Ines Slama

A hybrid MAC with prioritization for wireless sensor networks

This paper introduces I-MAC, a new medium access control protocol for wireless sensor networks. I-MAC targets at improving both channel utilisation and energy efficiency while taking into account traffic load for each sensor node according to its role in the network. I-MAC reaches its objectives through prioritized and adaptive access to the channel. I-MAC performances obtained through simulations for different network topologies, scenarios and traffic loads show significant improvements in energy efficiency, channel utilization, loss ratio and delay compared to existing protocols.

Multiple Mobile Sinks Deployment for Energy Efficiency in Large Scale Wireless Sensor Networks

In this paper, we consider the multiple sinks placement problem in energy constrained large-scale Wireless Sensor Networks (WSN). First, some fundamental design parameters in WSNs are investigated such as nodes deployment, the network architecture, sink velocity and transmission range. Each of these parameters is analysed and discussed according to its influence on the energy consumption in a WSN. Second, a simple and efficient approach for the placement of multiple sinks within large-scale WSNs is proposed. The objective is to determine optimal sinks’ positions that maximize the network lifetime by reducing energy consumption related to data transmissions from sensor nodes to different sinks. Balanced graph partitioning techniques are used to split the entire WSN into connected sub-networks. Smaller sub-networks are created, having similar characteristics and where energy consumption can be optimized independently but in the same way. Therefore, different approaches and mechanisms that enhance the network lifetime in small-size WSN can be deployed inside each sub-network. Performance results show that the proposed technique significantly enhances the network lifetime.

Topology Control and Routing in Large Scale Wireless Sensor Networks

In this paper, a two-tiered Wireless Sensor Network (WSN) where nodes are divided into clusters and nodes forward data to base stations through cluster heads is considered. To maximize the network lifetime, two energy efficient approaches are investigated. We first propose an approach that optimally locates the base stations within the network so that the distance between each cluster head and its closest base station is decreased. Then, a routing technique is developed to arrange the communication between cluster heads toward the base stations in order to guaranty that the gathered information effectively and efficiently reach the application. The overall dynamic framework that combines the above two schemes is described and evaluated. The experimental performance evaluation demonstrates the efficacy of topology control as a vital process to maximize the network lifetime of WSNs.

Routing for wireless sensor networks lifetime maximisation under energy constraints

Power limitation is one of the main constraints in sensor networks. Different power-saving strategies are proposed in the literature, but most of them are mainly focusing on power saving rather than maximizing the network lifetime. Moreover, Energy consumption related to reception operations is generally not considered. In this paper, we propose a new power based routing strategy that maximizes the network lifetime. The main idea is to dynamically select routes according to the remaining available power on sensors and the required power for both the transmission and reception operations. The objective is to not focus on minimizing energy consumption, but to fairly distribute power consumption so that the lifetime of the whole sensor network is maximized. The scheme is detailed and modeled. It is a non-linear programming problem that we analyzed by simulations. Numerical results show that the proposed scheme converges to an optimal routing that maximizes the network lifetime. They also demonstrate that energy consumption linked to reception operations has an important effect on the network lifetime.

DNIB: Distributed Neighborhood Information Based TDMA Scheduling for Wireless Sensor Networks

A slot assignment (or scheduling) in TDMA based wireless sensor networks (WSNs) considering energy efficiency, scalability and complexity is presented. The algorithm named DNIB is a new TDMA free collision distributed slot assignment algorithm for WSNs. DNIB relies on two-hop neighborhood information. Performance analysis and simulations show that DNIB is scalable and outperforms existing mechanisms.

A Free Collision and Distributed Slot Assignment Algorithm for Wireless Sensor Networks

This paper introduces I-MAC a new hybrid medium access control protocol for wireless sensor networks (WSNs). I- MAC combines both CSMA and TDMA techniques while introducing prioritization. It aims to improve energy efficiency as well as channel utilization. I-MAC is composed of two phases: a setup phase and a transmission phase. During the setup phase, several operations such as neighborhood discovery, slot assignment, local framing and global synchronization are run. During the transmission phase, a priority scheme is investigated to control the access to the channel. We focus in this paper on the description and evaluation of the different setup phase operations particularly DNIB, a new TDMA free collision slot assignment algorithm proposed for WSNs.

Priority-Based Hybrid MAC for Energy Efficiency in Wireless Sensor Networks

This paper introduces I-MAC, a new medium access control protocol for wireless sensor networks. I-MAC targets at improving both channel utilization and energy efficiency while taking into account traffic load for each sensor node according to its role in the network. I-MAC reaches its objectives through prioritized and adaptive access to the channel. I-MAC performances obtained through simulations for different network topologies, scenarios and traffic loads show significant improvements in energy efficiency, channel utilization, loss ratio and delay compared to existing protocols.

Tracking topology dynamicity for link prediction in intermittently connected wireless networks

Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. The validity of this method is proved when the prediction is made in a distributed way (i.e. with local information) and its performance is compared to well-known link prediction metrics proposed in the literature.

Adaptive Lifetime Maximization Strategies for Wireless Sensor Networks

Energy consumption optimization constitutes one of the main challenges in wireless sensor networks. Most of the power based routing strategies proposed in the literature are based on global power consumption optimization rather than maximizing the network lifetime. In this paper, we propose an adaptive routing strategy that maximizes the lifetime of the sensor network, where optimal routes are selected in order to delay, as long as possible, the first energy run out among sensor nodes. The proposed routing strategy also takes into account both the reception and the transmission energy dissipations. Moreover, in order to adapt to the changes that may occur in the network topology or characteristics, we propose a global adaptive framework that dynamically reconfigures routes according to the current network state. The proposed strategy is modelled and simulation results are presented