Mehdi Mekni

A Survey on Sensor Webs Simulation Tools

Currently, few real sensor Web applications are being explored and some of them are yet to come. Meanwhile, developing and deploying prototypes in order to analyze the sensor Web performance supposes a great effort. Consequently, simulation is fundamental to study sensor Webs, and is being the common way to test new applications and protocols in this evolving research field. This fact has brought a recent growing number of simulation tools available to model sensor Webs. In this paper, we provide background on a number of different sensor webs simulation tools and we discuss the advantages and the drawbacks of each. We also propose an evaluation methodology in order to assess the capabilities of each simulation tool. The results of the evaluation process are analyzed and the open research issues are pointed out providing for an opportunity of improvement of future sensor Web simulators.

Informed Virtual Geographic Environments: An Accurate Topological Approach

Virtual Geographic Environment (VGE) technique derives from Geographic Information Systems (GIS) and Virtual Reality (VR). A VGE represents three dimensional geographic data, to target visualisation as well as simulation applications. It is generally built upon a grid-based representation which raises the well-known problems of localised data accuracy and multiple data merging. In this paper we propose a novel approach of VGE using a topological model. This approach provides an exact representation of GIS data, allowing an accurate geometrical exploitation. Moreover, our model can merge and represent several semantic information, even if spatially overlapping. Finally, we illustrate this model with a VGE application which is able to automatically extract the required data from standard GIS files, and which then allows to navigate and retrieve information from the computed VGE.

Holonic Modelling of Large Scale Geographic Environments

In this paper, we propose a novel approach to model Virtual Geographic Environments (VGE) which uses the holonic approach as a computational geographic methodology and holarchy as organizational principle. Our approach allows to automatically build VGE using data provided by Geographic Information Systems (GIS ) and enables an explicit representation of the geographic environment for Situated Multi-Agent Systems (SMAS) in which agents are situated and with which they interact. In order to take into account geometric, topologic, and semantic characteristics of the geographic environment, we propose the use of the holonic approach to build the environment holarchy. We illustrate our holonic model using two different environments: an urban environment and a natural environment.

Hierarchical Path Planning for Multi-agent Systems Situated in Informed Virtual Geographic Environments

Multi-Agent Geo-Simulation (MAGS) is a modelling and simulation paradigm which involves a large number of autonomous situated agents evolving in, and interacting with, an explicit description of a geographic environment called a Virtual Geographic Environment (VGE). Path planning in MAGS has to be solved in real time, often under constraints of limited memory and CPU resources. Moreover, the computational cost of path planing increases in complex and large-scale VGEs. In addition, most current planners only provide agents with obstacle-free paths and do not take into account the environments’ topologic and semantic characteristics nor the agents’ capabilities. In this paper, we propose a novel approach to build a semantically-enhanced and geometrically-accurate VGE called an Informed VGE (IVGE). We also present a hierarchical path planningalgorithm which takes advantage of this IVGE’s rich description in order to provide autonomous situated agentswith plausible paths with respect to both the environment’sand the agents’ characteristics.

Using multi-agent geo-simulation techniques for intelligent sensor web management

Sensor webs consist of a large collection of small nodes providing collaborative and distributed sensing ability in unpredictable environments. Nodes composing such sensor webs, are characterized by their resource restrictions, especially the energy, the processing, and the communication capacities. These nodes are also in constant interaction with each other and with their geographic environment. An efficient system aiming at managing sensor webs must take into account the evolution of the sensor nodes as well as the geographic environment. Such a management process involves coping with a variety of dynamic variables including the nodes characteristics, the environment properties as well as the sensed data. In this context, Multi-Agent Geo-Simulation (MAGS) provides a flexible approach that can be used to easily analyse complex systems such as sensor webs in large scale georeferenced environments. The purpose of this paper is to present SensorMAGS, an agent-based geo-simulation system which manages sensor nodes in virtual geographic environments. This system is applied in the context of a water resource monitoring project.

Using Multi-agent Geo-simulation Techniques for the Detection of Risky Areas for Trains

A transportation system is spatially and functionally distributed; its subsystems have a high degree of autonomy and are in constant interaction with each other and with the surrounding geographic environment. Modeling and simulating such systems in large-scale geographic spaces is a complex process. In this paper we address the domain of railway systems, and more particularly the problem of detecting risky areas along railroads. This requires that we consider a variety of static and dynamic variables, including train characteristics, hazardous events (e.g. rock-falls), and the properties of the large-scale geographic environment, as well as weather conditions. This simulation enables us to recommend speed limits in risky areas while taking into account all of the aforementioned factors. Since statistical and analytical models are not appropriate to represent such a complex process in which spatial constraints are of high importance, we adopted a multi-agent geo-simulation (MAGS) approach that facilitates the simulation of complex systems in large-scale geo-referenced environments. In this paper, we present Train-MAGS, an agent-based geo-simulation tool that simulates train behaviors in risky areas in large-scale virtual geographic environments. We also demonstrate how risky areas can be detected in real time using an agent-based approach. This work also illustrates how the application of artificial intelligence techniques, such as the MAGS approach, provides interesting perspectives of realistic and plausible simulations aimed at improving the functioning, the efficiency, and the safety of the transportation systems.

A Multi-agent Geosimulation Approach for Sensor Web Management

Sensor Webs can be thought of as distributed network systems composed of hundreds of resource constrained nodes. Sensor Webs are deployed in large scale geographic environments for in-situ sensing and data acquisition purposes. However, interpreting the collected data as well as managing the sensor Web has historically been done manually. This task has grown difficult if not impossible due to the complex functionality of modern sensor Webs. Current initiatives seek to automate the process of data interpretation and sensor Web management. In this paper, we propose a multi-agent geosimulation approach for the management of sensor Webs. Our approach is applied in the context of a water resource monitoring project. Current results show the adequacy of our approach to cop with the highly dynamic operating conditions of such an application domain and its inherent distribution of resources.

A Knowledge-Based Multi-agent Geo-simulation Framework: Application to Intelligent Sensor Web Deployment

Sensor Web deployment is by nature a spatial problem since nodes are highly constrained by the geographic characteristics of the environment. Therefore, there is a need for an efficient modelling paradigm to address the issue of SW deployment taking into consideration the constraints of the geographic space. In this paper we propose a knowledge-based multi-agent geo-simulation framework to support the simulation of SW deployments in Informed Virtual Geographic Environments. This framework builds on our previous works on Informed Virtual Geographic Environments generation, on spatially reasoning agents and on qualitative reasoning about geo-simulation results. We illustrate the framework with a scenario of a sensor web deployment for weather monitoring purposes.

Technical capability of the radio access technology 1xEV-DO

The performance of a mobile network is essentially based on the capability of its radio access technology. This paper presents technical capabilities of the emerging radio access technology 1xEV-DO. Such capabilities are expressed in terms of throughputs, and are based on realistic radio and geographical parameters, as well as realistic traffic models. Simulation results enable to evaluate how environment conditions affect the throughput offered by 1xEV-DO.

A Model-Driven Simulation for Performance Evaluation of 1xEV-DO

Finding an appropriate approach to evaluate the capacity of a radio access technology with respect to a wide range of parameters (radio signal quality, quality of service, user mobility, network resources) has become increasingly important in todays wireless network planning. In this paper, we propose a model- based simulation to assess the capabilities of the IxEV- DO radio access technology. Results are expressed in terms of throughputs and signal quality (C/I and Ec/Io) for the requested services and applications.