Rana Rahim-Amoud

Crisis management using MAS-based wireless sensor networks

Wireless communication is increasingly used to manage large-scale crises (e.g., natural disasters or a large-scale city fire). Communication has traditionally been based on cellular networks. However, real-life experience has proven that the base stations of these networks may collapse or become unreachable during a crisis. An incident commander must also know as much information as possible about the occurring events to control them quickly and efficiently. This paper thus proposes a crisis management approach that overcomes the problems encountered by the base stations and insures relevant, rich and real-time information about events. This approach is based on wireless sensor networks, which are distributed in nature with no need for infrastructure and could be deployed in dangerous and inaccessible zones to gather information. Our proposal uses a multi-agent system as a software layer. The multi-agent system aims to improve the wireless sensor network performance by allowing cooperation between sensor nodes, offering better lifetime management and virtualizing the application layer. This virtualization supports several required applications simultaneously, including event monitoring and object tracking. Through successive simulations, we prove the importance of our approach in crisis management using several criteria to estimate the positions error in object tracking, end-to-end delay and wireless sensor network lifetime management.

A cooperative aggregation-based architecture for vehicle-to-grid communications

In the future Intelligent Transportation Systems, vehicles will be equipped with special units giving them the capacity to communicate wirelessly. Furthermore, electric vehicles are expected to take a bigger part of the market in the future. Global preoccupations to reduce carbon emissions and stimulate the use of renewable and sustainable energies have motivated the concept of vehicle-to-grid power, which integrates the electric vehicles within the smart grid (the electricity network of the future). The vehicle-to-grid vision aims to take advantage of these battery equipped vehicles, using them as a storage device for intermittent energy sources, and as a power resource to provide ancillary services to the power grid. This paper focuses on the architectural needs of such a system, specifically at the communications level. It also presents an agent-based model for an aggregative system for vehicle-to-grid communications. The agent-based approach will allow the distributed architecture to benefit from a variety of well-established communication and cooperation mechanisms and methods that can be applied to the vehicle-to-grid concept.

An Agent-Based Approach for Energy Management in Smart-Grids

The advances in Information and Communication Technologies (ICT) permits interactions among the computational and the physical elements of the smart-grid, and provide opportunities for novel energy management techniques allowing thus renewable energy integration and energy price minimization. Few of the current energy management schemes integrate storage aspects. In this paper, we propose an agent-based algorithm for better energy management in the smart-grid using a storage system. Furthermore, we propose a negotiation algorithm to help consumer choose the appropriate producer which provides him the needed energy at the lowest price. Simulation results show that our proposal minimizes the energy costs for each energy demand and reduces conventional energy utilization.

Factors that May Influence the Performance of Wireless Sensor Networks

The Wireless Sensor Networks (WSNs) are penetrating more and more our daily life. They are used in a large type of applications as supervision, tracking and control in military, environmental, medical and several other domains. Therefore, new approaches and protocols are proposed every day in order to optimise the performance of the WSNs and to increase their reliability and quality of service. These new protocols take into consideration the challenges of the WSN and they are built up some key factors (parameters and concepts) to achieve their goals.

An Agent-Based Approach for Efficient Energy Management in the Context of Smart Houses

Traditional power systems are centralized systems that supply electricity to end users through unidirectional transmission and distribution networks. The heterogeneity of renewable energy sources has introduced complexity in the transmission and distribution of electricity. Thus, intelligent distributed coordination and real-time information is needed to ensure that the electricity infrastructure will run efficiently in the future. This information enables the grid to meet the challenge of balancing supply and demand by actively sensing and responding to fluctuations in power demand, supply, and costs. In the near future, smart homes will be able to exchange energy, to sell to or buy from different actors available in the market. These new changes will introduce a soft competition in the market where each user will try to get lower contract prices according to his needs. In order to respond to the user’s needs while integrating new sources of energy, we propose an agent-based approach for optimizing energy consumption. We present the agents’ interactions that aim to procure energy for household activities at a suitable price to satisfy the user’s needs. The results showed that these strategies can lead to a more environmental friendly, responsible, and efficient way to consume and distribute energy.

A Multi-criterion Data Aggregation Scheme for WSN

The basic role of a Wireless Sensor Network (WSN) is to collect information from the environment by many sensor nodes (SNs). The SN typically has a finite battery life and nodes’ failures can lead to network partition. Therefore, it is important to minimize the energy usage of each sensor node and to manage the power of SN in critical position that their failure could divide the network. The current paper proposes a data aggregation scheme based on a multi-agent system to reduce the amount of communicated information and hence to reduce the power consumption. In addition, this approach manages the power of each SN following several criteria like its resident power, the importance of its information, the network density and its position within the WSN. Through successive simulations, in different network scales, the proposed algorithm proved interesting results in term of power consumption optimization and power management of nodes in critical positions

Improvement of MPLS Performance by Implementation of a Multi-Agent System

Multi-Protocol Label Switching (MPLS) is a network layer packet forwarding technology that provides flexible circuit switched traffic engineering solutions in packet switched networks by explicit path routing. However, the actual weakness of MPLS resides in its inability to provide application-level routing intelligence, which is a fundamental component especially for voice delivery. In this paper we propose to introduce a Multi-Agent System (MAS) within the MPLS network to improve its performance. The introduction of agents takes place into the decision points in MPLS at the flow level, and distributes traffic based on the quality of service required by the type of traffic. We also propose an intelligent framework for network as well as an architecture of our agent in order to improve the efficiency of the Quality of Service (QoS) within MPLS.

Enhancing smart grid operation by using a WSAN for substation monitoring and control

One of the main preoccupations of the next generation power network, i.e. the smart grid, is improving the reliability of the power network. In order to achieve that, monitoring and control applications play an important role, in particular at a substations level. Using a wireless sensor and actuator network is an attractive option for these applications. However, what is missing so far is that information collection should be complemented with the ability to transform significant data into actions in a decentralized manner. In this paper, we address this issue by adopting an agent-based approach. Autonomous agents are embodied in sensor nodes in order to evaluate the importance of collected data and choose an appropriate communication policy. In order to evaluate each phase of the proposed algorithm, different variants are compared with the legacy client/server scheme. Simulation results have shown better performance in terms of network congestion, energy consumption, and transmission delay.

Information-Importance Based Communication for Large-Scale WSN Data Processing

Gathering information in an energy-efficient and scalable manner from a wireless sensor network is always a basic need. In this work, we use the multi-agent approach in order to build an Information-Importance Based Communication for large scale wireless sensor network data processing. The principal goal of our proposition is to tackle the problem of network density and scalability in an energy efficient manner. Simulation results are provided to illustrate the efficiency of our proposition.

A Strategy for Multi-Agent Based Wireless Sensor Network Optimization

The multi-agent approach has been proposed in the literature as a solution for data gathering, and routing in Wireless Sensor Networks (WSNs). In these propositions, the knowledge of an agent is generally limited to a single parameter such as the energy of the sensor node and/or to the address of its next hop in a routing protocol proposition. In this paper, we propose a strategy for the agent to make a more appropriate decision to cooperate or not in a data gathering session. This strategy uses, in addition to the energy of the node, several parameters from the local view of the agent as the position of the node within the network, the network density, and the information importance degree. Through successive simulations, this strategy has proved its ability to manage cleverly the power consumption of the sensor nodes and hence to extend the WSN life time.