Massive capacity demand is a major impetus behind the advances, in various ways, of today and near future wireless communication networks. To face this challenge, more wireless spectrum is needed, efficient usage of this spectrum is necessary, and adequate architectures are required. In this paper, we present a conceptual solution based on a cognitive-radio-inspired cellular network, for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. We describe the conceptual architecture of this integrating network, referred to as Integrating cognitive-radio-inspired cellular network (I-CRICNet), and present a cooperative spectrum-harvesting scheme that keeps the former supplied with spectrum resources. In the latter scheme, we make extensive use of cross-correlated sequences (CSSs), for events signaling purposes. This choice is motived by the particularly interesting characteristics of the CSSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

Reliable data transport is an essential requirement for many multimedia applications in wireless sensor networks. Actually, an efficient transport protocol for these applications must take into account not only reliability and energy consumption factors but also memory occupancy and data delivery delay. Recently, many research works have been conducted in this area, however the proposed protocols treat some of these aspects and neglect others. Contrarily, in this paper we present a novel transport solution designed to provide 100% reliability without making light of other factors. Through different mechanisms, we attempt to reach this objective with congestion avoidance and good performances in terms of energy consumption, delivery delay, and memory storage. The proposed protocol, called congestion avoidance with reliable transmission and energy efficiency (CARTEE), attains these goals through several mechanisms, namely: fixed sliding window transmission, alternative implicit/explicit acknowledgement, a new congestion detection technique, and distributed transmission rate adjustment. To evaluate the proposed protocol, we have conducted simulations using ns-3. The obtained results confirm the efficiency and scalability of CARTEE and demonstrate that it outperforms the recent proposed transport protocols in terms of reliability, congestion avoidance, data cache occupancy, and latency.

The interest shown by some community of researchers to autonomous drones or UAVs (unmanned aerial vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we proposed a flocking-based routing protocol for UAVs called BR-AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. Moreover, an automatic ground base stations discovery mechanism has been introduced for a proactive drones and ground networks association needed for the context of real-time applications. The performance of BR-AODV was evaluated and compared with that of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

Examines the market for wireless sensor networks in the era and expansion of the Internet of Things. Over the past decade, the fast expansion of the Internet of Things (IoT) paradigm and wireless communication technologies has raised many scientific and engineering challenges that call for ingenious research efforts from both academia and industry. The IoT paradigm now covers several technologies beyond RFID and wireless sensor networks (WSNs). In fact, the number of potential application fields has already exceeded expectations. According to Cisco IBSG, more than 50 billion devices are expected to be connected to the Internet by 2020, with around 20 percent from the industry sector. Therefore, integrating the IoT concept and industrial WSNs (IWSNs) is an attractive choice for industrial processes, which may optimize operational efficiency, automation, maintenance, and rationalization. Moreover, IoT ensures large-scale interconnection between machines, computers, and people, enabling intelligent industrial operations. This emergent technological evolution has led to what has become the Industrial IoT (IIoT). IIoT will bring promising opportunities, along with new challenges.

The emergence of new data handling technologies and analytics enabled the organization of big data in processes as an innovative aspect in wireless sensor networks (WSNs). Big data paradigm, combined with WSN technology, involves new challenges that are necessary to resolve in parallel. Data aggregation is a rapidly emerging research area. It represents one of the processing challenges of big sensor networks. This paper introduces the big data paradigm, its main dimensions that represent one of the most challenging concepts, and its principle analytic tools which are more and more introduced in the WSNs technology. The paper also presents the big data challenges that must be overcome to efficiently manipulate the voluminous data, and proposes a new classification of these challenges based on the necessities and the challenges of WSNs. As the big data aggregation challenge represents the center of our interest, this paper surveys its proposed strategies in WSNs.

Motion detection is a live issue. Moving objects are an important clue for smart video surveillance systems. In this work we try to detect the motion in video surveillance systems. The aim of our work is to propose solutions for the automatic detection of moving objects in real time with a surveillance camera. We are interested by objects that have some geometric shape (circle, ellipse, square, and rectangle). Proposed approaches are based on background subtraction and edge detection. Proposed algorithms mainly consist of three steps: edge detection, extracting objects with some geometric shapes and motion detection of extracted objects.

Over the last few years, different traffic sign recognition systems were proposed. The present paper introduces an overview of some recent and efficient methods in the traffic sign detection and classification. Indeed, the main goal of detection methods is localizing regions of interest containing traffic sign, and we divide detection methods into three main categories: color-based (classified according to the color space), shape-based, and learning-based methods (including deep learning). In addition, we also divide classification methods into two categories: learning methods based on hand-crafted features (HOG, LBP, SIFT, SURF, BRISK) and deep learning methods. For easy reference, the different detection and classification methods are summarized in tables along with the different datasets. Furthermore, future research directions and recommendations are given in order to boost TSR’s performance.

Over the past few years, multicore systems have become increasingly powerful and thereby very useful in high-performance computing. However, many applications, such as some linear algebra algorithms, still cannot take full advantage of these systems. This is mainly due to the shortage of optimization techniques dealing with irregular control structures. In particular, the well-known polyhedral model fails to optimize loop nests whose bounds and/or array references are not affine functions. This is more likely to occur when handling sparse matrices in their packed formats. In this article, we propose using 2d-packed layouts and simple affine transformations to enable optimization of triangular and banded matrix operations. The benefit of our proposal is shown through an experimental study over a set of linear algebra benchmarks.

Wireless capsule endoscopy (WCE) has several benefits over traditional endoscopy such as its portability and ease of usage, particularly for remote internet of things (IoT)-assisted healthcare services. During the WCE procedure, a significant amount of redundant video data is generated, the transmission of which to healthcare centers and gastroenterologists securely for analysis is challenging as well as wastage of several resources including energy, memory, computation, and bandwidth. In addition to this, it is inherently difficult and time consuming for gastroenterologists to analyze this huge volume of gastrointestinal video data for desired contents. To surmount these issues, we propose a secure video summarization framework for outdoor patients going through WCE procedure. In the proposed system, keyframes are extracted using a light-weighted video summarization scheme, making it more suitable for WCE. Next, a cryptosystem is presented for security of extracted keyframes based on 2D Zaslavsky chaotic map. Experimental results validate the performance of the proposed cryptosystem in terms of robustness and high-level security compared to other recent image encryption schemes during dissemination of important keyframes to healthcare centers and gastroenterologists for personalized WCE.

Background: Collaborative learning is an important pedagogical strategy which gained a huge interest in critical domains such as the medical field. However, to ensure the quality of this learning method, it is necessary to focus intention not only on the cognitive aspect but also on the social activities that represent an essential issue during collaborative learning sessions. Our objective in this study is to highlight the collaborative aspect in the group learning method of clinical reasoning.

Methods: In this work, we have focused on cognitive studies that are interested in the clinical reasoning processes, while proposing a model dedicated to the design of collaborative clinical reasoning learning environment in synchronous mode. This model is primarily interested in social activities that have a strong influence on the collaborative learning effectiveness, and they are generally treated implicitly by basing on the improvisation and spontaneity of the learners group.

Results: The research idea was embodied through a collaborative learning clinical reasoning environment based on Web 2.0 technologies. We chose this technology to benefit from its ease of use and from its technical performances that can significantly contribute to the development of the cognitive and social aspects in the collaborative learning environment.

Conclusion: Our first contact with medical students showed us that they are appreciating this learning method. Indeed, to evaluate objectively our choices reliability, we plan to accomplish this research with a quantitative study based on real experiences with clinicians and medical students. The suggested study will allow us to collect the necessary lessons to work in depth on the relevant questions concerning the cognitive and social activities in the collaborative clinical reasoning learning.

Mobility has always represented a complicated phenomenon in the network routing process. This complexity is mainly facilitated in the way that ensures reliable connections for efficient orientation of data. Many years ago, different studies were initiated basing on routing protocols dedicated to static environments in order to adapt them to the mobile environment. In the present work, we have a different vision of mobility that has many advantages due to its 'mobile' principle. Indeed, instead of searching to prevent mobility and testing for example to immobilize momentarily a mobile environment to provide routing task, we will exploit this mobility to improve routing. Based on that, we carried out a set of works to achieve this objective. For our first contribution, we found that the best way to make use of this mobility is to follow a mobility model. Many models have been proposed in the literature and employed as a data source in most studies. After a careful study, we focused on the Random Waypoint mobility model (RWP) in order to ensure routing in wireless networks. Our contribution involves a Random Waypoint model (in its basic version) that was achieved on the TOSSIM simulator, and it was considered as a platform for our second (and main) contribution, in which we suggested an approach based RWP where network nodes can collaborate and work together basing on our recommended algorithm. Such an approach offers many advantages to ensure routing in a dynamic environment. Finally, our contributions comprise innovative ideas for suggesting other solutions that will improve them.

Recently, multimedia streaming applications are deployed anywhere (homes, campuses, etc.). Delivering these applications over mobile ad hoc networks is a challenging task: first, mobile ad hoc networks are infrastructure less, with dynamic topology, and limited resources. Secondly these applications have strict quality of service (QoS) requirements given with delay, jitter, bandwidth, loss rate, etc. Several architectures have been developed. However, an important part like QoS in routing level is still omitted. In this paper, many different coding techniques for video streaming are reviewed and two routing protocols (reactive and proactive) are used to evaluate which of them can improve QoS for multimedia streaming applications. Results show that reactive protocol performs better than proactive protocol in terms of throughput and network load in high mobility, but roles are reversed in terms of loss rate and network load for large-scale networks. PNSR and Jitter are influenced by nodes numbers independently of used protocol.

Ensuring (QoS) in wireless sensor networks (WSNs) is a challenging issue due to the lack of resources and energy exhausting of sensor nodes. In this paper we propose a new QoS aware routing protocol for multi-hop wireless sensor networks based on cross-layer interaction between the network, MAC and physical layers. At physical layer, a link quality estimator is studied for the purpose of evaluating link quality. At MAC layer, a differentiated services mechanism is used to distinguish between real time and non-real time packets and to allocate more channel resources for real time traffic; TDMA slots also have been modified to allocate more and earlier slots to real time packets. At network layer, a routing path selection algorithm is introduced for QoS optimisation. Simulation results show that our proposed protocol improves network's performances in terms of energy efficiency and QoS.

The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet).

Many self-adaptation routing schemes have been proposed for sensor networks. The most relevant of them consider a hierarchical topology and aim to meet energy conservation and QoS requirements in a homogeneous environment. In such networks, one specific algorithm is commonly applied by all nodes inside clusters. Contrarily, in this paper, we propose a heterogeneous routing by applying different strategies according to specific parameters at the same time inside different clusters. Moreover, each cluster can adopt different strategies at different moments under different conditions. This approach leads to a new self-adaptation protocol based on heterogeneity of the routing process in a multi-hop clustering WSN. The proposal uses a set of mechanisms that have been adopted in well-known protocols (HEEP, APTEEN, LEACH, PEGASIS, etc.) taking into account their strengths and weaknesses. Simulations under NS2 show that our proposal, based on heterogeneous routing protocol, prolongs the network lifetime with different ratios compared to HEEP, PEGASIS and others.

Providing quality of service (QoS) for real-time multimedia applications such as video streaming in mobile ad hoc networks (MANETs) is an important challenge. MANETs are characterized by lack of fixed infrastructure, dynamic topology, and limited resources that make more difficult multimedia applications transport and run on this networks. To overcome this challenge, video coding techniques combined to multiple routing paths (multipath) is a promising technique for supporting transmission of multiple video streams with appropriate QoS over mobile ad hoc networks. In this paper, firstly, many issues and different techniques for video streaming over MANET have been reviewed and secondly two multi paths routing protocols (M-AODV and MDSDV) have been evaluated in order to improve QoS for real-time multimedia applications. Results show that none of these two protocols is better than the other. In certain situations (throughput and load network with high mobility) is M-AODV but in others (network load and reliability for large-scale network) is MDSDV protocol which displays good performance. It is also noted that these two protocols provide between acceptable and good quality and a small jitter regardless of nodes number in medium mobility.

In wireless sensor networks, one of the most important constraints is the low power consumption requirement. For that reason, several hierarchical or cluster-based routing methods have been proposed to provide an efficient way to save energy during communication. However, their main challenge is to have efficient mechanisms to achieve the trade-off between increasing the network lifetime and accomplishing acceptable transmission latency. In this paper, we propose a novel protocol for cluster-based wireless sensor networks called PEAL (Power Efficient and Adaptive Latency). Our simulation results show that PEAL can extend the network lifetime about 47% compared to the classic protocol LEACH (Low-Energy Adaptive Clustering Hierarchy) and introduces an acceptable transmission latency compared to the energy conservation gain.

This work is located in the domain of distributed information retrieval (DIR). A simplified view of the DIR requires a multi-search in a set of collections, which forces the system to analyze results found in these collections, and merge results back before sending them to the user in a single list. Our work is to find a fusion method based on the relevance score of each result received from collections and the relevance of the local search engine of each collection, which is the main issue of our work.

Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

This paper proposes a semi-structured information retrieval model based on a new method for calculation of similarity. We have developed CASISS (Calculation of Similarity of Semi-Structured documents) method to quantify how two given texts are similar. This new method identifies elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of descriptors for each element, which characterize the contents of elements.It can be used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document but also the topology (position continuity) of these terms.