Section: New Results

Wireless network deployment

Participants: Walid Bechkit, Ahmed Boubrima, Oana Iova, Rodrigue D. Komguem, Abdoul-Aziz Mbacke, Jad Oueis, Hervé Rivano, Razvan Stanica, Fabrice Valois

Deployment of wireless sensor networks for air quality mapping

Wireless sensor networks (WSN) are widely used in environmental applications where the aim is to sense a physical phenomenon such as temperature, air pollution, etc. A careful deployment of sensors is necessary in order to get a better knowledge of these physical phenomena while ensuring the minimum deployment cost [18]. In this work, we focus on using WSN for air pollution mapping and tackle the optimization problem of sensor deployment [3]. Unlike most of the existing deployment approaches, which are either generic or assume that sensors have a given detection range, we define an appropriate coverage formulation based on an interpolation formula that is adapted to the characteristics of air pollution sensing. We derive from this formulation two deployment models for air pollution mapping using integer linear programming while ensuring the connectivity of the network and taking into account the sensing error of nodes. We analyze the theoretical complexity of our models and propose heuristic algorithms based on linear programming relaxation and binary search. We perform extensive simulations on a dataset of the Lyon city, France in order to assess the computational complexity of our proposal and evaluate the impact of the deployment requirements on the obtained results.

Characterization of radio links in case of a ground deployment

In this work, we are interested in characterizing the link properties of a wireless sensor network with nodes deployed at ground level [5]. Such a deployment is fairly common in practice, e.g., when monitoring the vehicular traffic on a road segment or the status of infrastructures such as bridges, tunnels or dams. However, the behavior of off-the-shelf wireless sensor nodes in these settings is not yet completely understood. Through a thorough experimentation campaign, we evaluated not only the impact of the ground proximity on the wireless links, but also the impact of some parameters such as the packet payload, the communication channel frequency and the topography of the deployment area. Our results show that a ground-level deployment has a significant negative impact on the link quality, while parameters such as the packet size produce unexpected consequences. This allows us to parameterize classical theoretical models in order to fit a ground-level deployment scenario. Finally, based on the lessons learned in our field tests, we discuss some considerations that must be taken into account during the design of communication protocols and before the sensor deployment in order to improve network performance.

Sensor deployment in linear wireless sensor networks using the concept of virtual node

In a multi-hop wireless sensor network with a convergecast communication model, there is a high traffic accumulation in the neighborhood of the sink. This area constitutes the bottleneck of the network since the sensors deployed within it rapidly exhaust their batteries. In this work, we consider the problem of sensors deployment for lifetime maximization in a linear wireless sensor network [6]. Existing approaches express the deployment recommendations in terms of distance between consecutive sensors. Solutions imposing such constraints on the deployment may be costly and difficult to manage. We propose a new approach where the network is formed of virtual nodes, each associated to a certain geographical area. An analytical model of the network traffic per virtual node is proposed and a greedy algorithm to calculate the number of sensors that should form each virtual node is presented. Performance evaluation shows that the greedy deployment can improve the network lifetime by up to 40%, when compared to the uniform deployment. Moreover, the proposed approach outperforms the related work when complemented by a scheduling algorithm which reduces the messages overhearing. It is also shown that the lifetime of the network can be significantly improved if the battery capacity of each sensor is dimensioned taking into account the traffic it generates or relays.

Core network function placement in self-deployable mobile networks

Emerging mobile network architectures (e.g., aerial networks, disaster relief networks) are disrupting the classical careful planning and deployment of mobile networks by requiring specific self-deployment strategies. Such networks, referred to as self-deployable, are formed by interconnected rapidly deployable base stations that have no dedicated backhaul connection towards a traditional core network. Instead, an entity providing essential core network functionalities is co-located with one of the base stations. In this work, we tackle the problem of placing this core network entity within a self-deployable mobile network, i.e., we determine with which of the base stations it must be co-located [9], [15] [15]. We propose a novel centrality metric, the flow centrality, which measures a node capacity of receiving the total amount of flows in the network. We show that in order to maximize the amount of exchanged traffic between the base stations and the core network entity, under certain capacity and load distribution constraints, the latter should be co-located with the base station having the maximum flow centrality. We first compare our proposed metric to other state of the art centralities. Then, we highlight the significant traffic loss occurring when the core network entity is not placed on the node with the maximum flow centrality, which could reach 55% in some cases.

Cyber physical systems and Internet of things: emerging paradigms on smart cities

A city is smart when investment in traditional and modern infrastructure, human and social capital, fuel well being, high quality of life, and sustainable economic development. The Smart City paradigm is driven by technological evolution in the field of Information and Communication Technologies, and more specifically the paradigms of Internet of Things, Industrial Internet of Things and their confluence with Cyber Physical Systems [12]. Smart Cities present a number of application domains that are related to their critical infrastructures, including energy and transport. These domains present needs similar to the industrial manufacturing environment utilizing smart devices and employing control automation for their applications. They could thus be labeled as industrial domains in the wider sense. This work presents three application domains associated with Smart Cities, namely Smart Lighting, Smart Buildings / Energy, and Smart Urban Mobility, identifies their requirements and challenges and reviews existing solutions.