Ubiquitous Networking

The purpose of this paper is to compare two estimation methods when identifying the coefficients of the Simplified Volterra Series (SVS) model, in order to linearize a class AB GaN Power Amplifier (PA) driven by a 20-MHz LTE-A signal. First, a Digital Predistorter (DPD) design using the cholesky decomposition based inversion method and the Least Square QR (LSQR) algorithm is carried out, and next the performances of each method are analyzed in terms of computational complexity and suppressing distortions capability. The co-simulation test results show that the LSQR performs better than Cholesky decomposition in terms of Adjacent Channel Power Ratio (ACPR) and Normalized Mean Square Error (NMSE) by a margin of 3 dB and 4 dB, receptively.

We consider the following fundamental sweep coverage problem that arises in mobile wireless sensor networks: Given a set of k mobile sensors and a set of m points of interests (POIs) in the Euclidean plane, how to schedule the mobile sensors such that the maximum delay between two subsequent visits to a POI by any sensor is minimized. We study two scenarios of this problem: (i) start positions of the sensors are fixed such that they must return to their start positions between subsequent traversals to POIs that fall in their trajectories, and (ii) sensor positions are not fixed and they are not required to return to their start positions between subsequent traversals. Scenario (i) models battery-constrained sensors which need to be recharged frequently, whereas scenario (ii) models sensors that have no constraint on battery and hence frequent recharging is not necessary. We present two constant factor approximation algorithms for each scenario. The problem we consider is NP-hard and, to the best of our knowledge, these are the first algorithms with guaranteed approximation bounds for this problem.

Recently, the deployment of small-cell with overlay coverage has emerged as a reliable solution for 5G heterogeneous network (HetNets). While they provide useful properties, these architectures bring several challenges in network management, including interference alignment, extensive back-hauling, and cell selection within HetNets. In this work, we model the cell selection paradigm in 5G HetNets using a non-cooperative game-theoretic framework, and we show that it admits an equilibrium using mixed strategy Nash Equilibrium (NE) method.

Free space optical (FSO) transmission is a technology which uses a narrow laser beam to transmit the signal from the source to the destination through the free space. Although it has various advantages, a laser beam propagating through the atmosphere is subjected to different kind of disturbances causing the attenuation of the signal and, in some extreme conditions, leading to the link outage. In fact, the atmospheric turbulences and the chemical nature of the medium is the main source of link attenuation. In this paper, we present the different challenges of FSO communications: absorption, pointing errors, atmospheric turbulence and scattering phenomenon. Moreover, based on the strength of turbulences, we will detail the FSO channel modeling. Then, we introduce some techniques to overcome the weakness presented by FSO link under different strength of atmospheric turbulences.

In this paper, a new scalable and adaptable STBC (space time bloc coding) architecture is proposed. This architecture is based on switching between diversity and spatial multiplexing depending on the instantaneous channel state and offers an improvement of bit error rate performances comparing to conventional STBCs.

Taking advantage of the PLC module developed using NS-3 network simulator, we aim through this work to study a realistic model of a cooperative in-home network based on the MAC switching. To evaluate the QoS of the implemented system, we study the channel behaviour in terms of maximum capacity and bit error rate for the AF and DF relay protocols, in comparison with direct transmission. We also study the throughput obtained by our cooperative system. According to the simulations, and despite the short distances and the minimal variations, the cooperative transmission has proved its out-performance compared to the direct transmission protocol.

This paper deals with a scheduling problem in the telecommunication field, namely the node migration scheduling for an access network. The problem consists of migrating nodes from a former network to a new one affording the required services. The migration procedure needs the installation of a bridge between the two networks without disrupting current services. Nodes are moved sequentially one by one. Our objective is to minimize the cost of the required bridge. We describe an enhanced genetic algorithm based on a good initial population. Numerical experiments show that our method has good performance.

With the advent of Big Data, new challenges have emerged regarding the evaluation of decision support systems (DSS). Existing evaluation benchmarks are not configured to handle a massive data volume and wide data diversity. In this paper, we introduce a new DSS benchmark that supports multiple data storage systems, such as relational and Not Only SQL (NoSQL) systems. Our scheme recognizes numerous data models (snowflake, star and flat topologies) and several data formats (CSV, JSON, TBL, XML, etc.). It entails complex data generation characterized within “volume, variety, and velocity” framework (3 V). Next, our scheme enables distributed and parallel data generation. Furthermore, we exhibit some experimental results with KoalaBench.

Thanks to the development in the wireless communication technologies and the microelectronics domain, Wireless Sensor Networks (WSNs) are more and more omnipresent. The most important challenge of WSN is how to extend its lifetime. For long distance communication, using one hop transmission causes the dissipation of a lot of energy. To avoid this dissipation, an energy-efficient multihop transmission strategy based on Dijkstra algorithm is proposed in this paper. We consider a WSN organized into clusters, each cluster is composed of N sensor nodes classified as follows: source node, cluster head (CH) node as the destination, group of active nodes and group of sleeping nodes. The selection of CH node is based on the position of nodes within the cluster and their residual energy. Then, the CH groups the remaining nodes into active or sleeping nodes according to a reference distance. We suppose that the transmitting symbol is correctly received only if the Signal-to-Noise Ratio (SNR) at the receiver is above a threshold $$\gamma _{th}$$ . Our main objective is to define a new transmission technique minimizing the power consumption using multihop communication. The selected relays which cooperate to aid the source-destination communication are those offering the least transmit power while maintaining SNR equal to the threshold $$\gamma _{th}$$ . We use Dijkstra algorithm to select the reliable relays. Simulations results demonstrate that the proposed transmission technique can reduce enormously the power consumption.

A Wireless Sensor Network (WSN) consists of a set of sensor nodes which have a limited energy, processing and memory capabilities. The applications of WSN in some hostile environment make the sensor nodes difficult to replace once their battery resources exhaust. The wireless transmission is the most energy consuming operation and designing an energy efficient routing protocol becomes the main goal for the wireless sensor network. LEACH is considered as the most popular routing protocol which has better performance in saving the energy. However, it has some limits. This paper presents a new variant of LEACH protocol called TV-LEACH that aims extending the lifetime of the network. The simulation results show that the network lifetime in the improved protocol is better than that of the LEACH Protocol.

Nowadays there is a great interest in the development of cross-domain IoT applications that are able to gather an high number of observations taken from sensors belong to heterogeneous IoT platforms and efficiently combine them in flows that can be exploited for conducting analysis. However, their realization poses several concerns. From one side, graphical interfaces are needed for facilitating the specification and composition of the data acquisition operations. From the other side, facilities are required to manage big data streams, to check the application correctness, and to set up and configure clusters of machines. Starting from the graphical facilities of the StreamLoader system for the development of Data Acquisition Plans (DAPs) from sensors belonging to heterogeneous IoT platforms, in this paper we show the approach developed for translating DAPs in a Spark-Streaming application. Experiments are shown for assessing the scalability of the developed applications.

This study provides a road traffic portrait in urban areas to compare the congestion level of certain sections. In view of a better exploitation, we proposed a Bayesian network (BN) analysis approach to modeling the probabilistic dependency structure of congestion causes on a particular road segment and analyzing the probability of traffic congestion. In this case, two steps are also necessary, the macroscopic traffic flow modeling and the traffic simulation for which empirical measurements can be developed and tested. The BN method is used to analyze the uncertainty and probability of traffic congestion, and is proved to be fully capable of representing the stochastic nature of road network situation. This approach is used to represent road traffic knowledge in order to build scenarios based on a practical case adapted in the city of Sfax.

Data centers are the infrastructures that support the cloud computing services. So, their topologies have an important role on controlling the performance of these services. Designing an efficient topology with a high scalability and a good network performance is one of the most important challenges in data centers. This paper surveys recent research advances linked to data center network topologies. We review some representative topologies and discuss their proprieties in details. We compare them in terms of average path length, network fault tolerance, scalability and connection pattern techniques.

Nowadays, Internet of thing including network support (i.e. checking social media, sending emails, video conferencing) requires smart and efficient data centers to support these services. Hence, data centers become more important and must be able to respond to ever changing service requirements and application demands. However, data centers are classified as one of the largest consumers of energy in the world. Existing topologies such as ScalNet improves the data center scalability while leading to enormous amounts of energy consumption. In this paper, we present a new energy efficient algorithm for ScalNet called Green ScalNet. The proposed topology strikes a compromise between maximizing the energy saving and minimizing the average path length. By taking into consideration the importance of the transmitted data and the critical parameters for the receiver (e.g. time, energy), the proposed topology dynamically controls the number of active communication links by turning off and on ports in the network (switches ports and nodes ports). Both theoretical analysis and simulation experiments are conducted to evaluate its overall performance in terms of average path length and energy consumption.

Virtual Machine Placement (VMP) is one of the challenging problem arising in cloud computing data centers. VMP is the process of selecting the most suitable Physical Machine (PM) to host the Virtual Machines (VMs). The placement goal can be either maximizing the usage of existing available resources or it can be saving power by being able to shut down some servers (PMs). In this paper, we propose a new Two-Objective Integer Linear Programming (TOILP) model to solve the VMP problem aiming, for the first time as far as we know, at maximizing simultaneously the usage of PM resources while ensuring power efficiency. We also assume heterogeneous configuration for the data center which has been proven, through recent research work and industrial experience, to be more cost-effective for some applications especially those with intensive I/O operations. Two heterogeneous data center configurations are studied in order to ascertain the impact of each configuration on the performance of the proposed model. Simulation results point out the benefits brought by the TOILP model with an average number of used PMs gain of 32.45% and an average total potential cost of resource wastage gain of 60.62%. It was also reported that the cloud provider should not choose the PMs’ configuration independently of the offered virtual machines.

Over the last few years, cloud computing has become a prominent paradigm. It promises to offer to users cost-effective and on-demand decentralized services, in terms of computing, memory, storage, etc., without the need for large infrastructure investments. Moreover, with the growing number of data centers resources, much higher levels of energy are being consumed. Also, the increasing level of associated carbon dioxide is emitted in the air, which consequently, raises the costs. Considering that there is an extreme growth in demand for Data Centers cloud computing requiring high computational complexity, there is an utmost need to take sufficient measures to lower the risk of energy demand. Hence, efficient energy-aware techniques are required to assure proper performance with regards to Service Level Agreements (SLA). In this work, we highlighted the issue of Virtual Machines (VMs) allocation in cloud computing data centers, and how to better manage the placement of VMs in order to optimize performance and reduce energy consumption. In our proposed solution, we will focus on minimizing the number of Physical Machines (PMs) hosting the VMs and utilize them as sufficient as possible.

The need to monitor areas of high risk in terms of temperature indexes has included two important elements for its compliance: monitoring and forecast of records in an environment. Performing this procedure manually is inefficient as it provides a flat perspective and can’t predict the state of the environment rigorously. Software systems are contemporary elements in constant refinement which satisfy the emerging needs within a certain context. The monitoring and forecasting processes can be hence automated and that tends to lead to a better supervision of the risks present in the environment. This article presents a proposal for the supervision of high-risk areas, through temperature records that can be managed through the design of a software system with the implementation of mobile 4.0G LTE technologies, aimed at efficiency and effectiveness in the notification of the environmental status. Finally, the development of a remote temperature monitoring and forecast system using mobile technologies leads to conclude that the fuzzy logic prediction system‘s quadratic error is lower than 2.6%. Additionally, future work is presented from the research standpoint according to the emergence of new perspectives related to this developing software system.

IoT is the third wave of economy after the first and second being agriculture and industry, respectively, paving the way for the fourth industrial revolution (4IR). IoT is a combination of all the revolutionary technologies in the last two decades. More than a billion of smart devices have been developed across the world by more than 10 vendors to satisfy billions of needs that are trusted by 98% of economic actors. This study describes design and implementation of IoT architectures stressing on scalability, integration, and interoperability of heterogeneous IoT systems. It gives answers to (i) how systems can be designed to become easily configurable and customizable for a specific IoT infrastructure? And (ii) how Investors, producers and consumers can be integrated on the same page of an IoT platform?We have developed a master database and directories from top chart IoT nomenclature, frameworks, vendors, devices, platforms and architectures and integrated data from 27 big online resources commonly used by Forbes, Businessweek and CNBC. Also, datasheets of IoT equipment by vendors (e.g. Intel, IBM, ARM, Microchip, Schneider, and CISCO), used tools (e.g. Labcenter Proteus, AutoCAD and Excel), and platforms (e.g. Visual Studio, Eclipse) are combined to build directories of plethora of data. The main outcome of this work culminates in providing a seamless solution and recommendations for various infrastructures (hardware and software) for effective and integrated resource utilization and management in a new IoT paradigm.

In this paper, we address the distributed caching device-to-device (D2D) network in which the popular contents are cached proactively as chunks in the storage of users’ devices (referred to as “helpers”) in order to offload the content delivery traffic and reduce the transmission delay. If a content is cached as a chunk-based content, the requester has to download all the chunks of this content, thus, he may encounter a case wherein the consumed energy for obtaining this chunk-based content exceed the one for obtaining the same content as single-based content, if any. As the dissemination of a content as a single-based content can considerably impact the helper energy expenditure, the chunk-based caching may incurs additional energy burden owing to the limited battery capacity. So, in order to optimally trade-off between energy consumption and transmission delay, we propose a hybrid strategy wherein each content is cached simultaneously as single-based strategy and chunk-based strategy. We show through simulations that the proposed strategy outperforms these two strategies and achieves the trade-off.

The prosumers represent a new profile of consumer/producer of energy that deploy the renewable technology to produce a pure quantity of energy oriented for internal Household demand, or for grid injection (Grid Connected PV). Based on decentralized structure, several studies discuss the requirement efficiency to enhance yield results and reduce energy loss in the grid while the moment of injection and distribution. On this paper, we use a game theory approach to incentivize prosumers to participate in a market game-based quantity of PV energy injected to maximize incomes profit and reduce the energy consumed from the grid by implementing Cournot-Nash equilibrium approach.

Cities are the economic and social progress for nations, but the speed with which they grow up creates many problems, especially in terms of mobility. In reality, finding a parking space in the city of Casablanca in Morocco in working hours is an almost impossible mission. This search for parking space results in waste of time, fuels, and traffic jams. In order to resolve these issues and reduce the problems caused by inefficient and classic parking system, we proposed a solution to contribute to the good management of traffic, reduce the search time of free parking spaces and improve the profitability of the parking by regulating rates.

Researches in the field of wireless sensor networks set as a main objective the development of algorithms and protocols to ensure the minimum of energy consumption. Most of the proposed solutions are based on a single-layer approach of the OSI model. Recently, works tend to use several layers at the aim of optimizing the energy consumption. We proposed in this paper an energy-aware protocol based on the Cross-Layer mechanism for wireless sensor networks and that considers the physical layer, the MAC layer and the network layer to route the sensed data. The new variant of the proposed protocol Energy Efficient Cross-layer Protocol (EECP) tries to improve the algorithm of relay nodes selection in order to avoid loops and delaying the packet delivery. We simulate the new variant and we compare it with CLEEP in terms of residual energy, packet delivery ratio and load balancing metric.

Nowadays, unmanned aerial vehicles (UAVs) as flying base stations have attracted significant interest in telecommunications service field; Thanks to their low-cost, high maneuverability, flexible deployment and mobility advantages, they have become a main stream solution, to provide wireless communication in exceptional scenarios such as hard to reach areas or massive-attended events. Because UAVs are energy budget constrained, optimal availability control for energy efficiency is proposed in this paper. Within such a situation, the most important objective of a UAVs operator is to provide a service with acceptable availability and cost effective, so that, to realize a satisfactory benefit. The conducted study provides a non-cooperative duopoly game where UAVs Service Providers (SP) are competing to serve a geographical area. We focus on the scheduling of beaconing periods as an efficient mean of energy consumption optimization that results in temporary unavailability of network connectivity. A tractable comparative analysis for the game’s equilibrium, in terms of both Cournot and stackelberg frameworks is derived. We show that the benefit when adopting the leadership model is exhibiting some additional properties compared to the Cournot (anarchic) game. Some extensive simulations are given to confirm our proposal.

The purpose of this paper is to describe the development and present the results of the design and implementation of a laser shooting simulator based on computer vision. Our proposal is to develop a virtual environment through a simulation platform to project it on a surface and combine it with computer vision to interact with created targets. Two main stages haven been structured: adjustment and calibration of the camera in the environment and integration of the laser in the simulation.

This article will establish the physical design of a tetrapod robot, highlighting its own characteristics of low-level three-dimensional movement to move from one point to another. The navigation system was also examined in environments not defined from a top-down perspective, making the analysis and processing of the images with the purpose of avoiding collisions between the robot and static obstacles, and using probabilistic techniques and partial information on the environment, RRT generate paths that are less artificial.

The present document discusses a methodology for the implementation of services that require QoS in 5G Li-Fi networks. It takes into account the inherent characteristics of these technologies and the necessary requirements for their implementation.

Deploying security solutions to defend against known security attacks could fail not only due to policy, design, or implementation flaws in the designed solutions, but also due to lack of data regarding the environment under which the attack is executed, or the security solution supervising the malicious behavior. To this end, we develop in this paper a new cyber defense system that assesses the efficiency of a cyber security solution when faced to attack scenarios occurring under different contexts (the configuration and location of distributed security solutions, called observer agents, the used reaction system, and the information visibility of attacks). The work also considers the development of a model for describing the concept of global, local and observable executable scenarios, which allows to observe step by step the execution of an attack scenario, and the observer agents’ behavior and their reactions to the attack execution. The model allows also to identify the step at which an attack scenario can be blocked. A case study is presented to exemplify the proposal.

Contrary to interference which is unintended, jamming is intentionally created by an adversary in order to prevent the receiver from properly decoding the legitimate signal. It can cause severe denial of service by targeting channels carrying critical information. In this paper, we use multiple-input multiple-output (MIMO) technology to eliminate the jamming signal in mobile smallcells. To achieve this, we combine spectral diversity together with beamforming. The receiver is equipped with two antennas receiving at two different frequencies, while the transmitter uses two uniform linear antennas arrays (ULA) each transmitting the signal at one of those frequencies. Based on a pre-calculated ratio of the jammer’s channels sensed by the receiver, jamming is suppressed from the output signal. In fact, beamforming weights associated to each antenna array are adequately adjusted in order to constructively combine the received signals. Conducted simulations prove the efficiency of the solution in mitigating the attack by achieving satisfying bit-error-rates (BER).

The healthcare industry has become a very important pillar in modern society but has witnessed an increase in fraudulent activities. Traditional fraud detection methods have been used to detect potential fraud, but in certain cases, they have been insufficient and time-consuming. Data mining which has emerged as a very important process in knowledge discovery has been successfully applied in the health insurance claims fraud detection. We performed an analysis of studies that used data mining techniques for detecting healthcare fraud and abuse using the supervised and unsupervised data mining methods. Each of these methods has their own strengths and weaknesses. This article attempts to highlight these areas, along with trends and propose recommendations relevant for deployment. We identified the need for the use of more computationally efficient models that can easily adapt and identify the novel fraud patterns generated by the perpetrators of healthcare claims fraud.

The growth of ubiquitous networks moves ever more personal data into collectible and computational opportunities. This changes assumptions based on past latency and limits on data analysis and brings challenges to the reliability of data acquisition principles and practices and their proper use in societies. System engineers must consider outcomes and related regulation in the design and use of these systems. It also cautions us as to overreaching. We examine the general legal sphere within which ubiquitous networks and associated data exist, mapping some technological outcomes to legal consequences. We consider the impact and legal decisions regarding ubiquitous networks in the United States as an indicator of future direction and legal entanglements of these technological systems. In particular, we consider security and privacy principles that may regulate computational use through ubiquitous networks, and the competing interests/benefits/detriments in their use. This informs as to possible future regulation that may be needed or required and offer guidance with the growing data sphere and ubiquitous networking, and advises that the engineering of such systems should be flexible enough to accommodate new regulatory regimes as to deployment, access and use.

Finding the shortest path from source to target is key to efficient search missions of unmanned aerial vehicles (UAVs). For fixed wing UAVs, Dubins curves can be used to find the shortest path. For successive visits to targets during a single mission, the direction of flight of the UAV at each target is not of any significance. In such cases Dubins curves can be simplified to two instead of three constituent components. This paper proposes an algorithm derived using elementary geometry that generates Dubins curves for multiple target search missions. The algorithm proposed is tested and results reported for a search and rescue mission indicate that the path generator is fairly robust.

Recent studies have revealed the benefit of capitalising on the interplay between Unmanned Aerial Vehicles (UAVs) and ground sensors, for the efficient data muling from locations of interest to back-end infrastructures where, it is analysed and processed for further decision making. However, such studies have not considered minimizing the energy spent by a UAV for moving from one location to another; a requirement that can help maximize the lifetime of the resulting hybrid network infrastructure before recharging. This paper proposes an optimal clustering model for a case where, an Unmanned Aerial Vehicle (UAV) is to monitor an area of interest, to collect data captured by a terrestrial sensor network. The proposed clustering algorithm minimises a combination of the energy for routing data in the terrestrial network and the energy used by the UAV to collect data from cluster heads and report to a back-end infrastructure. We formally calculate the optimal number of clusters in a uniformly distributed sensor network, to support existing k-clustering schemes, and for general networks, a general clustering algorithm is proposed. Performance evaluation reveals relevance of accurately modelling the hybrid networks underlying the“Internet-of-Things in Motion”.

Unmanned aerial vehicles (UAV) deployment and emerging air-to-ground wireless services have been a topic of great interest in the last few years. The main virtue of UAV networks is that they provide on demand connectivity. However, the design of such networks is intrinsically dependent on the air-to-ground propagation conditions. In order to construct a reliable air-to-ground channel model that takes into account the nature of the surrounding environment, we propose to exploit the information provided by building footprints. The obtained results are compared with existing statistical air-to-ground channel models. It is shown that both the the path loss exponent and the variance of the shadow fading are dependent on the distance on the ground between the UAV and the user and the drone’s altitude. The proposed channel modeling method is then used to estimate the coverage probability over the studied area.

This paper describes a proposal of solution for target visual loss in autonomous navigation of UAVs by using artificial. Tests of target maintenance and position recovery have been included along with the sequence of images that verify the method performance.

In this article, we present the use of depth estimation in real time using the on-board camera in a micro-UAV through convolutional neuronal networks. The experiments and results of the implementation of the system in a micro-UAV are presented to verify the unsupervised model improvement with monocular cameras and the error regarding real model.