Developing countries usually lack the proper governance means to generate and regularly update a national rooftop map. Using traditional photogrammetry and surveying methods to produce a building map at the federal level is costly and time consuming. Using earth observation and deep learning methods, we can bridge this gap and propose an automated pipeline to fetch such national urban maps. This paper aims to exploit the power of fully convolutional neural networks for multi-class buildings’ instance segmentation to leverage high object-wise accuracy results. Buildings’ instance segmentation from sub-meter high-resolution satellite images can be achieved with relatively high pixel-wise metric scores. We detail all engineering steps to replicate this work and ensure highly accurate results in dense and slum areas witnessed in regions that lack proper urban planning in the Global South. We applied a case study of the proposed pipeline to Lebanon and successfully produced the first comprehensive national building footprint map with approximately 1 Million units with an 84% accuracy. The proposed architecture relies on advanced augmentation techniques to overcome dataset scarcity, which is often the case in developing countries.

Generating smooth surfaces of arbitrary topology is a major challenge in geometric modeling, computer graphics, and scientific visualization. Subdivision surfaces have emerged as a powerful and useful technique in modeling free-form surfaces. Recursive subdivision techniques generate visually pleasing smooth surfaces through the repeated application of a fixed set of subdivision rules. Given a control mesh, a Catmull-Clark Subdivision Surface (CCSS) is generated by iteratively refining (subdividing) the control mesh to form new control meshes. CCSS implementations do not perform well and suffer from low CPU utilization because they are often waiting for data to be transferred from memory due to the repeated pointer indirections. Rapid Evaluation of CCSS is an approach that focuses on achieving maximum performance by carefully addressing caching issues. However, this approach is designed with primary target being single core machines. In this paper, we implement the Rapid Evaluation of Catmull-Clark Subdivision Surfaces (RECCSS) algorithm in C++ and measure its achieved performance. We then redesign RECCSS to leverage the potential of parallel computation on widely available multicores machines and show that Parallelized RECCSS (PRECCSS) achieves noticeable speedup when run on diverse set of machines compared to the original RECCSS implementation. In addition, we conduct a study about the data value predictability of PRECCSS load instructions using Pin dynamic binary instrumentation tool, and conclude that 93.25% prediction accuracy can be achieved with existing value prediction techniques.

Wi-Fi connectivity, a necessity in this digital era, requires careful infrastructure planning and tuning during installation. In this paper, we propose “Aparecium Wi-Fi Planner”, an open-source and cross-platform, Wi-Fi planning software tool based on an enhanced empirical path loss model. The proposed “Enhanced Solah's model” delivers more accurate results than existing models. And hence, “Aparecium Wi-Fi Planner” accurately estimates path loss attenuation, absorption attenuation by obstacles and fading effect. Moreover, the tool integrates the design and development of several algorithms to find full-coverage and optimal access point location with reduced complexity. Aparecium has been thoroughly tested and validated using both simulation and real testbed scenarios.

Modern wideband receivers must be able to slice and dice a large band of the spectrum in real time, while available receivers are increasingly faced with the challenges of providing flexible operations on large number of channels simultaneously. We present in this paper a comprehensive review of major channelizer algorithms available in the literature that are compatible with Software Defined Radio platforms. We employ analytical models to evaluate and compare various channelizer algorithms. Moreover, we implement and simulate the Polyphase Fast Fourier Transform (PFFT) channelizer using MATLAB software. We show using the reported results that PFFT computation complexity is about four times lower than any other channelizer. We also contribute the first hardware implementation of PFFT using Vivado High Level Synthesis. In addition, we provide a clear and practical manipulation of the PFFT structure to enable real-time streaming support taking into account system optimization in terms of hardware resources and latency.

Recent rules from FCC and OFCOM foresee the utilization of spectrum database as the main solution to provide accurate spectrum information about TV white spaces for secondary users in cognitive vehicular networks. Spectrum database provides maximum protection to licensed users, however, its implementation is not straight-forward in vehicular environments, due to the significant query overhead generated by mobile vehicles in congested urban scenarios. For this reason, in this paper we investigate possible solutions to integrate cooperative sensing and spectrum database querying, with the goal to minimize the primary users detection overhead while guaranteeing maximum protection for these primary users. We propose both theoretical and practical contributions in this field. First, we introduce a topological study to determine the optimal ratio between cooperation and spectrum database querying (referred to as ModeI, ModeII, cooperative Sensing-only devices according to FCC terminology) in order to minimize the network utilization for white space detection. We investigate various system parameters such as spectrum database query frequency, broadcast frequency (for cooperative sensing) and vehicles' velocity, and study their impact on system performance. Then, we propose a distributed (bio-inspired) protocol for network deployment that enables multi-interfaces vehicles to dynamically decide the detection mode to use, in order to minimize the database load, while providing high enough protection for licensed users.

The IEEE 1609.4-Multi-Channel Operation protocol has been proposed to support the co-existence of safety and non-safety (infotainments) applications over the Dedicated Short Range Communication (DSRC) channels at the 5.9 GHz band. However, the multi- channel approach over a single-radio transceiver might result in several performance degradations that have not been thoroughly investigated yet. In this paper, we analyze the performance of safety- related applications over multi-channel vehicular networks. We demonstrate through a simulation study that the synchronous channel switching enforced by the IEEE 1609.4 protocol might easily compromise the performance of safety applications that rely on the periodic exchange of short lived broadcasts. Thus, we propose in this work the WAVE-enhanced Adaptive Broadcast (WAB) scheme. WAB provides a novel MAC contention control mechanism intended to reduce the impact of packet collisions caused by the synchronous channel switching, and to increase the packet delivery rate of broadcast messages in congested vehicular scenarios. The WAB scheme dynamically adapts to the channel conditions through a distributed load estimator metric, and implements priority mechanisms to ensure fairness among vehicles. Simulation results reveal that the proposed WAB scheme can significantly increase the packet delivery rate of broadcast messages when compared to the existing IEEE 802.11p/1609.4 scheme.

Recently, the IEEE 1609.4 WAVE protocol has been proposed to enable multi-channel communication in Vehicular Ad Hoc Networks (VANETs). While the usage of multi-channel technology can favor the co-existence of safety and non-safety vehicular applications, its implementation on single-radio transceivers poses some major concerns about the effective utilization of the channel resources. In this paper, we investigate the performance of safety-related applications on multi-channel VANETs. We demonstrate that the synchronous channel switching operations enforced by the IEEE 1609.4 protocol introduce additional delays to the delivery of safety messages, that might compromise the viability of such applications. To cope with this problem, we propose a WAVE-enhanced Safety message Delivery scheme (WSD) that minimizes the delivery delay of safety messages in multi-channel VANETs, while preserving compatibility with the IEEE 1609.4/802.11p standards. WSD attempts to transmit high priority safety message during SCH intervals while guaranteeing reception by all neighbors. We formulate the broadcast problem in multi-channel VANETs as a scheduling problem over the different DSRC channels. We extend the problem formulation to cooperative scenarios, in which multiple vehicles contribute to disseminate the safety message over the different channels. We evaluate our proposed WSD scheme through a simulation study. We show that our proposed solution can provide effective reduction of the delivery delay in multi-channel VANETs, when compared to the legacy IEEE 1609.4/802.11p protocols.

Mobile devices are getting more pervasive, and it is becoming increasingly necessary to integrate web services into applications that run on these devices. We introduce a novel approach for dynamically invoking web service methods from mobile devices with minimal user intervention that only involves entering a search phrase and values for the method parameters. The architecture overcomes technical challenges that involve consuming discovered services dynamically by introducing a man-in-the-middle (MIM) server that provides a web service whose responsibility is to discover needed services and build the client-side proxies at runtime. The architecture moves to the MIM server energy-consuming tasks that would otherwise run on the mobile device. Such tasks involve communication with servers over the Internet, XML-parsing of files, and on-the-fly compilation of source code. We perform extensive evaluations of the system performance to measure scalability as it relates to the capacity of the MIM server in handling mobile client requests, and device battery power savings resulting from delegating the service discovery tasks to the server.

Port scanning is the most popular reconnaissance technique attackers use to discover services they can break into. Port scanning detection has received a lot of attention by researchers. However a slow port scan attack can deceive most of the existing Intrusion Detection Systems (IDS). In this paper, we present a new, simple, and efficient method for detecting slow port scans. Our proposed method is mainly composed of two phases: (1) a feature collection phase that analyzes network traffic and extracts the features needed to classify a certain IP as malicious or not. (2) A classification phase that divides the IPs, based on the collected features, into three groups: normal IPs, suspicious IPs and scanner IPs. The IPs our approach classify as suspicious are kept for the next (K) time windows for further examination to decide whether they represent scanners or legitimate users. Hence, this approach is different than the traditional approach used by IDSs that classifies IPs as either legitimate or scanners, and thus producing a high number of false positives and false negatives. A small Local Area Network was put together to test our proposed method. The experiments show the effectiveness of our proposed method in correctly identifying malicious scanners when both normal and slow port scan were performed using the three most common TCP port scanning techniques. Moreover, our method detects malicious scanners that are otherwise not detected using well known IDSs such as Snort.

The Wireless Access in Vehicular Environments (WAVE) protocol stack is one of the most important protocols used to allocate spectrum for vehicular communication. In a previous work, we proved that WAVE does not provide sufficient spectrum for reliable exchange of safety information. More specifically, safety message delay is not acceptable and exceeds application requirements. In this paper, we propose a system that provides Data delivery guarantees using Cognitive networks principles in congested Vehicular ad hoc networks. We will refer to our system as DCV. Our goal is to ensure that all safety packets get generated and transmitted during the same interval. The system monitors the contention delay experienced by cars on the control channel where all safety packets should be transmitted. If the sensed contention delay exceeds delay threshold γ, the Road Side Unit (RSU) needs to increase the spectrum allocated to the control channel using cognitive networks. The RSU employs a feedback control design where additional bandwidth is added to drive the contention delay below the delay threshold γ used as reference input for the controller. Analysis and simulations indicate the effectiveness of the system in providing data delivery guarantees in vehicular networks and thus increasing safety measures on the road.

Wireless Access in Vehicular Environments (WAVE) protocol stack is the most important protocol used to allocate spectrum for vehicular communication. The capabilities of WAVE to provide reliable exchange of safety information are questionable. In a previous work, we suggested a system that employs cognitive networks principles to increase the spectrum allocated to the control channel (CCH) by the IEEE 802.11p amendment, where all safety information is transmitted. However, the decision making process implemented in that work does not differentiate between contention levels and does not relate precisely the measured contention to the amount of needed spectrum, which leads to an inefficient utilization of the white spectrum. In order to assign the minimum necessary additional bandwidth to relieve the contention, we suggest in this paper a new system that quantifies contention into multiple levels of severity based on Fuzzy Logic and maps additional spectrum correspondingly. Simulations show the effectiveness of the system in allocating the minimum needed bandwidth to relieve contention, without affecting other QoS parameters such as delay and number of untransmitted packets.

The Wireless Access in Vehicular Environments (WAVE) protocol stack is one of the most important protocols proposed to standardize and allocate spectrum for vehicle-to-vehicle and vehicle-to-infrastructure communication. In a previous work, we proved that WAVE faces a spectrum scarcity problem which hinders reliable exchange of safety information. To overcome this problem, we proposed a system that applies cognitive networks principles to WAVE as to increase the spectrum allocated to the control channel (CCH) by the IEEE 802.11p amendment, where all safety information is transmitted. However, the decision making process in our previous work did not utilize the extra spectrum efficiently as it was not allocated according to the contention level experienced by the vehicle. In this paper, we suggest a system that employs a fuzzy logic system (FLS) to dynamically assign additional spectrum from the ISM band to the CCH. This system, which we call FCVANET, assigns the minimum necessary additional bandwidth to relieve the contention. The FLS takes as input 2 parameters, the message delay and the un-transmitted packets and utilizes a feedback loop. Our simulations show that the proposed system allocates bandwidth more efficiently in accordance with the contention level faced by the vehicles. The system succeeds to relieve contention by reducing delay and the number of un-transmitted packets.