployments of air pollution sensors in an urban environment.

In the last decade, we witness a proliferation of potential application domains of wireless sensor networks (WSN). Therefore, a host of research works have been conducted by both academic and industrial communities. Nevertheless, given the sensitivity of the potential applications that are generally tightly related to the physical world and may be human beings, a large scale deployment of WSN depends on the dependability provided by these emerging networks. Particularly, security emerges as a challenging issue in WSN because of the resource limitations. Key management is one of the required building blocks of many security services, such as confidentiality, authentication, etc. Unfortunately, public key based solutions, which provide efficient key management services in conventional networks, are unsuitable for WSN because of resource limitations. Symmetric key establishment is then one of the most suitable paradigms for securing wireless sensor networks. In this paper, we tackle the resiliency of symmetric key pre-distribution schemes against node capture. We propose a hash-based mechanism which enhances the resiliency of key pre-distribution for WSN. Applied to existing key predistribution schemes, our solution gives birth to enhanced schemes which are more resilient against node capture attacks. We analyze and compare our solution against the existing schemes, with respect to some important criteria such as: the network resiliency against node capture, secure connectivity coverage, storage requirement, communication overhead and computation complexity. We show through analytical analysis that our solution enhances the network resiliency without introducing any new storage or communication overheads. Moreover, we show that our solution introduces insignificant computational overhead.

One of the widely used communication patterns in WSN is routing convergecast traffic to one or more sinks. In order to collect data at a sink, most existing systems use a tree rooted at the sink as underlying structure. We consider in this paper the Shortest Path routing Tree problem in WSN under different metrics; we show that the basic approach commonly used in the literature is unsuitable for the many-to-one WSN when considering some metrics. Indeed, existing SPT approaches aim to construct a tree rooted at the sink such that the cost of the path from any node to the sink is minimal, while the cost of a given path is computed as summation of the costs of links that compose this path. However, in many-to-one WSN, links which are close to the sink are more solicited to route packets towards the sink and, hence, they are more critical than other links. Therefore, links in the tree should not have the same weight. We propose in this paper a new weighted path cost function, and we show that our cost function is more suitable for WSN. Based on this cost function, we propose a new efficient shortest path tree construction which does not introduce any new communication overhead compared to basic SPT schemes. We consider, then, the particular case of energy-aware routing in WSN when we apply our new solution in order to construct more suitable energyaware SPT. We conduct extensive simulations which show that our approach allows to enhance the network lifetime up to 20% compared to the basic one.

Recently, air pollution monitoring emerges as a main service of smart cities because of the increasing industrialization and the massive urbanization. Wireless sensor networks (WSN) are a suitable technology for this purpose thanks to their substantial benefits including low cost and autonomy. Minimizing the deployment cost is one of the major challenges in WSN design, therefore sensors positions have to be carefully determined. In this paper, we propose two integer linear programming formulations based on real pollutants dispersion modeling to deal with the minimum cost WSN deployment for air pollution monitoring. We illustrate the concept by applying our models on real world data, namely the Nottingham City street lights. We compare the two models in terms of execution time and show that the second flowbased formulation is much better. We finally conduct extensive simulations to study the impact of some parameters and derive some guidelines for efficient WSN deployment for air pollution monitoring.

Monitoring air quality has become a major challenge of modern cities where the majority of population lives. In this paper, we focus on using wireless sensor networks for air pollution mapping. We tackle the optimization problem of sensor deployment and propose two placement models allowing to minimize the deployment cost and ensure an error-bounded air pollution mapping. Our models take into account the sensing drift of sensor nodes and the impact of weather conditions. Unlike most of existing deployment models, which assume that sensors have a given detection range, we base on interpolation methods to place sensors in such a way that pollution concentration is estimated with a bounded error at locations where no sensor is deployed. We evaluate our model on a dataset of the Lyon City and give insights on how to establish a good compromise between the deployment budget and the precision of air quality monitoring. We also compare our model to generic approaches and show that our formulation is at least 3 times better than random and uniform deployment.

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Given the sensitivity of the potential applications of wireless sensor networks, security emerges as a challenging issue in these networks. Because of the resource limitations, symmetric key establishment is one favorite paradigm for securing WSN. One of the main concerns when designing a key management scheme for WSN is the network scalability. Indeed, the protocol should support a large number of nodes to enable a large scale deployment of the network. In this paper, we propose a new highly scalable key establishment scheme for WSN. For that purpose, we make use, for the first time, of the unital design theory. We show that the basic mapping from unitals to pairwise key establishment allows to achieve an extremely high network scalability while degrading, however, the key sharing probability. We propose then an enhanced unital-based pre-distribution approach which provides high network scalability and good key sharing probability. We conduct analytic calculation and simulations to compare our solutions to existing ones regarding different criteria. The obtained results show that our approach enhances considerably the network scalability while providing good overall performances. We show also that our solutions reduce significantly the storage overhead at equal network size compared to existing solutions.