Philippe Hunel

Classification of usual protocols over Wireless Sensor Networks

Applications over Wireless Sensor Networks (WSNs) are growing quickly. Various parameters may be considered to configure a network functioning but there is a lack of methodologies able to guide to choose the most appropriate parameters for any specific situation. An application can be characterized as one of the following three applications: a regular application, an application requiring a high communication rate, and a burst rate based application. In WSNs, the following routing protocols are usually used: AODV, AOMDV, DSDV and DSR. The ZigBee protocol was designed based on the assumption that infrastructure nodes have a constant power supply and low-rate wireless personal area networks. In the ZigBee Medium Access Control (MAC) layer, there exists two system parameters which provide a power-saving mechanism: macBeaconOrder (BO) and macSuperFrameOrder (SO). We are convinced that the choice of the appropriate protocol in each layer will surely have an impact on the whole network functioning. In this paper, we intend to observe the impact of these choices on the performances in the purpose of getting a useful classification. These analyses are conducted through the NS-2 simulator. We have experimented various routing protocols, BO and SO values on different kinds of applications in order to observe two relevant indicators on WSNs: energy consumption and lost packet rate.

Acoustic counting algorithms for wireless sensor networks

This study presents two algorithms that count birds with wireless sensors equipped with microphones. Audio inputs are parametrized to get some kind of fingerprints which are used to recognize the song of the birds in a classification process. Afterward, counting algorithms derive an estimate of the number of singing birds in the habitat. Unlike traditional approaches which leverage the audio waveform to get the location of the targets, we use a trilateration technique on graphs derived from the detection of the birds. These graphs exhibit nice properties which enable the finding of the estimate in polynomial time. Further, experiments are conducted and confirmm the efficiency of our counting algorithms even in the presence of noise.

Counting birds with wireless sensor networks

This paper proposes several methods to estimate the number of endangered birds in their habitat. Our solutions use passive unknown networks sensors to get birds positions and gather data to a central base which runs our algorithms to estimate the number of singing birds. A first scheme derives the motes networks and the data in an altered unit disk graph to give its estimation on the number of birds. The second scheme, a linear algorithm, uses aggregated information from the motes to count the birds. Finally, we confirm our schemes efficiency through experimentation.

Towards efficient deployment of wireless sensor networks

Applications over wireless sensor networks WSNs are various and different. Many routing protocols have been proposed for WSNs since a decade. Medium access control protocols can differ from a network to another. The transmission range can also be variable from a sensor to another depending on their battery capacities. All these various protocols have an influence on the WSNs performance, in particular, the quality of service QoS they provide. It is worthy to choose the appropriate protocol for each specific situation in order to ensure a high security of the network. In this paper, we show that the type of application, the type of routing protocol, and the transmission range value have a real impact on WSN performance. Indeed, if we do not choose the right protocol in the right situation, the network could provide a low QoS in terms of lost packet rate and energy consumption. We have undertaken a set of experimentations in order to extract a road map that could be useful for any designer who intend to deploy a WSN with a high QoS degree. For the application layer, we have handled three types of applications: regular applications, applications requiring a high communication rate, and burst rate based applications. We have also considered different network sizes. For the routing layer, we have investigated the Ad hoc On-demand Distance Vector, ad hoc on-demand multipath distance vector routing, dynamic source routing, and Destination-Sequenced Distance Vector protocols. Various transmission range values have been used. We have conducted many simulations through the NS-2 simulator in order to analyze two relevant QoS indicators on WSNs: energy consumption and lost packet rate. Copyright

Data collection using WSN for counting individuals and habitat characterization

Abstract Decrease in the number of individuals of a species is an indicator of the state of biodiversity in a region. It is difficult to estimate this decline in the traditional way. We suggest to use ICT to measure this phenomenon. We propose using a distributed algorithm to count individuals in a population and to collect abiotic factors in order to characterize habitat. The first phase consists of detecting the presence of individuals from mapping ecotopes, the second allows counting the number of individuals and the last aggregates the numbers of individuals over several paths. We propose an approach that uses a wireless sensor network built on a linear architecture based on the concept of green tunnel. Here, each mote has a successor and a predecessor.

Anomaly Detection with Wireless Sensor Networks

The aim of this study is to suggest two automated techniques able to help medical staff to detect earlier than usual some diseases using wireless sensor networks (WSNs). In this context, a patient is equipped with physical sensors which sense health parameters. This WSN will perform some computations and will run an alarm when a disease is suspected. The first technique uses a population protocol to handle data exchanged between motes and provides an efficient algorithm to suggest that a disease is diagnosed on a patient. The algorithm is distributed, i.e., the decision may be done by any sensor dealing with the disease detection. The second technique uses a token algorithm where, some motes are denoted as masters. Each of them is in charge of deciding if a specific disease occurs. This technique is not totally distributed but enhances the network efficiency regarding to the energy consumption, the time execution and the number of exchanged messages.

A data collection framework for tracking collective behavior patterns

Many initiatives have been taken to observe the adaptation of endangered animal species to various environmental changes they face and their chances of surviving. In this paper, we propose an original solution that consists on a new framework based on wireless sensor technology that enables to track individual movements and to collect spatio-temporal data to be analyzed without any harmful contact with animals. We discuss network configuration parameters what may optimize the elicitation of two specific kinds of collective motion behavior from such recorded data.

Population protocol over Wireless Sensor Networks

The aim of this study is to suggest an automated technique for distributed decision. It is based on population protocol deployed on a Wireless Sensor Networks (WSN). This approach could be used by any medical staff to detect earlier than usual some diseases on patients. Moreover, It could be easily adapted to many other fields (fire monitoring, environment supervising, …) In this context, a patient is equipped with health parameter transducers which are connected to a WSN. This WSN will perform some computations and will raise an alarm when some diseases are suspected. The algorithm is distributed, i.e., the decision may be done by any mote dealing with the disease detection. The experimentations show promising results.

Simulation of large scale WSN for medical care

The aim of this study is to perform a simulation of large scale Wireless Sensor Networks (WSN) working on medical diagnosis. The main feature of this WSN is its density and the fact that all sensors are in the same radio range. Our approach helps medical staff to diagnose diseases in an automatic way. In this context, each patient is equipped to a set of sensors. Each sensor is connected to a transducer dedicated to measure a specific health parameter. This WSN will perform some computations and run an alarm when some diseases are suspected. This technique is based on the population protocol to handle data exchanged between sensors. This approach is in fact an efficient distributed algorithm which implies that the diagnose may be done by any sensor dealing with the disease detection. The main result of this paper is the approach supports large scalability which proves its practicability for real cases.

Detecting movement patterns with wireless sensor networks: application to bird behavior

More and more animal species are endangered every day on earth. In order to study their adaptation to world and climate change and their chances of survival, numerous initiatives have been taken that mostly need human intrusion into animal communities. Today mobile devices enable researchers to go beyond this limit. In this paper, we propose an original solution that consists on a new framework for detecting individual songs in a bird population and identifying remotely by this way their collective behavior in movements without human interaction. Movement patterns are elicited by analyzing data collected via wireless sensors fitted with microphone. Whereas similar methods use mobile devices fitted on some specimens, we rather propose fixed sensors. We demonstrate that this solution provides a good answer to technical constraints assessed by the context and we discuss results of experimental simulations that allow to define optimized parameters for the architecture to be set up on the ground. Experimental results are provided and show the relative impact of different parameters such as the number of sensors or the population size on the detection rate.