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This volume offers the proceedings of the 2nd UNet conference, held in Casablanca May 30 - June 1, 2016. It presents new trends and findings in hot topics related to ubiquitous computing/networking, covered in three tracks and three special sessions:

Main Track 1: Context-Awareness and Autonomy Paradigms Track
Main Track 2: Mobile Edge Networking and Virtualization Track
Main Track 3: Enablers, Challenges and Applications
Special Session 1: Smart Cities and Urban Informatics for Sustainable Development
Special Session 2: Unmanned Aerial Vehicles From Theory to Applications
Special Session 3: From Data to Knowledge: Big Data applications and solutions



Main Track 1: Context-Awareness and Autonomy Paradigms


The Allocation in Cognitive Radio Network: Combined Genetic Algorithm and ON/OFF Primary User Activity Models

Cognitive radio (CR) has appeared as a promising solution to the problem of spectrum underutilization. Cognitive radio user (CU) is an intelligent equipment who scent the spectrum which is licensed to primary radio users (PUs) when it is idle and use it with other CUs for their communication. Thus by modeling PUs activity, CUs can predict the future state ON or OFF (busy or idle) of PUs by learning from the history of their spectrum utilization. In this manner, CUs can select the best available spectrum bands. On this point, many PU ON/OFF activity models have been proposed in the literature. Among this models, Continuous Time Markov chain, Discrete Time Markov chain, Bernoulli and Exponential models. In this paper, we firstly compare these four models in term of better numbers of OFF slots to deduce which model give best performance of available resources. Then, the activity history patterns generated from each model are combined with the genetic algorithm as sensing vectors to select the best available channel in terms of quality and least PU arrivals.

Yasmina El Morabit, Fatiha Mrabti, El Houssein Abarkan

An Optimized Vertical Handover Approach Based on M-ANP and TOPSIS in Heterogeneous Wireless Networks

Due to a deployment of different networks technologies such as 3G (UMTS, IEEE 802.11), 4G (LTE, IEEE 802.16) and 5G, the users have the opportunity to be connected to Internet at any time and any where. This ability to be quickly and easily connected is ensured by using the intelligent mobile terminal multi-modes such as mobile phones, smart-phones, IPAD, etc. These equipments mobiles have enabled users also to handle simultaneously various applications by using different access networks. The most issue in this heterogeneous wireless network is enabling for users to continuously choose the most appropriate access network during their communication. To deal with this task, we propose a new approach for network selection based on two multi attribute decision making (MADM) methods namely multiple analytic network process (M-ANP) and technique for order preference by similarity to ideal solution (TOPSIS) method. The M-ANP is used to weigh each criterion and TOPSIS is applied to rank the alternatives. The simulation results illustrate the effectiveness of our optimized approach in terms of reducing of the reversal phenomenon and the ping-pong phenomenon.

Mohamed Lahby, Abdelbaki Attioui, Abderrahim Sekkaki

Performance Analysis of Routing Protocols in Vehicular Ad Hoc Network

Vehicular Ad Hoc Network (VANET) networks are very likely to be deployed in the coming years and thus become the most relevant form of mobile ad hoc networks. They provide wireless communication among vehicles and vehicle-to-road side equipment. The communication between vehicles is used for safety, comfort and for entertainment as well. The performance of communication depends on how better the routing takes place in the network. Routing of data depends on the routing protocols being used in network. In this article, we investigated different routing protocols for VANET. The main aim of our study was to identify which routing method has better performance in highly mobile environment of VANET.

Bouchra Marzak, Hicham Toumi, Elhabib Benlahmar, Mohamed Talea

A Message Removal Mechanism for Delay Tolerant Networks

The dissemination of redundant copies of a message is one of the techniques used in Delay/Disruption Tolerant Networks (DTN) to improve the delivery rate and to decrease the incurred delay. Nevertheless, many of these copies remain in the buffer of intermediate nodes even after the message is delivered to the destination. In this paper, we propose mechanism to remove obsolete messages for DTN routing protocols. Furthermore, we compare its performance with other state-of-art techniques under two different realistic scenarios and using two datasets of human mobility traces. Through the obtained results, we observed a better performance of the tested DTN routing protocols in most scenarios in terms of delivery ratio and overhead messages, when compared to others related works.

Elenilson da Nóbrega Gomes, Carlos Alberto V. Campos, Sidney C. de Lucena, Aline Carneiro Viana

A Context-Aware Access Network Selection Based on Utility-Function for Handover in WLAN-LTE Environment

Network selection plays an essential role in serving mobile users with the requisite Quality of Service (QoS) in the context of next generation networks (NGN). It boosts efficiently the use of radio resources in heterogeneous wireless networks environment. In order to be Always Best Connected in such environment that involve multiple networks with different access technologies, user’s preferences and QoS requirements need to be considered during the Vertical Handover process. To address this issue, this paper proposes a context-aware access network selection based on utility-function that takes into consideration user’s and QoS preferences. It aims at maximizing the user satisfaction while meeting application QoS when connecting to a target network. The proposed approach prioritizes networks with higher relevance to different types of applications and enables seamless connectivity to mobile user and applications. Thus, network resources are conveniently managed to support diverse services that might be considered by mobile users. Simulations results are provided to evaluate the performance of the proposed approach in low, medium and high mobility scenarios consisting in WLAN-LTE networks compared with the existing baseline scheme.

Maroua Drissi, Mohammed Oumsis, Driss Aboutajdine

Study of the Impact of Designed Objective Function on the RPL-Based Routing Protocol

The routing over Low Power and Lossy network working group (ROLL) has specified RPL as an IPv6 routing protocol for Low Power and Lossy networks. RPL builds a Destination Oriented Directed Acyclic Graph (DODAG) based on a set of metrics and constraints trough a specific Objective Functions (OFs). This OF can specify the selection of the parent and the construction of the route. In this paper, the performances of RPL are analyzed based on two main objective functions: Minimum Rank with Hysteresis Objective Function (MRHOF) that uses number of expected transmission (ETX) as a condition to select the routes and the Objective Function Zero (OF0) based on the Minimum Hop Count to determine the best parent. The analysis of RPL performances with the two comparative Objective Function is made with different metrics such as ETX, Hop Count, lost packet, energy, and control traffic overhead. This comparison makes it possible to distinguish which objective function is the most optimal to guarantee good functioning of RPL especially in mobile environment and which one respond better to the requirements of its application.

Hanane Lamaazi, Nabil Benamar, Antonio J. Jara

Multi-channel Coordination Based MAC Protocols in Vehicular Ad Hoc Networks (VANETs): A Survey

Multi-channel communications protocols in Vehicular Ad Hoc Networks (VANETs) is a very important topic that has been attracting the research community in the last decade. These communication protocols are based on the latest standard draft IEEE 802.11p and IEEE 1609.4, in which the channel is divided into multiple channels (i.e., control channel (CCH) and service channels (SCHs)) in order to improve open public road safety services, comfort and efficiency of driving. There are several survey papers that present and compare the Multi-channel communication protocols from various perspectives, but a survey on Multi-channel coordination based MAC protocols in Vehicular Ad Hoc Networks (VANETs) is still missing. In this work, we provide a comparative study of the existing literature on multi-channel coordination based MAC protocols in vehicular Ad Hoc Networks. We first define suitable criteria to classify existing solutions, and then describe them by separately addressing a set of protocols in order to compare them. We conclude the paper by addressing some open issues that need to be tackled in future studies.

Mina Ouyous, Ouadoudi Zytoune, Driss Aboutajdine

Towards the Enhancement of QoS in 802.11e for Ad Hoc Networks

Multimedia applications running over Ad hoc networks must achieve some level of performance QoS guarantees. This topic is very broad and there is an extensive pool of solutions in the literature. For the last few years, works on enhancing Quality of service at MAC layer in wireless networks, have attracted tremendous research efforts. In this paper, we examine the QoS issue of MAC layer in Ad hoc networks. We present a state-of-the-art review and a comparison of typical enhancements of distributed versions of both 802.11 and 802.11e standards, designed first to work in infrastructure wireless networks. We start our work by highlighting problems of deploying the original algorithms in a distributed architecture such as MANETs. Then, we propose an enhancement of the 802.11e in order to improve the QoS and correct the reactivity of this standard when network conditions become highly disturbed.

Fatima Lakrami, Mohamed El-Kamili, Najib Elkamoun

DTN Network: Optimal Cluster Head in DTN Routing Hierarchical Topology (DRHT)

In this paper, we study the problem of data routing with an optimal delay in the bundle layer, by exploiting : the clustering, the messages ferries and the optimal election of cluster head (CH). We first introduce the DTN routing hierarchical topology (DRHT) which incorporates these four factors into the routing metric. We propose an optimal approach to elect a CH based on four criteria : the residual energy, the intra-cluster distance, the node degree and the head count of probable CHs. We proceed then to model a Markov decision process (MDP) to decide the optimal moment for sending data in order to ensure a higher delivery rate within a reasonable delay. At the end, we present the simulation results demonstrating the effectiveness of the DRHT. Our simulation shows that while using the DRHT which is based on the optimal election of CH, the traffic control during the TTL interval (Time To Live) is balanced, which greatly increases the delivery rate of bundles and decreases the loss rate.

El Arbi Abdellaoui Alaoui, Said Agoujil, Moha Hajar, Youssef Qaraai

Implementation of Bit Error Rate Model of 16-QAM in Aqua-Sim Simulator for Underwater Sensor Networks

Aqua-Sim is a simulator built on top of NS-S, is designed for Underwater Sensor Networks(UWSNs). It can be used to simulate acoustic attenuation signal and packet collision in UWSNs. Aqua-Sim supports three-dimensional deployment that doesn’t exist in the simulators developed for terrestrial wireless networks. Although this simulator doesn’t consider any signal modulation scheme. In this paper, we introduce the Bite Error Rate(BER) model of 16-QAM modulation scheme in Aqua-Sim. Also we consider the ambient noise resulting from different environmental noise sources such as turbulence, shipping, waves and thermal noise in 16-QAM BER formula. The consideration of such BER model instead of random bit error improve the reliability of routing protocols simulated in Aqua-Sim. That is shown in this paper through the simulations of Vector Based Void Avoidance routing protocol (VBF).

Mohammed Jouhari, Khalil Ibrahimi, Mohammed Benattou

Energy Efficient In-Network Aggregation Algorithms in Wireless Sensor Networks: A Survey

Advancement in ubiquitous networking has led to the production of wireless sensor networks, consisting of many autonomous small devices called sensor nodes, able to observe and report various real world physical phenomena with no wired infrastructure. Onetheless, this feature precisely makes these nodes energy constrained, since most of the energy is consumed in data communication. In-network processing may be regarded as an efficient technique that reduces the amount of data to be transmitted in the network. We focus on data aggregation algorithms, whose fundamental idea is to gather, combine and compress data from different sources by applying simple functions in order to reduce the traffic load, thus enhancing the network’s lifetime. However, it is difficult for developers to identify data aggregation algorithms strengths and weaknesses, nor to pinpoint current open research issues to be investigated. In this paper, we propose a survey of the most energy efficient data aggregation algorithms. After reviewing over 900 papers from which we selected 15 algorithms based on the energy efficiency criteria, we classify these protocols according to the network topology, then we describe each one in order to compare them. We conclude the paper with possible future research directions for aspiring researchers and algorithm developers.

Hafsa Ennajari, Yann Ben Maissa, Salma Mouline

Towards an Autonomic Approach for Software Defined Networks: An Overview

Under the new paradigm Software Defined Networking (SDN), which involves decoupling control plane from data plane, and allowing control planes to be deployed on external servers, our main goal is to propose an overview of architecture that can effectively solve problems of network QoS caused by this separation. The overall objective is to study and evaluate the use of SDN networks as a cornerstone of a communication system that can effectively support distributed applications whose needs change over time. In this paper, we focus, in particular, on the controller placement problem in SDN, optimizing the latency, resilience, reliability, scalability and other network performance. The technical solutions to these problems will be studied to identify the components of SDN that can be improved.

Soukaina Bouzghiba, Hamza Dahmouni, Anouar Rachdi , Jean-Marie Garcia

Privacy Preservation in the Internet of Things

The Internet of Things (IoT) is the future of Internet where users, machines and everyday Things have the ability to sense, communicate and interact with their environment. IoT promises a wide variety of applications to make the human’s life more comfortable, safe and improve quality of life. It’s also considered as big business opportunity for enterprises based on huge quantity of data gathered by connected Things. In the IoT applications such as smart home, smart city, heath and so on, Things cohabit with humans and deal with their personal data even the most private ones. When this data is collected massively and exposed to Internet without an explicit person’s agreement, Things constitute by this way a threat for privacy, which is a universal human right. Thus privacy preservation is one of the most prominent issues in IoT. This paper analyzes the privacy in the context of IoT based on case study, and proposes mechanisms to improve security and preserve privacy. This analysis considers also the economic advantages related to the use of IoT as new business opportunity without personal private data disclosure. The proposed solutions are based on data anonymity technologies with recommendation for users and for developers of IoT application.

Fatima Zahra Berrehili, Abdelhamid Belmekki

Packet Delay Analysis in Wireless Sensor Networks Using Fountain Code Enabled-DCF

Many applications currently exploit wireless sensor networks for long term data gathering, ranging from environmental sensing, etc., and many more are under development. This paper introduces an analytical model to investigate the delay analysis for the Fountain-Code-Enabled–Distribution Coordination Function (FCE-DCF) for the IEEE 802.11 protocol in the Wireless Sensor Networks (WSN). The state transition of buffering queue data in node is described by a two-dimensional Markov chain model. The delay is developed by extending the throughput analysis introduced by our model. This study is validate by comparison with the result obtained by Bianchi’s model. The packet delay analysis results present as a function of a number of station, packet size and the effects of contention windows are obtained using DCF for asynchronous packets transmission with four-way handshaking technique.

Rachid Aouami, Mohamed Hanaoui, Mounir Rifi, Mohammed Ouzzif

Main Track 2: Mobile Edge Networking and Virtualization


Cost-Precision Tradeoffs in 3D Air Pollution Mapping Using WSN

Air pollution has become a major issue of modern megalopolis, where the majority of world population lives. Measuring air pollution levels is an important step in designing and assessing air quality related public policies. Unfortunately, existing solutions are inadequate to get insights on the real exposition of citizens. In particular, high quality sensors deployed today are too large and too costly to envision a three dimensional deployment at the scale of a street. In this paper, we investigate the deployment of wireless sensor networks (WSN) used for building a three-dimensional mapping of pollution concentrations. We consider in our simulations a 3D model of air pollution dispersion based on real experiments performed in wind tunnels emulating the pollution emitted by a steady state traffic flow in a typical street canyon. Our contribution is to analyze the performances of different 3D WSN topologies in terms of the trade-off between the economical cost of the infrastructure and the quality of the reconstructed air pollution mapping.

Ahmed Boubrima, Walid Bechkit, Hervé Rivano, Lionel Soulhac

A Novel Architecture with Dynamic Queues Based on Fuzzy Logic and Particle Swarm Optimization Algorithm for Task Scheduling in Cloud Computing

Cloud computing is an emerging high performance computing paradigm for managing and delivering services using a large collection of heterogeneous autonomous systems with flexible computational architecture. Task scheduling is one of the most challenging aspects to improve the overall performance of the cloud computing such as response time, cost, makespan, throughput etc. Task scheduling is also essential to reduce power consumption, processing time and improve the profit of service providers by decreasing operating costs and improving the system reliability. This paper focuses on Task Scheduling using a novel architecture with Dynamic Queues based on hybrid algorithm using Fuzzy Logic and Particle Swarm Optimization algorithm (TSDQ-FLPSO) to optimize makespan and waiting time. The experimental result based on an open source simulator (CloudSim) show that the proposed TSDQ-FLPSO provides an optimal balance results, minimizing the waiting time, reducing the makespan and improving the resource utilization compared to existing scheduling algorithms.

Hicham Ben Alla, Said Ben Alla, Abdellah Ezzati, Ahmed Mouhsen

A Vehicular Cloud for Secure and QoS Aware Service Provision

The Vehicular Cloud (V-Cloud) is a new technology that will have impact on traffic management and road safety. It enables the release of various reliable and low cost services, including on board advertisement, multimedia, and traffic management. This paper presents a secure and QoS aware three-layer Vehicular Cloud architecture enabling a tree-based connection of vehicles to the network. We propose a certificate based authentication and privacy preservation protocol for secure vehicular communication. The proposed protocol allows generating and using public key certificate with zone based temporal vehicles identities to prevent Sybil and Tracking attacks.

Mouna Garai, Slim Rekhis, Noureddine Boudriga

A Conceptual Architecture for a Cloud-Based Context-Aware Service Composition

In today’s ubiquitous environments, more and more companies use cloud computing services to achieve their everyday operations and processes. However, the development of these services is a tedious and time consuming task. Moreover, existing solutions rarely take into account the personalization and the adaptation of services to the context of their use. In this paper, we propose an architecture for context-aware service composition in cloud environments to address the challenges mentioned above. The architecture takes advantage of service composition as a way to create new composite services from a set of atomic or composite ones, causing the reduction of development efforts and time to market, and also, the introduction of context-awareness to manage the dynamics of ubiquitous environments.

Soufiane Faieq, Rajaa Saidi, Hamid Elghazi, Moulay Driss Rahmani

Knowledge Flows Within Open Source Software Projects: A Social Network Perspective

Developing software is knowledge-intensive activity, requiring extensive technical knowledge and awareness. The abstract part of development is the social interactions that drive knowledge flows between contributors, especially for Open Source Software (OSS). This study investigated knowledge sharing and propagation from social perspective using social network analysis (SNA). We mined and analyzed the issue and review histories of three OSS from GitHub. Particular attention has been paid to the socio-interactions through comments from contributors on reviews. We aim at explaining the propagation and density of knowledge flows within contributor networks. The results show that review requests flow from the core contributors toward peripheral contributors and comments on reviews are in a continuous loop from the core teams to the peripherals and back; and the core contributors leverage on their awareness and technical knowledge to increase their notoriety by playing the role of communication brokers supported by comments on work items.

Noureddine Kerzazi, Ikram El Asri

A Pub-Sub Based Architecture for IDS as Service

Cloud services have become increasingly popular and massively deployed over the past years. However, providing security as cloud service, accessible from outside the cloud, remains one of the most challenging research problems in this topic. The main problem comes from the fact that it is hard to maintain scalability with client growth while ensuring an efficient intrusion detection requests management inside cloud services. In this paper, we propose the use of Pub-Sub communication mechanism to provide a highly available and distributed IDS cloud service. Our aim is to reduce intrusion detection time and increase accuracy by specializing IDS nodes according to various taxonomies based attack categories. Our cloud IDS service is available from outside via web service interfaces, and is appropriate for limited-capacity devices such as smartphones or tablets.

Maïssa Mbaye, Cheikh Ba

Towards a Service Broker for Telecom Service Provision and Negociation in IMS Network

The world of telecommunications is undergoing a rapid change in designing and developing applications. Telecom operators are becoming increasingly forced to diversify the portfolio of available services to ensure customer loyalty. Indeed the operator’s business has far exceeded the supply of traditional telephony to open up to the most demanding services. For this purpose IP Multimedia Subsystem (IMS) has been a major work effort of the 3GPP (3rd Generation Partnership Project) standards bodies for several years now. However, the acquisition of services by operators slows down the development of services offered because of the integration difficulties, and the negotiation issues. In this paper we propose a new negotiation approach. The idea is to set up a Service Broker able to look for the best offer of the service and execute the Service Level Agreement (SLA) between Service Provider, network operator, and customer. To ensure a transparent communication at all levels, the NGOSS (New Generation Operations Systems and Software) Framework is used in a consistent manner.

Imane Haddar, Brahim Raouyane, Mostafa Bellafkih

A New Approach for Modeling Strategic IT Governance Workflow

In this article we propose a new approach to govern an information system (IS) through The Control Objectives for Information and related Technology Business (COBIT) in an intelligent way. The purpose of this approach is monitoring IS good governance and enabling other frameworks to apply specific processing, if needed. In fact, Information Technologies Management (ITM) is a recent discipline aiming at guiding and controlling organization resources to achieve business goals, by relating human resources, financial resources, and technical resources to IT tools. ITM needs Information Technologies Governance (ITG) methodologies and frameworks to achieve competitive edge in the marketplace. COBIT, a base of ITG, offers a generic framework of structured IT control activities. It is designed to ensure harmonization of terms and principles to facilitate its integration with other frameworks. To benefit from this generic aspect, we propose an IT Governance kernel based on COBIT with an intelligent learning layer for Enterprise knowledge. We appealed to the Loose Inter-Organizational Workflow to address the constraints of heterogeneity and difference between IS components. We use both the multi-agent technology to insure the issues of autonomy, cooperation and coordination and the semantic web to understand business stakeholders’ languages to express their needs. An implementation of this solution was done in J2EE technology to ensure its performance.

Meriem Chergui, Aziza Chakir, Hicham Medromi, Mostafa Radoui

Decentralized Control of Substations in Smart Cities

The role of smart electric substation in smart cities becomes more important compared with the traditional one. Some benefits of smart substation and the concept of a decentralized control with an example of simulation are presented in this paper.

Mohamed Nouh Dazahra, Faycel Elmariami, Aziz Belfqih, Jamal Boukhrouaa, Lakbich Anass, Cherkaoui Nazha

Main Track 3: Enablers, Challenges and Applications


Comparative Analysis of Different Excitation Techniques for Cylindrical Dielectric Resonator Antenna

Direct Microstrip line, Microstrip slot-coupled feed and hybrid coupler techniques are investigated for Cylindrical Dielectric Resonator Antenna (CDRA). The Dielectric resonator has a dielectric constant of 30, and etched on Arlan dielectric substrate having a relative permittivity of 3.58 and dimensions of 150 × 150 mm2. The structures are numerically analyzed using the numerical software HFSS. Radiation characteristics including return loss, gain, directivity and VSWR versus frequency characteristic are presented and compared based on the excitation method employed for the studied CDRA. The simulation results proved that the 90° hybrid coupler provides good performances particularly: a wider impedance bandwidth of 1.15 GHz and a maximum coupling of −45 dB.

Kaoutar Allabouche, Fabien Ferrero, Najiba El Amrani El Idrissi, Mohammed Jorio, Jean Marc Ribero, Leonardo Lizzi, Abdellatif Slimani

Recognition of OFDM and SCLD Signals Based on Second-Order Statistics

This work addresses the problem of the modulation recognition signal in the context of cognitive radio. In particular, the discrimination between OFDM (Orthogonal Frequency Division Multiplexing) and SCLD (Single Carrier Linear Digitally) signals. We present a new method based on second order statistics. The main advantages of this method are fast, robust in a context of AWGN (Additive White Gaussian Noise) channel, frequency and timing offsets. Computer simulations are provided in order to illustrate the behavior of the proposed algorithm.

Mohamed Firdaoussi, Hicham Ghennioui, Mohamed El-Kamili

MDE-Based Languages for Wireless Sensor Networks Modeling: A Systematic Mapping Study

Wireless Sensor Networks (WSNs) are ubiquitous systems of small devices equipped with sensors that collaborate to sense physical quantities in an area. However, the design constraints, the behavior requirements and the error prone nature, make the development of WSNs and their deployment an extremely challenging task. The Model Driven Engineering (MDE) approach helps tackling these issues by using models and automatic transformation to generate code or analyze WSNs against their requirements. In this paper, we propose a systematic mapping study which presents the existing WSNs MDE-based modeling languages. We surveyed a total of 1852 papers from which we selected 21 languages satisfying 7 selection criteria. We analyze these languages according to 5 rigorous research questions and 12 comparative criteria. Then we provide a precise view on the existing languages and their weaknesses mainly regarding mobility and data fusion. Finally, we propose research directions and recommendations for aspiring languages developers.

Fatima Essaadi, Yann Ben Maissa, Mohammed Dahchour

Multi-homing as an Enabler for 5G Networks: Survey and Open Challenges

Driven by the unprecedented growth in the number of connected devices and mobile data traffic, 5G wireless network is expected to afford a full scale Internet of Things. Various wireless access networks will continue to coexist; one concept is allowing a device to virtually and simultaneously be connected to other devices using all available network resources at its location which is multi-homing. In this paper, we draw an overall picture of multi-homing based solution for provisioning Quality of Service and Quality of Experience taking into consideration the economics issues and the challenging problems that must be solved in the future.

Salma Ibnalfakih, Essaïd Sabir, Mohammed Sadik

Fast Algorithm for 3D Local Feature Extraction Using Hahn and Charlier Moments

In this paper, we propose a fast algorithm to extract 3D local features from an object by using Hahn and Charlier moments. These moments have the property to compute local descriptors from a region of interest in an image. This can be realized by varying parameters of Hahn and Charlier polynomials. An algorithm based on matrix multiplication is used to speed up the computational time of 3D moments. The experiment results have illustrated the ability of Hahn and Charlier moments to extract the features from any region of 3D object. However, we have observed the superiority of Hahn moments in terms of reconstruction accuracy. In addition, the proposed algorithm produces a drastic reduction in the computational time as compared with straightforward method.

Abderrahim Mesbah, Aissam Berrahou, Mostafa El Mallahi, Hassan Qjidaa

Automatic Detection of Suspicious Lesions in Digital X-ray Mammograms

Mammography remains the most effective tool for the early detection of breast cancer, as well as the systems of computer-aided detection/diagnosis (CAD) is typically used as a second opinion by the radiologists. So, the main goal of our method is to introduce a new approach for automatic detecting the suspicious lesions in mammograms (regions of interest) for early diagnosis of breast cancer. This study has two phases: The first one is the preprocessing step and the second one is the detection of Regions of Interest (ROIs). Our method has tested with the well-known Mammography Image Analysis Society (MIAS) database and we’ve used Free-Receiver Operating Characteristics (FROC) to measure methods performance. The obtained experimental results show that our algorithm’s performance has sensitivity of 94.75 % at 0.54 false positive per image.

Abdelali Elmoufidi, Khalid El Fahssi, Said Jai-Andaloussi, Abderrahim Sekkaki, Gwenole Quellec, Mathieu Lamard, Guy Cazuguel

Smart Antenna System Using Butler Matrix Based Beamforming Network for X Band Applications

This paper presents the optimum design of a 4 × 4 planar Butler matrix array as a key component of a switched beam smart antenna system operating at 10 GHz for X band applications. In 4 × 4 Butler matrix, four input ports are used for the input signal connections and four output ports can be connected to an array of four micro-strip edge feed patch antennas to form the beamforming network. Such a network is capable of production of four orthogonal uniform beams (at −50°, −10°, 10° and 50°) with effective coverage over 120°, when feed with electromagnetic signals. Conception details, and simulation results are also given for the components (hybrid coupler, crossover, phase shifter) used to implement the matrix. Finally, the simulation results using Ansoft HFSS show a great improvement of Gain and HPBW of the four generated orthogonal beams.

Hayat Errifi, Abdennaceur Baghdad, Abdelmajid Badri, Aicha Sahel

Comparative Study of Radiation Performance Between Two Ultra Wide Band Planar Patch Array Antennas for Weather Radar Applications in C-Band

This paper presents a comparative study of radiation performance between two Ultra Wide Band (UWB) microstrip planar array antennas for weather RADAR applications which operate in C band. These arrays are etched onto a FR4 printed circuit board with an overall size of $$(162 \times 100 \times 1.58)$$(162×100×1.58) mm3 and dielectric constant $$\upvarepsilon_{\text{r}} = 4.4$$εr=4.4. The proposed arrays antennas are composed of a twenty radiating patch element with a T-junction power divider which has a role to divide the power equally to all antenna elements above a partial ground plane. Simulation results show that each array antennas has its own characteristics. The results show that the use of an array antennas with rectangular radiating elements give a bandwidth which is about 118 %, gain and high directivity can exceed 12 dB and a half power beam width of 10°, which are relatively closer to those obtained in array antennas with circular radiating elements.

Abdellatif Slimani, Saad Dosse Bennani, Ali El Alami, Kaoutar Allabouche

Performance Evaluation of MB-OFDM UWB Systems Based on Optimization Algorithm for CP Decomposition

In this paper, a Canonical Polyadic (CP) tensor decomposition for Ultra WideBand (UWB) based MultiBand Orthogonal Frequency Division Multiplexing (MB-OFDM) systems is presented. Therefore, the conventional MB-OFDM, which is a multibanding technique of Ultra WideBand technology that differs in approach from the impulse Direct-Sequence (DS-UWB) is introduced. An application of the proposed Canonical Polyadic decomposition, with isolation of scaling matrix to MB-OFDM system is proposed. A simple blind receiver based on the enhanced gradient algorithm is then presented. For illustrating this application, computer simulations are provided to demonstrate the good behavior of these algorithm compared to others in the literature.

Zakaria Mohammadi, Awatif Rouijel, Rachid Saadane

CPW-Fed Dragon Fractal Antenna for UWB Applications

This paper presents six iterations of CPW-Fed Dragon fractal antenna. The results show that more the number of iterations increases more the antenna has a broadband behavior. Also, Simulation results show that the 6th iteration of CPW-Fed Dragon fractal antenna have a bandwidth of 3.03 GHz (from 3.67 to 6.6 GHz) with important radiation gains (peak gains from 2 to 5.5 dB) which makes it a suitable solution for Ultra Wide Band (UWB) Applications. All the simulations were performed in CADFEKO, a Method of Moment (MoM) based solver.

Abdelati Reha, Abdelkebir El Amri, Othmane Benhmammouch

An Efficient Method of Improving Image Retrieval Using Combined Global and Local Features

Nowadays, with the increased use of digital images it has become essential to find an efficient system for searching and indexing of images from large image collections. CBIR systems can be used for searching and retrieving different kinds of images from large databases on the bases of the visual content of the images. Currently, CBIR techniques work on combination of low level features i.e. color, shape and texture. In this paper we have designed a content based image retrieval system based on the combination of local and global features. The local features are obtained through local binary pattern (LBP) technique which is used to extract texture-based features from an image, while the global features are extracted using Angular Radial Transform (ART). To demonstrate the efficacy of this combination, experiments are conducted on Columbia Object Image Li-brary (COIL-100) and MPEG-7 shape-1 part B database. The result showed significant improvement in the retrieval accuracy when compared to the existing system.

Abderrahim Khatabi, Amal Tmiri, Ahmed Serhir

A Comparative Experimental Study of Spectral Hashing

Binary encoding methods that keep similarity in large scale data become very used for fast retrieval and effective storage. There have been many recent hashing technics that produce semantic binary codes. We are particularly interested in Spectral Hashing based methods which provide an efficient binary hash codes in a very simple way. This paper presents a comparative experimental study of Spectral Hashing to show the performance gain and the behaviour of this method on large scale Databases. In the best of our knowledge there is no experiments done on the evolution of the hamming matrix size on big data. Two large databases are used to show the limitation of Spectral Hashing and possible research tricks will be proposed.

Loubna Karbil, Imane Daoudi, Hicham Medromi

Comparison of Feeding Modes for a Rectangular Microstrip Patch Antenna for 2.45 GHz Applications

A microstrip patch antenna consists of a metal patch on a substrate on a ground plane. Different feeding modes are used such as: coaxial probe feed, microstrip line feed, proximity-coupled feed, and coplanar wave guide feed (CPW). The patch can take different shapes to meet various design requirements. The most known forms are rectangular, square, circular, hexagonal… The microstrip patch antenna is low-profile, conformable to planar and nonplanar surfaces, simple and cheap to manufacture using modern printed-circuit technology. There are many methods of analysis for the microstrip patch antennas. The most popular models are the transmission-line, cavity and full wave methods. In this paper, a microstrip patch antenna for 2.45 GHz applications is designed based on the transmission line method. The design is optimized with the Method of the Moments (frequency domain method) because it’s one of the accurate methods for wire and planar antennas. Also, the four feeding modes are simulated and compared.

Ouadiaa Barrou, Abdelkebir El Amri, Abdelati Reha

Online Signature Verification: A Survey on Authentication in Smartphones

Smart phones are advance generation of mobile phones. They enable us to access a large variety of services like data storages, voice communication, wireless connectivity etc. As the number of services increased the number of vulnerabilities and attacks has been increasing as well. There has been a corresponding rise of security solution proposed by researchers for authentication in smart phones like password, face and voice recognition, secret path and signature verification. The most popular authentication mechanism is online biometric signature verification. People adopt this mechanism due to its nature which is most fashionable, secure, trustable and difficult for unauthorized persons to breach privacy. With this work, we aim to provide a structured and broad over view of the research on signature verification process for authentication in smart phones. This paper surveys on signature verification process in smart phones, by focusing on different techniques used in signature verification process. We grouped existing approaches aimed to analyze performance and accuracy rate of different approaches adopted by signature verification process in smart phones. With this categorization, we aim to provide an easy and concise view of different approaches adopted by signature verification process in smart phones.

Waseem Akram, Munam Ali Shah

Hybrid Approach for Moving Object Detection

Moving object detection is a major step for video analysis. In this paper, we present a new approach for moving object detection. It is based on motion and edge detection technique. It makes use of the most three recent consecutive frames to detect moving area. Firstly, we compute the infimum gradient and we generate the motion saliency map. Then, we normalize both results to eliminate the parasitic elements. Finally, after applying point-by-point addition between the infimum gradient with the motion saliency map, a morphological closing operation is applied to complete the edge. The experimental results show the effectiveness of our approach for moving object detection with an accuracy rate of 92.49 %.

Bouchra Honnit, Mohamed Nabil Saidi, Ahmed Tamtaoui

The Analysis of KDD-Parameters to Develop an Intrusion Detection System Based on Neural Network

The intrusion Detection System (IDS) is designed to protect a computer or a network by detecting malicious attempts to storm the system. Therefore, it is important to develop a flexible IDS which is able to detect attacks with best performance. In recent researches, most of IDS are based on neural network and alimented by KDD data. Which means that the neural networks inputs correspond to the KDD-parameters. However, some of KDD-parameters are meaningless and can increase the detection rate. In order to optimize the IDS performance, it is primordial to exploit uniquely the most important and crucial parameters. In fact, there are three categories of KDD attributes; the basic attributes, the parameters relating to content and the time-based ones. The study carried out in this work consists on selecting the most efficient parameters in intrusion detection by demonstrating their utility and performance and neglecting the meaningless attributes. It has to be emphasized that MATLAB tool has been used to develop and put into practice the IDS in question.

Ilhame El Farissi, Sara Chadli, Mohamed Emharraf, Mohammed Saber

A CAD System for the Detection of Abnormalities in the Mammograms Using the Metaheuristic Algorithm Particle Swarm Optimization (PSO)

The discovery of a malignant mass in the breast is considered one of the most devastating and depressing health issue women can face. However an early detection can be so helpful and could bring hope to control the disease and even cure it. Nowadays In spite the fact that Digital mammograms have proven to be an efficient tool for the screening of breast cancer, an accurate detection of the abnormalities remains a challenging task for radiologists. In this paper, we propose an effective method for the detection and classification of the suspicious regions. In our proposed approach, we use Entropy thresholding for pectoral muscle removal, and we extract the region of interest (ROI) using the Metaheuristic algorithm Particle Swarm Optimization (PSO). Then we extract Shape and texture features from the abnormalities using Fourier transform and Gray Level Co-Occurrence Matrix (GLCM) respectively. The classification of the detected abnormalities is carried out through the Support Vector Machine, which classifies the segmented region into normal and abnormal based on the extracted features.

Khaoula Belhaj Soulami, Mohamed Nabil Saidi, Ahmed Tamtaoui

Texture Segmentation Based on Dual Tree Complex Wavelet Transform and Support Vector Machine

This paper presents a new approach for segmentation of the textured images that exploits properties of the dual-tree complex wavelet transform, shift invariance and six directional sub-bands at each scale, and uses a feature vector comprising of mean and standard deviation of the six directional sub-bands over a sliding window. The classification of each sliding window using Support Vector Machine (SVM) leads to a segmented image. Through experiments on a variety of synthetic images of texture data sets, we show that our algorithm yields significant performance improvements for texture segmentation, as compared with other state-of-the-art methods of feature extraction.

Amal Farress, Mohamed Nabil Saidi, Ahmed Tamtaoui

Parallel and Reconfigurable Mesh Architecture for Low and Medium Level Image Processing Applications

Image processing and especially real time image processing is a very compute intensive task. Nowadays, with the high volume of data to be processed and the increasing size of images, the development of image processing architectures is very required, but most cases of architectures are mostly limited to one single task. This work introduces a parallel Reconfigurable Mesh architecture called RMC (Reconfigurable Mesh Computer) suitable for image processing applications. This architecture provides the flexibility of a programmable architecture and performance of a dedicated circuit, geared to the efficient parallel execution of low and medium level image processing operations. These processing operations derive abstractions from the image pixels so that it can help in further decision making about image. Before describing the proposed architecture, this paper reviews the criteria to be taken into consideration to compare image processing architecture, reinforced by an illustration of some hardware image processing architectures. We also identify some performed applications on RMC, to finally conclude with our future research directions for RMC architecture.

Ihirri Soukaina, Errami Ahmed, Khaldoun Mohamed

A Survey on Segmentation Techniques of Mammogram Images

Mammogram images are important tools allowing visualization of various types of breast cancer. In fact, cancer detection refers to the extraction of region of interest ROI, which represents the tumor, in the mammogram image. In medical imaging field, Computer Aided Diagnosis systems (CAD) are used to analyze this type of images. To extract region of interest from mammograms, image segmentation methods have been wildly applied. These methods consist of partitioning the image on meaningful regions or segments easy to analyze. There are various techniques and methods of segmentation of mammogram images in the literature. In this paper, we present a survey of different approaches of segmentation that we compared theoretically in terms of advantages and drawbacks, particulary for mammogram images.

Ilhame Ait lbachir, Rachida Es-salhi, Imane Daoudi, Saida Tallal, Hicham Medromi

Special Session 1: Smart Cities and Urban Informatics for Sustainable Development


A Hybrid Machine Learning Based Low Cost Approach for Real Time Vehicle Position Estimation in a Smart City

The Global Positioning System (GPS) enhanced with low cost Dead Reckoning (DR) sensors allows to estimate in real time a vehicle position with more accuracy while maintaining a low cost. The Extended Kalman Filter (EKF) is generally used to predict the position using the sensor’s measures and the GPS position as a helper. However, the filter performance tails off during periods of GPS failure and may quickly diverge (e.g., in tunnels or due to multipath phenomenon). In this paper, we propose a novel hybrid approach based on neural networks (NN) and autoregressive integrated moving average (ARIMA) models to circumvent the EKF limitations and improve the accuracy of vehicle position estimation. While GPS signals are available, we train NN and ARIMA models to learn the non-linear and linear structures in the vehicle position; therefore they can provide good predictions during GPS signal outages. We obtain empirically an improvement of up to 95 % over the simple EKF predictions in case of GPS failures.

Ikram Belhajem, Yann Ben Maissa, Ahmed Tamtaoui

Toward a Practical Method for Introducing and Evaluating Trust Learning Models in Open Multi-agent Systems

In multi-agent systems, agents often interact with each others to achieves their own goals. In open dynamic systems, trust between agents become a critical challenge to make such interactions effective. Many trust models have been proposed to formalise this concept. These models are such good for dealing with trust by proposing components that present a computational form of this concept and a learning strategies to manage it. Components and learning strategies differs from one model to another. This diversity may influence the decision of a user about the best trust model to use in his system. A comparative study is needed to evaluate each trust model and to show the prediction quality of each one. Several testbeds for the evaluation of trust models have been proposed. However, those testbeds are not flexible enough to handle different scenarios in various contexts. In this paper we formulate a practical method based on a framework that introduce the trust concept into open distributed systems, and a testbed that can be used to evaluate trust models in different contexts.

Youssef Mifrah, Abdeslam En-Nouaary, Mohamed Dahchour

Context-Aware Driving Assistance: An Approach for Monitoring-Based Modeling and Self-learning Cars

Recent cars are equipped with a large number of sensors, electronic and communication devices that collect heterogeneous information about the vehicle, the environment and the driver. The use of the information coming from all these devices can highly contribute to the improvement of the vehicle safety as well as the driving experience. The last few years were marked by the development of a large number of in-vehicle intelligent systems that use driving behavior models to assist the driver ubiquitously. However, an important aspect to enhance driving experience is to make the provided assistance as close as possible to the behavior of the car owner, hence a need of personal models of drivers learned from their observed behavior. In this paper, the concept of intelligent and self-learning car is presented and examples of some car’s embedded systems are given. Also, the role of modeling driver behavior in the design of driving assistance systems is emphasized. Further-more, the importance of monitoring-based driving behavior model construction to enable a personalized assistance is brought out together with some potential applications of formal driving behavior models.

Afaf Bouhoute, Rachid Oucheikh, Ismail Berrada

ABE Based Raspberry Pi Secure Health Sensor (SHS)

Electronic health data collected from bio-medical sensors is having a profound and increasing impact on mobile health services. When transferred over the air this data should be accessible only to legitimate users such as doctors, nurses etc. In this paper, we propose a unique Secure Health Sensor (SHS) node which provides fine access control mechanism such that only legitimate users can access sensitive medical data. Medical data security is achieved through ensuring a secure communication by encrypting sensor data, preventing loss of sensor data by using wired connection between Raspberry Pi and sensors and using Ciphertext Policy Based Attribute Based Encryption (CP-ABE) to provide access control in multi-user enviroment. We propose storage of cyrptogrphic credentials on Raspbery Pi on hardware tamper resistant area such as Secure Element on form factors such as Go Trust microSD card. It comprises of java card applets used to store credentials and can be accessed by special securely compiled applications on the Raspbery Pi.

Divyashikha Sethia, Suraj Singh, Vaibhav Singhal

Towards Data-as-a-Service Provisioning with High-Quality Data

Given the large amount of sensed data by IoT devices and various wireless sensor networks, traditional data services lack the necessary resources to store and process that data, as well as to disseminate high-quality data to a variety of potential consumers. In this paper, we propose a framework for Data as a Service (DaaS) provisioning, which relies on deploying DaaS services on the cloud and using a DaaS agency to mediate between data consumers and DaaS services using a publish/subscribe model. Furthermore, we describe a decision algorithm for the selection of appropriate DaaS services that can fulfill consumers’ requests for high-quality data. One of the benefits of the proposed approach is the elasticity of the cloud resources used by DaaS services. Moreover, the selection algorithm allows ranking DaaS services by matching their quality-of-data (QoD) offers against the QoD needs of the data consumer.

Elarbi Badidi, Hayat Routaib, Mohammed El Koutbi

Special Session 2: Unmanned Aerial Vehicles From Theory to Applications


Coverage and Power Gain of Aerial Versus Terrestrial Base Stations

Aerial stations have been recently recognized as an attractive alternative to provide wireless services to terrestrial users thanks to their superior coverage capability. In this paper, the coverage and power gain that can be achieved by a drone with respect to a terrestrial base station are studied. We address the problem by characterizing the coverage area based on the network outage probability, taking into account the height depending fading and path loss exponent that characterize air-to-ground wireless links. Results show that there exist a unique optimal altitude that provides the largest coverage and power gain, which strikes a fine balance between the path loss, due to the higher altitude, and a reduced influence of the multipath scattering. While numerical evaluations show that even at low altitudes the network gains up to 4x coverage or 20 dB power, the gain achieved at optimal altitude can be higher

Mohammad Mahdi Azari, Fernando Rosas, Alessandro Chiumento, Kwang-Cheng Chen, Sofie Pollin

Ultra-Reliable IEEE 802.11 for UAV Video Streaming: From Network to Application

Civilian application of Unmanned Aerial Vehicles (UAVs) are becoming more and more widespread. An important question is how ultra-reliable communication to and from the drone will be organised. At the moment complex and difficult to deploy point-to-point proprietary wireless links are often used. To enable ubiquitous usage of UAVs it is necessary to have a simple, reliable and widely available data link, such as IEEE 802.11. In this work we examine if infrastructure to control UAVs could be built from IEEE 802.11 access points already deployed for other applications. Our conclusions are based on a combination of measurements and simulations. The analysis presented assumes, but is not limited to, a representative UAV mission that involved streaming video to the ground. The proposed framework then significantly improves reliability by allowing the UAV to broadcast to multiple ground receivers and solves the limited acknowledgment available to the aerial node by applying FEC at the application layer.

Bertold Van den Bergh, Alessandro Chiumento, Sofie Pollin

A New Adaptative Security Protocol for UAV Network

An Unmanned Aerial Vehicle (UAV) is a pilotless aerial vehicle which can be controlled either autonomously by onboard computers or remotely controlled by a pilot at the Ground Control Station (GCS). UAV and Ground Control Station (GCS) define a new form network, this kind of network persuade some specific characteristics as sufficient energy, network connectivity, mobility and network security. These specifications persuade difficult challenges for building a trustworthy and secure communication architecture solution. In this paper we present our new secure communication protocol taking into account the specifications of UAV network. This new architecture depends mostly on the definition of a secure protocol which provides authentication, confidentiality and integrity, in preserving network resources for effective data exchanged between UAV and GCS.

Oumhany Zouhri, Siham Benhadou, Hicham Medromi

Optimal Beaconing Policy for Tactical Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAV) were initially developed for military monitoring and surveillance tasks. However, they recently found several interesting applications in the civilian domain. One promising application is to use UAV for military operations behind enmy lines. Rapid deployment along with limited operating costs are key factors that boost the development of UAVs for both military and civilian utilizations. UAVs are battery-powered which makes energy consumption optimization a critical issue for acceptable performance, high availability and an economically viable UAVs deployment. In this paper, we focus on tuning the beaconing probability as an efficient mean of energy consumption optimization. The conducted study provides markov decision process perspective of the problem. Also, we conduct extensive numerical investigations to assist our claims about the energy efficiency of the optimal beaconing policy.

Sara Koulali, Mostafa Azizi, Essaïd Sabir, Rim Koulali

Special Session 3: From Data to Knowledge: Big Data Applications and Solutions


Document-Oriented Data Warehouses: Complex Hierarchies and Summarizability

There is an increasing interest in implementing data warehouses with NoSQL document-oriented systems. In the ideal case, data can be analysed on different dimensions. These dimensions follow strict hierarchies that we can use to roll-up and drill-down on analysis axes. In this paper, we deal with non-strict and non-covering hierarchies, common issues in data warehousing a.k.a. summarizability issues. We show how to model these hierarchies in document-oriented systems and we propose an algorithm that can deal with summarizability issues. The new approach is tested and compared to existing approaches.

Max Chevalier, Mohammed El Malki, Arlind Kopliku, Olivier Teste, Ronan Tournier

Application of APSIS on a Card Payment Solution

As the adoption of Cloud Computing is growing exponentially, many issues linked to security and lack of governance have been noted increasingly. In the domain of payment, other than coins and banknotes, the security of digital transaction is a big concern. In this paper, we extend the work done on APSIS (Advanced Persistent Security Insights System) by applying it on a real Cloud based Card Payment Solution. In next steps, we will focus on evaluating Risk Management of deployed Card Transaction Platform on a Public Cloud and all the strategies to reduce impacts of all potential risks.

Hassan El Alloussi, Karim Benzidane, Othman El Warrak, Leila Fetjah, Said Jai-Andaloussi, Abderrahim Sekkaki

Predicting Chronic Kidney Failure Disease Using Data Mining Techniques

Kidney failure disease is being observed as a serious challenge to the medical field with its impact on a massive population of the world. Devoid of symptoms, kidney diseases are often identified too late when dialysis is needed urgently. Advanced data mining technologies can help provide alternatives to handle this situation by discovering hidden patterns and relationships in medical data. The objective of this research work is to predict kidney disease by using multiple machine learning algorithms that are Support Vector Machine (SVM), Multilayer Perceptron (MLP), Decision Tree (C4.5), Bayesian Network (BN) and K-Nearest Neighbour (K-NN). The aim of this work is to compare those algorithms and define the most efficient one(s) on the basis of multiple criteria. The database used is “Chronic Kidney Disease” implemented on the WEKA platform. From the experimental results, it is observed that MLP and C4.5 have the best rates. However, when compared with Receiver Operating Characteristic (ROC) curve, C4.5 appears to be the most efficient.

Basma Boukenze, Abdelkrim Haqiq, Hajar Mousannif
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