arXiv subjects

Georges Kaddoum

Publications and source records attributed to Georges Kaddoum.

At least 91 records · Page 5Linked to original sources

arXiv2019

Fairness and Sum-Rate Maximization via Joint Channel and Power Allocation in Uplink SCMA Networks

In this work, we consider a sparse code multiple access uplink system, where $J$ users simultaneously transmit data over $K$ subcarriers, such that $J > K$, with a constraint on the power transmitted by each user. To jointly optimize the subcarrier assignment and the transmitted power per subcarrier, two new iterative algorithms are proposed, the first one aims to maximize the sum-rate (Max-SR) of the network, while the second aims to maximize the fairness (Max-Min). In both cases, the optimization problem is of the mixed-integer nonlinear programming (MINLP) type, with non-convex objective functions, which are generally not tractable. We prove that both joint allocation problems are NP-hard. To address these issues, we employ a variant of the block successive upper-bound minimization (BSUM) \cite{razaviyayn.2013} framework, obtaining polynomial-time approximation algorithms to the original problem. Moreover, we evaluate the algorithms' robustness against outdated channel state information (CSI), present an analysis of the convergence of the algorithms, and a comparison of the sum-rate and Jain's fairness index of the novel algorithms with three other algorithms proposed in the literature. The Max-SR algorithm outperforms the others in the sum-rate sense, while the Max-Min outperforms them in the fairness sense.

cs.IT↗

arXiv2019

A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing

With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for real-time data processing and analysis has emerged as an essential pre-requite for customers' satisfaction. In this direction, Mobile Edge Computing (MEC) provides seamless services with reduced latency, enhanced mobility, and improved location awareness. Since MEC has evolved from Cloud Computing, it inherited numerous security and privacy issues from the latter. Further, decentralized architectures and diversified deployment environments used in MEC platforms also aggravate the problem; causing great concerns for the research fraternity. Thus, in this paper, we propose an efficient and lightweight mutual authentication protocol for MEC environments; based on Elliptic Curve Cryptography (ECC), one-way hash functions and concatenation operations. The designed protocol also leverages the advantages of discrete logarithm problems, computational Diffie-Hellman, random numbers and time-stamps to resist various attacks namely-impersonation attacks, replay attacks, man-in-the-middle attacks, etc. The paper also presents a comparative assessment of the proposed scheme relative to the current state-of-the-art schemes. The obtained results demonstrate that the proposed scheme incurs relatively less communication and computational overheads, and is appropriate to be adopted in resource constraint MEC environments.

cs.NI↗

arXiv2019

LiSA: A Lightweight and Secure Authentication Mechanism for Smart Metering Infrastructure

Smart metering infrastructure (SMI) is the core component of the smart grid (SG) which enables two-way communication between consumers and utility companies to control, monitor, and manage the energy consumption data. Despite their salient features, SMIs equipped with information and communication technology are associated with new threats due to their dependency on public communication networks. Therefore, the security of SMI communications raises the need for robust authentication and key agreement primitives that can satisfy the security requirements of the SG. Thus, in order to realize the aforementioned issues, this paper introduces a lightweight and secure authentication protocol, "LiSA", primarily to secure SMIs in SG setups. The protocol employs Elliptic Curve Cryptography at its core to provide various security features such as mutual authentication, anonymity, replay protection, session key security, and resistance against various attacks. Precisely, LiSA exploits the hardness of the Elliptic Curve Qu Vanstone (EVQV) certificate mechanism along with Elliptic Curve Diffie Hellman Problem (ECDHP) and Elliptic Curve Discrete Logarithm Problem (ECDLP). Additionally, LiSA is designed to provide the highest level of security relative to the existing schemes with least computational and communicational overheads. For instance, LiSA incurred barely 11.826 ms and 0.992 ms for executing different passes across the smart meter and the service providers. Further, it required a total of 544 bits for message transmission during each session.

cs.NI↗

arXiv2019

A Novel Relay Selection Strategy of Cooperative Network Impaired by Bursty Impulsive Noise

Best relay selection (BRS) is crucial in enhancing the performance of cooperative networks. In contrast to most previous works, where the guidelines for BRS are limited to Gaussian noise, in this article, we propose a novel relay selection protocol for a decode-and-forward cooperative network taking into account the bursty impulsive noise (IN). The proposed protocol chooses the N'th best relay considering both the channel gains and the states of the IN of the source-relay and relay-destination links. For this scheme, to obtain the state of IN, we propose a state detection algorithm using maximum a posteriori (MAP) detection. To analyze the performance of the proposed protocol, we first derive closed-form expressions for the probability density function (PDF) of the received signal-to-noise ratio assuming all the relays know the state of IN perfectly (genie-condition). Then, these PDFs are used to derive closed-form expressions for the bit error rate (BER) and the outage probability. Finally, we also derive the asymptotic BER and outage expressions to quantify the diversity benefits. We show that the proposed MAP-based N'th BRS protocol attains the derived genie-aided analytical results and outperforms the conventional relay selection protocol, optimized for the Gaussian case, and which does not take into account the IN memory.

eess.SP↗

arXiv2019

Design and Performance Analysis of an Index Time Frequency Modulation Scheme for Optical Communications

In this article, we propose an index modulation system suitable for optical communications, based on jointly driving the time and frequency of the signal: an index-time frequency hopping (I-TFH) system. We analyze its performance from the point of view of its efficiency in power and spectrum, and its behavior in terms of error probability for the non-turbulent free-space optical (FSO) channel. We compare I-TFH with already proposed index modulated systems of the same nature, but where the amplitude or the number of transmitters are driven instead of the signal frequency. We derive and compare approximations for the average symbol and bit error probabilities of all these systems. The simulation results show that said approximations are tight enough for a wide range of signal-to-noise ratios and system parameters. Moreover, I-TFH shows to be better performing in BER and/or power efficiency than the comparative alternatives, and may offer interesting properties in a variety of contexts.

eess.SP↗

arXiv2019

Ultra-small Cell Networks with Collaborative RF and Lightwave Power Transfer

This paper investigates a hybrid radio frequency (RF)/visible light communication (VLC) ultra-small cell network consisting of multiple optical angle-diversity transmitters, one multi-antenna RF access point (AP), and multiple terminal devices. In the network, the optical transmitters play the primary role and are responsible for delivering information and power over the visible light, while the RF AP acts as a complementary power transfer system. Thus, we propose a novel collaborative RF and lightwave resource allocation scheme for hybrid RF/VLC ultra-small cell networks. The proposed scheme aims to maximize the communication quality-of-service provided by the VLC under a constraint of total RF and light energy harvesting performance, while keeping illumination constant and ensuring health safety. This scheme leads to the formulation of two optimization problems that correspond to the resource allocation at the optical transmitters and the RF AP. Both problems are optimally solved by appropriate algorithms. Moreover, we propose a closed-form suboptimal solution with high accuracy to tackle the optical transmitters' resource allocation problem, as well as an efficient semi-decentralized method. Finally, simulation results illustrate the achievable performance of the investigated system and the effectiveness of the proposed solutions.

cs.IT↗

arXiv2019

On Physical Layer Security over Fox's $H$-Function Wiretap Fading Channels

Most of the well-known fading distributions, if not all of them, could be encompassed by Fox's $H$-function fading. Consequently, we investigate the exact and asymptotic behavior of physical layer security (PLS) over Fox's $H$-function fading wiretap channels. In particular, closed-form expressions are derived for secrecy outage probability (SOP), probability of non-zero secrecy capacity (PNZ), and average secrecy capacity (ASC). These expressions are given in terms of either univariate or bivariate Fox's $H$-function. In order to show the comprehensive effectiveness of our derivations, three metrics are respectively listed over the following frequently used fading channels, including Rayleigh, Weibull, Nakagami-$m$, $α-μ$, Fisher-Snedecor (F-S) $\mathcal{F}$, and extended generalized-$\mathcal{K}$ (EGK). Our tractable results are more straightforward and general, besides that, they are feasible and applicable, especially the SOP, which was mostly limited to the lower bound in literature due to the difficulty of achieving closed-from expressions. In order to validate the accuracy of our analytical results, Monte-Carlo simulations are subsequently performed for the special case $α-μ$ fading channels. One can observe perfect agreements between the exact analytical and simulation results, and highly accurate approximations between the exact and asymptotic analytical results.

cs.IT↗

arXiv2019

Blockchain-based Lightweight Authentication Mechanism for Vehicular Fog Infrastructure

With the increasing development of advanced communication technologies, vehicles are becoming smarter and more connected. Due to the tremendous growth of various vehicular applications, a huge amount of data is generated through advanced on-board devices and is deemed critical to improve driving safety and enhance vehicular services. However, cloud based models often fall short in applications where latency and mobility are critical. In order to fully realize the potential of vehicular networks, the challenges of efficient communication and computation need to be addressed. In this direction, vehicular fog computing (VFC) has emerged which extends the concept of fog computing to conventional vehicular networks. It is a geographically distributed paradigm that has the potential to conduct time-critical and data-intensive tasks by pushing intelligence (i.e. computing resources, storage, and application services) in the vicinity of end vehicles. However secure and reliable transmission are of significant importance in highly-mobile vehicular networks in order to ensure the optimal Quality of Service (QoS). In this direction, several authentication mechanisms have been proposed in the literature but most of them are found unfit due to absence of decentralization, anonymity, and trust characteristics. Thus, an effective cross-datacenter authentication and key-exchange scheme based on blockchain and elliptic curve cryptography (ECC) is proposed in this paper. Here, the distributed ledger of blockchain is used for maintaining the network information while the highly secure ECC is employed for mutual authentication between vehicles and road side units (RSUs). Additionally, the proposed scheme is lightweight and scalable for the considered VFC setup. The performance evaluation results against the existing state-of-the-art reveal that the proposed scheme accomplishes enhanced security features.

cs.NI↗

arXiv2019

An Efficient Blockchain-based Hierarchical Authentication Mechanism for Energy Trading in V2G Environment

Vehicle-to-grid (V2G) networks have emerged as a new technology in modern electric power transmission networks. It allows bi-directional flow of communication and electricity between electric vehicles (EVs) and the Smart Grid (SG), in order to provide more sophisticated energy trading. However, due to the involvement of a huge amount of trading data and the presence of untrusted entities in the visiting networks, the underlying V2G infrastructure suffers from various security and privacy challenges. Although, several solutions have been proposed in the literature to address these problems, issues like lack of mutual authentication and anonymity, incapability to protect against several attack vectors, generation of huge overhead, and dependency on centralized infrastructures make security and privacy issues even more challenging. To address the above mentioned problems, in this paper, we propose a blockchain oriented hierarchical authentication mechanism for rewarding EVs. The overall process is broadly classified into the following phases: 1) System Initialization, 2) Registration, 3) Hierarchical Mutual Authentication, and 4) Consensus; wherein blockchain's distributed ledger has been employed for transaction execution in distributed V2G environments while Elliptic curve cryptography (ECC) has been used for hierarchical authentication. The designed hierarchical authentication mechanism has been employed to preserve the anonymity of EVs and support mutual authentication between EVs, charging stations (CSs) and the central aggregator (CAG). Additionally, it also supports minimal communicational and computational overheads on resource constrained EVs. Further, formal security verification of the proposed scheme on widely accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool validates its safeness against different security attacks.

cs.NI↗

arXiv2019

An Energy-driven Network Function Virtualization for Multi-domain Software Defined Networks

Network Functions Virtualization (NFV) in Software Defined Networks (SDN) emerged as a new technology for creating virtual instances for smooth execution of multiple applications. Their amalgamation provides flexible and programmable platforms to utilize the network resources for providing Quality of Service (QoS) to various applications. In SDN-enabled NFV setups, the underlying network services can be viewed as a series of virtual network functions (VNFs) and their optimal deployment on physical/virtual nodes is considered a challenging task to perform. However, SDNs have evolved from single-domain to multi-domain setups in the recent era. Thus, the complexity of the underlying VNF deployment problem in multi-domain setups has increased manifold. Moreover, the energy utilization aspect is relatively unexplored with respect to an optimal mapping of VNFs across multiple SDN domains. Hence, in this work, the VNF deployment problem in multi-domain SDN setup has been addressed with a primary emphasis on reducing the overall energy consumption for deploying the maximum number of VNFs with guaranteed QoS. The problem in hand is initially formulated as a "Multi-objective Optimization Problem" based on Integer Linear Programming (ILP) to obtain an optimal solution. However, the formulated ILP becomes complex to solve with an increasing number of decision variables and constraints with an increase in the size of the network. Thus, we leverage the benefits of the popular evolutionary optimization algorithms to solve the problem under consideration. In order to deduce the most appropriate evolutionary optimization algorithm to solve the considered problem, it is subjected to different variants of evolutionary algorithms on the widely used MOEA framework (an open source java framework based on multi-objective evolutionary algorithms).

cs.NI↗

arXiv2019

Spectral Efficiency Analysis of the Decoupled Access for Downlink and Uplink in Two Tier Network

This paper analyzes the efficacy of decoupled wireless access in a two-tier heterogeneous network. The decoupled wireless access and its performance benefits have been studied in different scenarios recently. In this paper, an in-depth analysis on its efficacy from spectral efficiency perspective is provided. To achieve this task, (i) new closed form expressions for probability of association of user equipment with different tiers employing different frequency bands (i.e., microwave and millimeter wave) with different pathloss exponents are derived using univariate Fox's H-functions; (ii) Distributions of the distance to the serving base stations are also derived; (iii) Exact expressions of spectral efficiency for different association cases are further obtained using bivariate Fox's H-functions. Furthermore, rigorous simulation results are provided which validate the aforementioned analytical results. In addition to that, a detailed discussion on the decoupling gain of decoupled wireless access and its efficacy is also provided. Lastly, despite the improvement provided by the decoupled wireless access, which is evident from the results presented in this paper, few questions are raised on its pragmatic value.

eess.SP↗

arXiv2019

Performance Analysis of DF Cooperative Relaying over Bursty Impulsive Noise Channel

In this article, we consider the performance analysis of a decode-and-forward (DF) cooperative relaying (CR) scheme over channels impaired by bursty impulsive noise. Although, Middleton class-A model and Bernoulli-Gaussian model give good results to generate a sample distribution of impulsive noise, they fail in replicating the bursty behavior of impulsive noise, as encountered for instance within power substations. To deal with that, we adopt a two-state Markov-Gaussian process for the noise distribution. For this channel, we evaluate the bit error rate (BER) performance of direct transmission (DT) and a DF relaying scheme using M-ary phase shift keying (M-PSK) modulation in the presence of Rayleigh fading with a maximum a posteriori (MAP) receiver. From the obtained results, it is seen that the DF CR scheme in bursty impulsive noise channel still achieves the space diversity and performs significantly better than DT under the same power consumption. Moreover, the proposed MAP receiver attains the lower bound derived for DF CR scheme, and leads to large performance gains compared to the conventional receiving criteria which were optimized for additive white Gaussian noise (AWGN) channel and memoryless impulsive noise channel.

eess.SP↗

arXiv2019

Design and Performance Analysis of Secure Multicasting Cooperative Protocol for Wireless Sensor Network Applications

This paper proposes a new security cooperative protocol, for dual phase amplify-and-forward large wireless sensor networks. In such a network, a portion of the K relays can be potential eavesdroppers. The source agrees to share with the destination a given channel state information (CSI) of a source-trusted relay-destination link to encode the message. Then, in the first hop, the source will use this CSI to map the right message to a certain sector while transmitting fake messages to the other sectors using sectoral transmission thanks to analog beamforming. In the second hop, the relays retransmit their received signals to the destination, using the distributed beamforming technique. We derived the secrecy outage probability and demonstrated that the probability of receiving the right encoded information by an untrustworthy relay is inversely proportional to the number of sectors. We also showed that the aggressive behavior of the cooperating untrusted relays is not effective compared to the case where each untrusted relay is trying to intercept the transmitted message individually.

cs.CR↗

arXiv2019

Secure Transmit Antenna Selection Protocol for MIMO NOMA Networks over Nakagami-m Channels

In this paper, we studied a multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) network consisting of one source and two legitimate users (LUs), so-called near and far users according to their distances to the source, and one passive eavesdropper, over Nakagami-\textit{m} fading channel. Specifically, we investigated the scenario that the signals of the far user might or might not be decoded successfully at the eavesdropper and the near user. Thus, we aimed at designing a transmit antenna selection (TAS) secure communication protocol for the network. Then, two TAS solutions, namely Solutions I and II, were proposed. Specifically, solutions I and II focus on maximizing the received signal power between the source and the near user, and between the source and the far user, respectively. Accordingly, the exact and asymptotic closed-form expressions of the secrecy outage probability for the LUs and the overall system were derived. Our analytical results corroborated by Monte Carlo simulation indicate that the secrecy performance could be significantly improved by properly selecting power allocation coefficients and increasing the number of antennas at the source and the LUs. Interestingly, solution II could provide a better overall secrecy performance over solution I.

cs.IT↗

arXiv2019

Securing Fog-to-Things Environment Using Intrusion Detection System Based On Ensemble Learning

The growing interest in the Internet of Things (IoT) applications is associated with an augmented volume of security threats. In this vein, the Intrusion detection systems (IDS) have emerged as a viable solution for the detection and prevention of malicious activities. Unlike the signature-based detection approaches, machine learning-based solutions are a promising means for detecting unknown attacks. However, the machine learning models need to be accurate enough to reduce the number of false alarms. More importantly, they need to be trained and evaluated on realistic datasets such that their efficacy can be validated on real-time deployments. Many solutions proposed in the literature are reported to have high accuracy but are ineffective in real applications due to the non-representativity of the dataset used for training and evaluation of the underlying models. On the other hand, some of the existing solutions overcome these challenges but yield low accuracy which hampers their implementation for commercial tools. These solutions are majorly based on single learners and are therefore directly affected by the intrinsic limitations of each learning algorithm. The novelty of this paper is to use the most realistic dataset available for intrusion detection called NSL-KDD, and combine multiple learners to build ensemble learners that increase the accuracy of the detection. Furthermore, a deployment architecture in a fog-to-things environment that employs two levels of classifications is proposed. In such architecture, the first level performs an anomaly detection which reduces the latency of the classification substantially, while the second level, executes attack classifications, enabling precise prevention measures. Finally, the experimental results demonstrate the effectiveness of the proposed IDS in comparison with the other state-of-the-arts on the NSL-KDD dataset.

cs.CR↗

arXiv2019

Enhanced Minimal Scheduling Function for IEEE802.15.4e TSCH Networks

MAC layer protocol design in a WSN is crucial due to the limitations on processing capacities and power of wireless sensors. The latest version of the IEEE 802.15.4, referenced to as IEEE 802.15.4e, was released by IEEE and outlines the mechanism of the Time Slotted Channel Hopping (TSCH). Hence, 6TiSCH working group has released a distributed algorithm for neighbour nodes to agree on a communication pattern driven by a minimal scheduling function. A slotframe contains a specific number of time slots, which are scheduled based on the application requirements and the routing topology. Sensors nodes use the schedule to determine when to transmit or to receive data. However, IEEE 802.15.4e TSCH does not address the specifics on planning time slot scheduling. In this paper, we propose a distributed Enhanced Minimal Scheduling Function (EMSF) based on the minimal scheduling function, which is compliant with 802.15.4e TSCH. In this vein, we introduce a distributed algorithm based on a Poisson process to predict the following schedule requirements. Consequently, the negotiation operations between pairs of nodes to agree about the schedule will be reduced. As a result, EMSF decreases the exchanged overhead, the end-to-end latency and the packet queue length significantly. Preliminary simulation results have confirmed that EMSF outperforms the 802.15.4e TSCH MSF scheduling algorithm.

cs.NI↗

arXiv2019

Managing Fog Networks using Reinforcement Learning Based Load Balancing Algorithm

The powerful paradigm of Fog computing is currently receiving major interest, as it provides the possibility to integrate virtualized servers into networks and brings cloud service closer to end devices. To support this distributed intelligent platform, Software-Defined Network (SDN) has emerged as a viable network technology in the Fog computing environment. However, uncertainties related to task demands and the different computing capacities of Fog nodes, inquire an effective load balancing algorithm. In this paper, the load balancing problem has been addressed under the constraint of achieving the minimum latency in Fog networks. To handle this problem, a reinforcement learning based decision-making process has been proposed to find the optimal offloading decision with unknown reward and transition functions. The proposed process allows Fog nodes to offload an optimal number of tasks among incoming tasks by selecting an available neighboring Fog node under their respective resource capabilities with the aim to minimize the processing time and the overall overloading probability. Compared with the traditional approaches, the proposed scheme not only simplifies the algorithmic framework without imposing any specific assumption on the network model but also guarantees convergence in polynomial time. The results show that, during average delays, the proposed reinforcement learning-based offloading method achieves significant performance improvements over the variation of service rate and traffic arrival rate. The proposed algorithm achieves 1.17%, 1.02%, and 3.21% lower overload probability relative to random, least-queue and nearest offloading selection schemes, respectively.

cs.DC↗

arXiv2019

Robust Design of AC Computing-Enabled Receiver Architecture for SWIPT Networks

Inspired by the direct use of alternating current (AC) for computation, we propose a novel integrated information and energy receiver architecture for simultaneous wireless information and power transfer (SWIPT) networks. In this context, the AC computing method, in which wirelessly harvested AC energy is directly used to supply the computing block of receivers, enhances not only computational ability but also energy efficiency over the conventional direct current (DC) one. Further, we aim to manage the trade-off between the information decoding (ID) and energy harvesting (EH) optimally while taking imperfect channel estimation into account. It results in a worst-case optimization problem of maximizing the data rate under the constraints of an EH requirement, the energy needed for supplying the AC computational logic, and a transmit power budget. Then, we propose a method to derive closed-form optimal solutions. The numerical results demonstrate that the proposed architecture with AC computing significantly improves the rate-energy region.

cs.IT↗