Richard Lorion

A single-hop clustering and energy efficient protocol for wireless sensor networks

Energy efficiency is an active research area in WSNs technology. There is an extensive research work going towards this direction and existing mechanisms fail to address the problem completely due to its limited specificity. This work focuses on the idea of enhancing the network lifetime on the basis of cluster-heads (CHs) remaining energy levels. Thus, instead of changing CHs at every round for dynamic clustering, we propose two sorts of CH threshold function as energy threshold function and optimal CH range threshold function for maximizing the network lifetime. Simulation results show that our protocol maximizes the network lifetime and captures the data three times more than the other known energy-efficient protocols in the literature.

L'utilisation des algorithmes génétiques pour l'identification de profils hydriques de sol à partir de courbes réflectométriques

Abstract We developed a unidimensional microwave propagation model in a stratified medium. It calculates, from a given soil water content profile, the reflected signal trace one would measure by timedomain reflectometry along a transmission line inserted in the soil. We identify the soil water content profile corresponding to a measured reflected signal trace using an identification technique based on optimisation of the model parameters by a genetic algorithm.

A clustering algorithm based on energy variance and coverage density in centralized hierarchical Wireless Sensor Networks

In Wireless Sensor Network (WSN), the clustering algorithm was developed to reduce the total energy consumption which determines the lifetime of the whole network. As a result, a number of recently-designed energy-efficient routing algorithms stated that clustering approach has an important issue for organizing a network into a connected hierarchy and increasing the network lifetime. This paper proposes a new algorithm to improve the performance of Low Energy Adaptive Clustering Centralized (LEACH-C) by improving the criterion for electing a cluster-head and the determination of optimal number of cluster-heads. Firstly, the optimal number of cluster-heads is based on the density of the covering. The sensor nodes are deployed randomly on the plane area of the sensing field covered by the communication range of the node. Secondly, nodes having the highest remaining energy and the lowest energy variance consumption becomes cluster-heads. The variance parameter keeps energy consumption dispersion, if the considered node is elected as cluster-head. This dispersion highly depends on the relative positioning of the node to the base station. This is useful for predicting node status when elected as cluster-head in the current round in order to balance the network energy. The simulation and analytical results of the proposed algorithm outperform the existing protocols in terms of lifetime of the network.

An energy-efficient addressing mechanism for wake-up radio systems

Wake-up Radio receivers (WuRx) must be energy-efficient for their integration into Wireless Sensor Networks (WSNs). The most energy-hungry component is the address decoding hardware and it is generally powered by the node battery. In this paper, an addressing mechanism is proposed and the decoding process is explained in detail, on the contrary of previous works. This paper also shows the energy reduction of the address decoding stage while performed by a microcontroller, in comparison with one of the best correlator approach. The energy consumption and latency are also well investigated with real measurements, which is often omitted in previous works. Our approach is also flexible since a trade-off between energy consumption and wake-up latency is proposed. While decoding the address, the most energy-efficient mode consumes only 23.8 μA with a wake-up latency of 8.88 ms.

Energy-efficient data aggregation techniques for exploiting spatio-temporal correlations in wireless sensor networks

The energy-efficient data aggregation in Wireless Sensor Networks (WSNs) has grown as one of the promising area in many applications. Prior research works have suggested several spatio-temporal models for effectively reducing the data collection costs, but the models are limited to their specificity. This paper presents a pre-filtration method in every sensor node. While using pre-filtration techniques on nodes data pre-processing can suppress a huge amount of redundant or correlated data transmissions, thus maximizes the nodes battery lifetime. This paper proposes a framework using both relative variation (RV) and a data aggregative window function (DAWF), which can exploit both spatial and temporal redundancies in WSNs. However, both compressive and prediction-based approaches can find temporal data redundancies or correlations in sensor nodes as well as spatio-temporal correlations in Cluster-Head (CH) nodes. In this regard, the experimental study shows that the proposed mechanism among the considered network nodes can suppress a huge amount of required data transmissions, while providing reliable data towards the base station (BS).

Data window aggregation techniques for energy saving in Wireless Sensor Networks

Redundant data transmissions are likely to happen repeatedly inWireless Sensor Networks (WSNs). According to the literature survey, energy-efficiency predominately relies on data aggregation rather than routing or duty-cycling approaches. As data redundancy dominates the power usage in communication costs, in order to identify and reduce the redundant data transmissions by individual nodes, we propose a hybrid data aggregative window function (DAWF) algorithm for exploiting both spatial and temporal data redundancies in WSNs. Furthermore, the proposed novel approach aims to process the hybrid filtration using both compressive and prediction-based techniques in sensor nodes (SN) as well as in cluster-head (CH) nodes. In this regard, the experimental study case of this work show that the DAWF mechanism can suppress a huge amount of temporal redundant data transmissions in sensor nodes while providing reliable data messages towards the base station (BS). Moreover, DAWF CH can also suppress a large amount of spatial redundancies by utilizing the optimum DAWF parameters of the CH node.

Forwarding and routing cluster-based protocol for wireless sensor networks

This paper presents Forwarding and Routing Cluster-Based Protocol which aims to prolong wireless network lifetime by balancing energy consumption among all nodes. It avoids the premature death of the closest cluster-head (CH) for multi-hop protocols using hierarchical network clustering. FoRoC introduces two items: first, to take into consideration the nodes local informations during CHs selection steps, such as remaining energy and its coefficient of variation. And secondly, it also combines one-hop and multi-hop elementary path routing methods for data transfer for inter-cluster communication as a unique path. Furthermore, periodically changing the role between CH or end-node, and periodically changing the route between CHs and base-station, balances the CHs energy consumption. For going further towards the ideal energy balance which is illustrated by a coefficient of synchronous death. Simulation results show that the FoRoC shows great performance in terms of energy consumption and the network lifetime. Lifetime is increased by 80% compared to one-hop protocols. Compared to multi-hop protocol, FoRoC reaches a coefficient of synchronous death of 2.09.

Energy-efficient cluster-based protocol using an adaptive data aggregative window function (A-DAWF) for wireless sensor networks

We present an adaptive data aggregative window function (A-DAWF) for a distributed sensor network model in which nodes store data in their attribute window functions, and provide non-correlated data towards the base station (BS). Unlike previous works, namely data collection or data gathering management systems, we propose a novel approach that aims to process temporal redundant techniques in sensor nodes as well as providing spatial redundant filtration methods in cluster-head (CH) nodes. In this regard, preliminary results show that A-DAWF can suppress up to 90% of temporal redundant data among the considered sensor nodes by an optimal threshold of the window sizes, and their spatial correlations in CH node by a maximum error threshold compared to either periodic or a continuous data transmission system.

Radio Frequency Mapping using an Autonomous Robot: Application to the 2.4 GHz Band

Radio signal strength measurement systems are essential to build a Radio Frequency (RF) mapping in indoor and outdoor environments for different application scenarios. This paper presents an autonomous robot making the construction of a radio signal mapping, by collecting and forwarding different useful information related to all access point devices and inherent to the robot towards the base station. A real case scenario is considered by measuring the RF field from our department network. The RF signal mapping consistency is shown by fitting the measurements with the radio signal strength model in two-dimensional area, and a path-loss exponent of 2.3 is estimated for the open corridor environment.

Interference evaluation of WiFi devices over wake-up radio in wireless sensor networks

While Wake-up Radio (WuR) systems greatly improve the energy efficiency of Wireless Sensor Networks (WSNs), their resilience to interference is often neglected in previous works. This might be an issue due to the proliferation of wireless devices and the growing field of internet of things. In this paper, an evaluation of in-band interferences from WiFi devices over a WuR system is performed. The approach proves that WuR systems are still performing well when coexisting with external wireless networks, even if the energy-efficiency is slightly reduced.