Ousmane Thiare

2-hop neighborhood information for cover set selection in mission-critical surveillance with Wireless Image Sensor Networks

Mission-critical surveillance applications such as intrusion detection or disaster response have vital requirement in QoS. We consider a Wireless Image Sensor Network (WISN) with a scheduling of image sensor nodes activity based on the application criticality level. Sentry nodes capable of detecting intrusions with a higher probability than others will alert neighbor nodes as well as activating cover sets member for image disambiguation or situation-awareness purposes. In order to optimize the performance of image transfer from multiple sensor nodes to the Sink we propose a 2-hop neighborhood information- based cover set selection to determine the most relevant cover sets. Then, in order to be consistent with our proposed approach, a multi-path extension of Greedy Perimeter Stateless Routing (called T-GPSR) wherein routing decisions are also based on 2-hop neighborhood information is proposed. Simulation results show that our proposal reduces packet losses, enabling fast packet delivery and higher visual quality of received images at the Sink.

Performance Comparison of Hierarchical Checkpoint Protocols Grid Computing

Grid infrastructure is a large set of nodes geographically distributed and connected by a communication. In this context, fault tolerance is a necessity imposed by the distribution as any node can fail at any moment and the average time between failures highly decreases. To improve the robustness of supercomputing applications in the presence of failures, many techniques have been developed to provide resistance to these faults of the system. Fault tolerance is intended to allow the system to provide service as specified in spite of occurrences of faults. To meet this need, several techniques have been proposed in the literature. We will study the protocols based on rollback recovery classified into two categories: checkpoint-based rollback recovery protocols and message logging protocols. However, the performance of a protocol depends on the characteristics of the system, network and applications running. Faced with the constraints of large-scale environments, many of algorithms of the literature showed inadequate.Given an application environment and a system, it is not easy to identify the recovery protocol that is most appropriate for a cluster or hierarchical environment, like grid computing. Hence there is a need to implement these protocols in a hierarchical fashion to compare their performance in grid computing. In this paper, we propose hierarchical version of these protocols. We have implemented and compare their performance in clusters and grid computing using the Omnet++ simulator.

A clustering Group Mutual Exclusion algorithm for mobile ad hoc networks

A mobile ad hoc network can be defined as a network that is spontaneously deployed and is independent of any static network. The network consists of mobile nodes1 with wireless interfaces and has an arbitrary dynamic topology. The networks suffers from frequent link formation and disruption due to the mobility of the nodes. A clustering method is used for obtaining a hierarchical organization for the ad hoc networks. In this paper we present a clustering token based algorithm for Group Mutual Exclusion in ad hoc mobile networks. The proposed algorithm is adapted from the RL algorithm in [1] and utilizes the concept of weight throwing in [2]. The proposed algorithm is sensitive to link forming and link breaking. The algorithm ensures the mutual exclusion, the bounded delay, and the concurrent entering properties.

Target coverage management in wireless sensor networks

As an important issue reflecting the QoS of the sensing task, coverage problem impacts widely on the performance of wireless sensor networks. The target coverage lifetime maximization problem is yet a challenging problem, which tries to settle a compromise between managing the coverage of a set of targets and maximizing the lifetime of the network. This problem becomes more accurate when targets detection is distance dependent. In this paper, we address the target coverage lifetime maximization problem by considering a probabilistic coverage model, which takes into account the distance parameter. We propose an algorithm based on a modified version of the classical well-known weighed set cover which organizes sensors in disjoint and non-disjoint set covers. Performance evaluation of our solution indicated good performance in managing coverage of targets while extending the network lifetime.

ALARM: An energy aware sleep scheduling algorithm for lifetime maximization in wireless sensor networks

Wireless Sensor Networks have emerging recently as a key solution to monitor remote or hostile environments. Such networks are faced for a numerous challenges such as energy efficiency usage, network lifetime maximization, etc. Sensing and communications consume energy, therefore judicious power management can effectively extend network lifetime. In this paper we focus on the problem of energy efficiency and lifetime maximization and we propose an energy aware sleep scheduling algorithm for lifetime maximization in wireless sensor networks (ALARM). ALARM is a strong node scheduling based mechanism for lifetime maximization in wireless sensor networks. Our mechanism use a probabilistic model that permit to cover fault tolerance and a dynamic and distributed sleep timer computation. Simulations and experimental results are presented to verify our approach and the performance of our mechanism. Experimental results show that ALARM allow low control overhead and a better energy management than PEAS with a ratio of 35,40427%

An Energy Efficient Self-healing Mechanism for Long Life Wireless Sensor Networks

In this paper, we provide an energy efficient self-healing mechanism for Wireless Sensor Networks. The proposed solution is based on our probabilistic sentinel scheme. To reduce energy consumption while maintaining good connectivity between sentinel nodes, we compose our solution on two main concepts, node adaptation and link adaptation. The first algorithm uses node adaptation technique and permits to distributively schedule nodes activities and select a minimum subset of active nodes (sentry) to monitor the interest region. And secondly, we introduce a link control algorithm to ensure better connectivity between sentinel nodes while avoiding outliers appearance. Without increasing control messages overhead, performances evaluations show that our solution is scalable with a steady energy consumption. Simulations carried out also show that the proposed mechanism ensures good connectivity between sentry nodes while considerably reducing the total energy spent.

A weight-based greedy algorithm for target coverage problem in wireless sensor networks

Recent improvements in affordable and efficient integrated electronic devices have enabled a wide range of applications in the estate of wireless sensor networks. An important issue addressed in wireless sensor networks is the coverage problem. This latter is centered on a fundamental question: how well do the sensors observe the physical space? A major challenge in coverage problem is how to maximize the lifetime of the network while ensuring coverage of a set of targets. To achieve this, the usual process, consists on scheduling sensors activity, which enables energy dissipation control. Scheduling process goes by activating sensors by round such that in each round, only one subset of sensors that satisfies the coverage requirement is activated, while all other sensors are in a low energy mode and will be activated later. In this paper, we propose a weight-based greedy algorithm (WGA) which organizes sensors in multiple subsets. Our objective is to partition an initial set of sensors into a maximum possible number of sensors set covers (SSCs), which can completely monitor targets in a region of interest. Performance evaluation of WGA have proven its efficiency over some well-known algorithms proposed in the literature, in term of computed set covers.

Bird Sounds Detection Using Normalized Audio Power Sequences

In this paper, we bring out the first research element in building an automated surveillance system for rice field monitoring against pest and grain-eating birds. We study how accurate can be the use of normalized power sequences in detecting bird sounds, which is a kind of harmonic sound type. We proposed a simply detection scheme (which can be executed by sensors), for the purpose of detecting the presence of birds based on the sounds and calls they produce. The scheme is based on pruning audio frame blocks to keep relevant peaks, computing the normalized power of the sequences of captured audio files, and derive the presence of birds by only considering important values of the variances of the input files. The experimental results conducted to test the efficiency of the scheme show that 91,07% of bird calls from our database can be correctly identified.

An hybrid scheduling algorithm for Wireless Sensor Networks

Wireless Sensor Networks are attracting during last decades more interest in both civil and military fields. This interest combined with recent advanced in microelectronics drive the Wireless Sensor Networks in the front of the stage. They are emerging as a key solution to monitor remote and/or hostile environments. However, they still faced various challenges among which, power management is one of the most remarkable. In this paper, we focus on power management problem and propose an Hybrid Scheduling Algorithm (HSA) for densely deployed Wireless Sensor Networks. The proposed solution is composed with two main phases: an initialization phase with where nodes execute a random scheduling technique and stabilization phase with an adaptive scheduling scenario. Our algorithm ensures a fast network availability with almost a representative number of sentinel (active nodes) from the network deployment. This also guarantee a consequent reduction of network overhead due to initialization informations exchanged. The algorithm presented here are also confirmed by simulations and obtained results show that our scheme can significantly reduce the energy consumption.

Best cover set selection with multi-criteria approach in mission-critical surveillance for Wireless Image Sensor Networks

Mission-critical surveillance applications such as intrusion detection or disaster response have vital requirement in QoS. We consider a Wireless Image Sensor Network (WISN) with a scheduling of image sensor nodes activity based on the application criticality level. This approach allows sentry nodes capable of detecting intrusions with a higher probability and alerting neighbor nodes as well as activating one of its cover sets for disambiguation purposes for instance. In this paper, we propose a multi-criteria approach to select the suitable cover set for reliable transmission of images in mission-critical applications. The proposed approach takes into account cover set size and energy, topology and routing information that affect the image quality at the sink in a multi-hop transmission network. The results show that our proposal provides low packet loss probability, low latency, and higher visual quality of received images at the Sink.