Showing papers in "Telecommunication Systems in 2017"

Evolution towards fifth generation (5G) wireless networks: Current trends and challenges in the deployment of millimetre wave, massive MIMO, and small cells

Abstract: The exponential increase in mobile data traffic is considered to be a critical driver towards the new era, or 5G, of mobile wireless networks. 5G will require a paradigm shift that includes very high carrier frequency spectra with massive bandwidths, extreme base station densities, and unprecedented numbers of antennas to support the enormous increase in the volume of traffic. This paper discusses several design choices, features, and technical challenges that illustrate potential research topics and challenges for the future generation of mobile networks. This article does not provide a final solution but highlights the most promising lines of research from the recent literature in common directions for the 5G project. The potential physical layer technologies that are considered for future wireless communications include spatial multiplexing using massive multi-user multiple-input multiple-output (MIMO) techniques with millimetre-waves (mm-waves) in small cell geometries. These technologies are discussed in detail along with the areas for future research.

ICT and renewable energy: a way forward to the next generation telecom base stations

Abstract: The tremendous growth in technology is also causing global warming due to harmful greenhouse gas emissions. The Information and Communication Technology (ICT) sector is one of the fastest growing, having the greatest impact on almost every other technology. Energy efficiency and reduction in global warming is now a desire and realization by all key players associated with this technology. Not only there is scope for energy efficiency in ICTs itself but it can also help other sectors in becoming smart i.e., energy efficient. Smart buildings, smart motors, smart logistics and smart grids are being realized with the incorporation of information and communication technologies. The ICT industry is equally aware of the potential benefits of renewable energy sources (RES) in making the future systems greener and sustainable. This is quite evident from the research that is going on towards sustainable ICT solutions, as reviewed in this paper. Not only renewable energy is applicable to large scale applications like telecom base stations (BS), it is also applicable to small and medium scale systems and devices like computer peripherals and electric vehicles. In order to explore the evident potential of RES, all aspects of renewable energy are being addressed by the researchers. These aspects can broadly be categorized as generation, distribution, management and most significantly application of renewable energy. This paper takes a broader look at both aspects in which ICTs are making our world eco-sustainable i.e., making other technologies smarter and incorporating renewable energy sources wherever possible.

Novel DV-Hop localization algorithm for wireless sensor networks

Abstract: Many improved DV-Hop localization algorithm have been proposed to enhance the localization accuracy of DV-Hop algorithm for wireless sensor networks. These proposed improvements of DV-Hop also have some drawbacks in terms of time and energy consumption. In this paper, we propose Novel DV-Hop localization algorithm that provides efficient localization with lesser communication cost without requiring additional hardware. The proposed algorithm completely eliminates communication from one of the steps by calculating hop-size at unknown nodes. It significantly reduces time and energy consumption, which is an important improvement over DV-Hop--based algorithms. The algorithm also uses improvement term to refine the hop-size of anchor nodes. Furthermore, unconstrained optimization is used to achieve better localization accuracy by minimizing the error terms (ranging error) in the estimated distance between anchor node and unknown node. Log-normal shadowing path loss model is used to simulate the algorithms in a more realistic environment. Simulation results show that the performance of our proposed algorithm is better when compared with DV-Hop algorithm and improved DV-Hop--based algorithms in all considered scenarios.

Towards the fulfillment of 5G network requirements: technologies and challenges

Abstract: Future 5G networks are expected to have the capabilities of providing extremely high data rates, seamless coverage, massive number of connected devices, low latency, etc., in order to support the internet of things era. The dynamic performance of 5G networks is a key feature for controlling the dense and rapidly changing communication environment. Technical issues such as limited frequency resources, interference, energy consumption, and network management are the main challenges facing 5G networks. This article presents a comprehensive study of 5G networks architecture, technologies, challenges, and possible solutions based on recent advances in technology and research.

A survey and comparative study of QoS aware broadcasting techniques in VANET

Abstract: Vehicular ad hoc networks are a special type of MANET providing vehicle to vehicle and vehicle to roadside wireless communications. Vehicular ad-hoc network (VANET) have been designed in order to assist drivers on the road with a variety of applications especially in preventing danger and saving lives. For such ends, broadcasting is a suitable scheme to convey emergency messages dissemination to the entire network. Broadcasting in VANETs is a challenging task due to the specific VANET features such as nodes mobility and frequent topology changes. VANET applications, especially those related with human life saving, are delay sensitive and have specific requirements in terms of performances and QoS. A QoS aware broadcasting scheme relies on different factors and has to deal with hard constraints. In this paper, we introduce a survey of broadcasting in vehicular networks and discussion of different performance and QoS related to broadcasting issues. Furthermore, a comparative study of QoS aware broadcasting protocols classifying them according to different taxonomies is elaborated. This survey specifies QoS requirements and performance metrics of VANET services. Furthermore, this survey focuses on QoS aware broadcasting as a challenging problem regrading VANET characteristics.

S-Detector: an enhanced security model for detecting Smishing attack for mobile computing

Abstract: Recently the mobile computing technology has been generally used to people with the development of the IT technology. The mobile computing environment has provided a convenient environment via the intelligent devices such as tablet PC, smartphone, etc. However, many security threats in the mobile computing environment exist. Therefore, secure elements to protect against security threats are needed. In particular, Short Message Service phishing (Smishing) damage has continued to increase with the normalization of mobile computing environment. We discuss and analyze the security considerations about Smishing in mobile computing environments. In addition, we propose an enhanced security model for detecting Smishing attack (we called "S-Detector"). The proposed model is applied to a Naive Bayes classifier to improve the Smishing attack detection in smart devices. This model distinguishes normal text message and Smishing message. And this is mainly used to filter by using statistical learning method. As a result, it is possible to analyze a text message and effectively detect SMS phishing. Finally, we demonstrate the efficiency of our model through the evaluation and analysis of our proposed model.

Security assessment framework for IoT service

Abstract: What are the critical requirements to be considered for the security measures in Internet of Things (IoT) services? Further, how should those security resources be allocated? To provide valuable insight into these questions, this paper introduces a security assessment framework for the IoT service environment from an architectural perspective. Our proposed framework integrates fuzzy DEMATEL and fuzzy ANP to reflect dependence and feedback interrelations among security criteria and, ultimately, to weigh and prioritize them. The results, gleaned from the judgments of 38 security experts, revealed that security design should put more importance on the service layer, especially to ensure availability and trust. We believe that these results will contribute to the provision of more secure and reliable IoT services.

Survey of Catch-up TV and other time-shift services: a comprehensive analysis and taxonomy of linear and nonlinear television

Abstract: This study analyzes recent changes on the television (TV) market, and the transformation of TV consumption habits, motivated by new transmission and recording technologies. Through an international survey spanning 62 countries and 4 continents, a growing presence of nonlinear TV services and over-the-top (OTT) content offerings is found. A detailed taxonomy of ways of watching TV content on the TV set is proposed to clarify the existing Pay-TV and OTT services, including time-shift and video-on-demand (VoD) terms such as Pause TV, Start-over TV, personal video recorder, Catch-up TV, transaction VoD, and subscription VoD, to name a few. An in-depth literature review is conducted, focusing not only on the technological aspects of nonlinear TV, but also on its business and consumer behavior impacts. The existing research works clearly demonstrate a lack of global reach by mostly concentrating their analyses on specific regions or countries. In addition to the literature review, the survey and taxonomy definition, the impact of nonlinear TV on the complete supply chain is also extensively discussed, indicating structural changes not yet addressed in the current literature.

Exact solutions for M/M/c/Setup queues

Abstract: Recently multiserver queues with setup times have been extensively studied because they have applications in power-saving data centers. A challenging model is the M/M/c/Setup queue where a server is turned off when it is idle and is turned on if there are some waiting jobs. Recently, Gandhi et al. (in: Proceedings of the ACM SIGMETRICS, pp. 153---166, ACM, 2013; Queueing Syst. 77(2):177---209, 2014) obtain the generating function of the number of jobs in the system, as well as the Laplace transform of the response time using the recursive renewal reward approach and the distributional Little's law (Keilson and Servi in Oper Res Lett 7(5):223--- 227, 1988). In this paper, we derive exact solutions for the joint stationary queue length distribution of the same model using two alternative methodologies: generating function approach and matrix analytic method. The generating function approach yields exact closed form expressions for the joint stationary queue length distribution and the conditional decomposition formula. On the other hand, the matrix analytic approach leads to an exact recursive algorithm to calculate the joint stationary distribution and performance measures so as to provide some application insights.

RMRPTS: a reliable multi-level routing protocol with tabu search in VANET

Abstract: Vehicular ad hoc network (VANET), a subclass of mobile ad hoc networks (MANETs), is a promising approach for the intelligent transportation system (ITS). One of the main challenges in VANETs is establishment of vehicular communication and stable routing. Another problem of VANETs is their tendency of being trapped in a local optimum. In this paper, a reliable multi-level routing protocol based on clustering, RMRPTS has been introduced in VANETs. Even if this topology constantly changes, clustering based multi-level routing will create the possibility of self-organization and route maintaining; moreover, it will solve the problem of developing a trap in the local optimum using tabu search. At the first level, the proposed protocol is an extension of AODV routing protocol that has been improved using fuzzy logic in order to create reliable routing between cluster members. Tabu search has been used at a higher level for routing between cluster heads and destination. Tabu search is a meta-heuristic improved learning method used for solving hybrid optimization problems, and it uses cost function to select a solution among a set of possible solutions. The effective parameters used in the proposed method to select the best path include nodes distance, the velocity of nodes, node's angle, link stability, and link reliability. The proposed protocol was simulated using an NS-2 simulator, and the results of its performance showed increased average packet delivery rate and decreased average end to end delays, number of packet losses compared with earlier protocols.

Handover in LTE-advanced wireless networks: state of art and survey of decision algorithm

Abstract: The increasing demand for mobile communication calls for improvements to network operating services in terms of capacity, coverage, and Quality of Services (QoS). Ensuring QoS is one of the challenges faced by wireless network operators, which include the provision of high mobility speeds, thus the implementation of a seamless and fast handover between network cells is a prominent issue that must be addressed, especially when fulfilling QoS prerequisites. Long Term Evolution (LTE)/LTE-Advance has met these demands of QoS through the use of a new Radio Access Network and distribution of Radio Resource Management including the handover decision technique to evolve NodeB instead of relying on centralized control. In this paper, we review the control plane structure of LTE/LTE-A and present a comprehensive discussion of handover procedures such as the phases, techniques, requirements, features, and challenges involved. According to the overview of the handover decision phase, we surveyed and classified the present handover decision algorithms for a LTE-A system-based technology in regard to the primary handover decision technique. For each class, we describe in detail the fundamental operations and decision parameters using representative algorithms. A summary of input parameters, techniques, and performance evaluation of the handover decision algorithms concludes this work.

Monkey King Evolution: an enhanced ebb-tide-fish algorithm for global optimization and its application in vehicle navigation under wireless sensor network environment

Abstract: Optimization algorithms are proposed to maximize the desirable properties while simultaneously minimizing the undesirable characteristics. Particle Swarm Optimization (PSO) is a famous optimization algorithm, and it has undergone many variants since its inception in 1995. Though different topologies and relations among particles are used in some state-of-the-art PSO variants, the overall performance on high dimensional multimodal optimization problem is still not very good. In this paper, we present a new memetic optimization algorithm, named Monkey King Evolutionary (MKE) algorithm, and give a comparative view of the PSO variants, including the canonical PSO, Inertia Weighted PSO, Constriction Coefficients PSO, Fully-Informed Particle Sawrm, Cooperative PSO, Comprehensive Learning PSO and some variants proposed in recent years, such as Dynamic Neighborhood Learning PSO, Social Learning Particle Swarm Optimization etc. The proposed MKE algorithm is a further work of ebb-tide-fish algorithm and what's more it performs very well not only on unimodal benchmark functions but also on multimodal ones on high dimensions. Comparison results under CEC2013 test suite for real parameter optimization show that the proposed MKE algorithm outperforms state-of-the-art PSO variants significantly. An application of the vehicle navigation optimization is also discussed in the paper, and the conducted experiment shows that the proposed approach to path navigation optimization saves travel time of real-time traffic navigation in a micro-scope traffic networks.

A churn prediction model for prepaid customers in telecom using fuzzy classifiers

Abstract: The incredible growth of telecom data and fierce competition among telecommunication operators for customer retention demand continues improvements, both strategically and analytically, in the current customer relationship management (CRM) systems. One of the key objectives of a typical CRM system is to classify and predict a group of potential churners form a large set of customers to devise profitable and targeted retention campaigns for keeping a long-term relationship with valued customers. For achieving the aforementioned objective, several churn prediction models have been proposed in the past for the accurate identification of the customers who are prone to churn. However, these previously proposed models suffer from a number of limitations which place strong barriers towards the direct applicability of such models for accurate prediction. Firstly, the feature selection methods adopted in majority of the past work neglected the information rich variables present in call details record for model development. Secondly, selection of important features was done through statistical methods only. Although statistical methods have been applied successfully in diverse domains, however, these methods alone without the augmentation of domain knowledge have the tendency to yield erroneous results. Thirdly, the previous models have been validated mainly with benchmark datasets which do not provide a true representation of real world telecom data consisting of noise and large number of missing values. Fourthly, the evaluation measures used in the past neglected the True Positive (TP) rate, which actually highlights the ability of a model to correctly classify the percentage of churners as compared to non-churners. Finally, the classifiers used in the previous models completely neglected the use of fuzzy classification methods which perform reasonably well for data sets with noise. In this paper, a fuzzy based churn prediction model has been proposed and validated using a real data from a telecom company in South Asia. A number of predominant classifiers namely, Neural Network, Linear regression, C4.5, SVM, AdaBoost, Gradient Boosting and Random Forest have been compared with fuzzy classifiers to highlight the superiority of fuzzy classifiers in predicting the accurate set of churners.

EIAS-CP: new efficient identity-based authentication scheme with conditional privacy-preserving for VANETs

Abstract: In VANETs, vehicles broadcast traffic-related messages periodically according to Dedicated Short Range Communication protocol. To ensure the reliability and integrity of messages, authentication schemes are involved in VANETs. As traffic-related messages are time-sensitive, they must be verified and processed timely, or it may cause inestimable harm to the traffic system. However, the OBUs and the RSUs are limited in computation ability and cannot afford vast messages' verification. Recently, some identity-based authentication schemes using bilinear pairing have been proposed to improve the efficiency of message verification for VANETs. Nevertheless, the bilinear pairing is not suited for VANETs due to its complex operations. The design of an efficient and secure authentication scheme with low computation cost for VANETs still is a rewarding challenge. To settle this challenge, a new efficient identity-based authentication scheme is proposed in this paper. The proposed scheme ensures reliability and integrity of messages and provides conditional privacy-preserving. Compared with the most recent proposed authentication schemes for VANETs, the computation costs of the message signing and verification in the proposed scheme reduce by 88 and 93 % respectively, while security analysis demonstrates that our proposed scheme satisfies all security and privacy requirements for VANETs.

Radio communication via Near Vertical Incidence Skywave propagation: an overview

Abstract: Near Vertical Incidence Skywave (NVIS) propagation can be used for radio communication in a large area (200 km radius) without any intermediate man-made infrastructure. It is therefore especially suited for disaster relief communication, communication in developing regions and applications where independence of local infrastructure is desired, such as military applications. NVIS communication uses frequencies between approximately 3 and 10 MHz. A comprehensive overview of NVIS research is given, covering propagation, antennas, diversity, modulation and coding. Both the bigger picture and the important details are given, as well as the relation between them.

Adaptive hybrid free space optical/radio frequency communication system

Abstract: Wireless communication has achieved lot of attention and the demand is continually increasing day by day. Radio frequency (RF) is highly attracted by various wireless communication applications. The RF spectrum is already very crowded and the rapid increase in the use of wireless services has led the problems of RF spectrum exhaustion and eventually RF spectrum deficit. Free space optical (FSO) communication is a viable technology with a plenty of bandwidth, license-free spectrum and interference free link. On the other hand, FSO channel is severely corrupted by atmospheric turbulence and non-predictive weather scenarios. We suggest a hybrid FSO/RF communication system in our previous research, which can mitigate the issues of the individual links. In this research, we investigate the performance of the proposed adaptive system for reliable data transmission. We develop modulation and power adaptive schemes for maximizing the mutual information. The proposed adaptive system is compared with non-adaptive system, which gives 2.75 dB gain for the joint power and 0.75 dB gain for the separate power constraint.

An improved DV-Hop localization algorithm based on evolutionary algorithms

Abstract: Localization is one of the most important issues in wireless sensor networks and designing accurate localization algorithms is a common challenge in recent researches. Among all localization algorithms, DV-Hop attracts more attention due to its simplicity; so, we use it as a basis for our localization algorithm in order to improve accuracy. The various evolutionary algorithms such as Genetic, Shuffled Frog Leaping and Particle Swarm Optimization are employed in different phases of the main DV-Hop localization algorithm. Simulation results prove that our proposed method decreases the localization error efficiently without additional hardware.

Multilevel heterogeneous network model for wireless sensor networks

Abstract: The lifetime of a network can be increased by increasing the network energy. The network energy can be increased either increasing the number of sensors or increasing the initial energy of some sensors without increasing their numbers. Increasing network energy by deploying extra sensors is about ten times costlier than that using some sensors of high energy. Increasing the initial energy of some sensors leads to heterogeneous nodes in the network. In this paper, we propose a multilevel heterogeneous network model that is characterized by two types of parameters: primary parameter and secondary parameters. The primary parameter decides the level of heterogeneity by assuming the values of secondary parameters. This model can describe a network up to nth level of heterogeneity (n is a finite number). We evaluate the network performance by applying the HEED, a clustering protocol, on this model, naming it as MLHEED (Multi Level HEED) protocol. For n level of heterogeneity, this protocol is denoted by MLHEED-n. The numbers of nodes of each type in any level of heterogeneity are determined by the secondary model parameter. The MLHEED protocol (for all level heterogeneity) considers two variables, i.e., residual energy and node density, for deciding the cluster heads. We also consider fuzzy implementation of the MLHEED in which four variables are used to decide the cluster heads: residual energy, node density, average energy, and distance between base station and the sensor nodes. In this work, we illustrate the network model up to seven levels ($$1\le n\le 7$$1≤n≤7). Experimentally, as the level of heterogeneity increases, the rate of energy dissipation decreases and hence the nodes stay alive for longer time. The MLHEED-m, $$m=2,3,4,5,6,7$$m=2,3,4,5,6,7, increase the network lifetime by $$73.05, 143.40, 213.17, 267.90, 348.60, 419.10\,\%$$73.05,143.40,213.17,267.90,348.60,419.10%, respectively, by increasing the network energy as $$40, 57, 68.5, 78, 84, 92.5\,\%$$40,57,68.5,78,84,92.5% with respect to the original HEED protocol. In case of fuzzy implementation, the MLHEEDFL-m, $$m=2,3,4,5,6,7,$$m=2,3,4,5,6,7, increases the network lifetime by $$282.7, 378.5, 435.78, 498.50, 582.63, 629.79\,\%$$282.7,378.5,435.78,498.50,582.63,629.79%, respectively, corresponding to the same increase in the network energy as that of the MLHEED (all levels) with respect to the original HEED. The fuzzy implementation of the HEED, MLHEEDFL-1, increases the network lifetime by $$176.6\,\%$$176.6% with respect to the original HEED with no increase in the network energy.

ReIDD: reliability-aware intelligent data dissemination protocol for broadcast storm problem in vehicular ad hoc networks

Abstract: Vehicular ad hoc networks (VANETs) have emerged as fast growing networks with aims to provide safety, and comfort to the onboard passengers. But, in this environment reliable data dissemination to the destination nodes is one of the biggest challenges as there may be a congestion in the network due to blind flooding of messages to their final destination, called as broadcast storm which may lead to the performance degradation with respect to the metric such as-message delivery, reliability and response time. To address this issue, in this paper, we propose a reliability-aware intelligent data dissemination protocol for broadcast storm problem in VANETs. We have solved the above specified problem using game theory concepts in which players, strategy space and decisions with respect to the current state of the system. To reduce the message overhead with respect to the communication cost among the players of the game, in the proposed scheme, messages are routed to the next destination by selecting the most reliable path in an intelligent manner. A coalition game is formulated among the vehicles by considering vehicles as the players in the game. Each player in the game has an initial payoff value based upon the parameters such as-communication range, storage requirements, and computation power. Based upon the payoff value of the players in the game, different coalitions/clusters are formulated among the players in the proposed scheme. Then, the players send the messages to the other vehicles/players within the same coalition which increases the reliability of transmission. In the proposed scheme, messages are unicasted to their final destination in an intelligent manner. Different algorithms are designed for coalition formation, maintenance, and reliability-aware data dissemination. The performance of the proposed scheme is evaluated using various evaluation metrics such as-service time, packet delivery ration, and throughput. The results obtained prove the effectiveness of the proposed scheme as compared to the other state-of-the-art existing schemes.

G-FANET: an ambient network formation between ground and flying ad hoc networks

Abstract: Networking with aerial vehicles has evolved considerably over a period of time. Its applications range across a wide spectrum covering areas of military and civilian activities. Connectivity between aerial vehicles in ad hoc mode allows formation of multiple control units in the sky which have an ability to handle complex tasks. One of the major applications of these aerial vehicles is to coordinate simultaneously with another ad hoc network operating on the ground. This formation is termed as cooperative ad hoc networking. These networks operate on multiple data-sharing in form of cognitive maps. Thus, an efficient traffic management strategy is required to form a robust network. In this paper, an ambient network framework for coordination between ground and flying ad hoc network is presented. A fault-tolerant and robust connectivity strategy is proposed using neural, fuzzy and genetic modules. quaternion Kalman filter and its variant $$\alpha -\beta -\gamma $$?-s-? filter is used to form the neural and decision system for guided aerial network. Effectiveness of the proposed traffic management framework for aerial vehicles is presented using mathematical simulations.

Adaptive mean queue size and its rate of change: queue management with random dropping

Abstract: The random early detection active queue management (AQM) scheme uses the average queue size to calculate the dropping probability in terms of minimum and maximum thresholds. The effect of heavy load enhances the frequency of crossing the maximum threshold value resulting in frequent dropping of the packets. An adaptive queue management with random dropping algorithm is proposed which incorporates information not just about the average queue size but also the rate of change of the same. Introducing an adaptively changing threshold level that falls in between lower and upper thresholds, our algorithm demonstrates that these additional features significantly improve the system performance in terms of throughput, average queue size, utilization and queuing delay in relation to the existing AQM algorithms.

ESSPR: an efficient secure routing scheme based on searchable encryption with vehicle proxy re-encryption for vehicular peer-to-peer social network

Abstract: In this paper, we propose an Efficient Secure routing Scheme based on searchable encryption with vehicle Proxy Re-encryption, called ESSPR, for achieving privacy preservation of message in vehicular peer-to-peer social network (VP2PSN). Specifically, the proposed ESSPR scheme consists of six phases: system initializations phase, peer registration phase, document generation phase, document forwarding phase, vehicle proxy re-encryption phase, and document receiving phase. Based on rationale of QoS-based clustering strategy, public key encryption with keyword search, identity based aggregate signature, and proxy re-encryption, ESSPR provides privacy for keyword, privacy for resources, and authentication and data integrity of the demand’s source. In addition, ESSPR is robust against eavesdropping attack, wormhole attack, packet analysis attack, packet tracing attack, and replay attack. Through performance evaluation, we demonstrate the effectiveness of ESSPR in terms of delivery ratio, average delay, average fairness, and detection ratio under malicious peers proportions in VP2PSN.

Energy detector based TOA estimation for MMW systems using machine learning

Abstract: 60 GHz millimeter wave signals can provide precise time and multipath resolution and so have great potential for accurate time of arrival (TOA) and range estimation. To improve TOA estimation, a new energy detector based threshold selection algorithm which employs a neural network is proposed. The minimum slope, kurtosis, and skewness of the received energy block values are used to determine the normalized thresholds for different signal-to-noise ratios (SNRs). The effects of the channel and integration period are evaluated. Performance results are presented which show that the proposed approach provides better precision and is more robust than other solutions over a wide range of SNRs for the CM1.1 and CM2.1 channel models in the IEEE 802.15.3c standard.

Hierarchical distributed management clustering protocol for wireless sensor networks

Abstract: In recent years, there has been a marked increase in the use of wireless sensor networks in various environments such as crisis areas, military operations, and monitoring systems. These networks do not use a fixed network infrastructure and therefore they are a popular choice for highly dynamic environments. One of the main concerns in these networks is the topology management issue, which the clustering method is a subfield for that. The main objective of clustering methods is optimizing the energy consumption. This paper proposes a new clustering protocol, which uses many parameters such as the activity history of each node, local and general state of nodes and their resources condition to determine the best cluster heads and members of each cluster that can increase the network lifetime, fair resource consumption and network coverage.

Secure and distributed certification system architecture for safety message authentication in VANET

Abstract: Vehicular Ad hoc NETworks (VANETs) are a burgeoning research focus, aimed at creating communication among vehicles to improve the road safety and enhance driving conditions. For such networks, security is one of the most challenging issues due to their nature of wireless transmission and high topology changing frequency. In this paper, we propose a secure and distributed certification system architecture for safety message authentication in VANET, which resists against false public-key certification. To increase the availability of the authentication service, our proposal is designed through a decentralized system, supervised by a root authority. The latter authority delegates to a set of regional certification authorities the privilege of issuing public-key certificates to the vehicles. Each regional certification authority cooperates with its subordinates RSUs to sign public-key certificates using threshold signature. The main purpose of our solution is to ensure the messages authentication while respecting the imposed constraints by the real-time aspect and the nodes mobility. We demonstrate through the practical analysis and simulation results the efficiency of our solution with comparison to other concurrent protocols.

Fast handover solution for network-based distributed mobility management in intelligent transportation systems

Abstract: The current IP mobility protocols are called centralized mobility management (CMM) solutions, in which all data traffic and management signaling messages must be forwarded to an anchor entity. In some vehicle scenarios, vehicles may move as a group from one roadside unit to another (i.e., after traffic lights or traffic jams). This causes data traffic and exchanged mobility messages to peak at the anchor entity and, consequently, affects the network performance. A new design paradigm aimed at addressing the anchor entity issue is called distributed mobility management (DMM); it is an IETF proposal that is still being actively discussed by the IETF DMM working group. Nevertheless, network-based DMM is designed based on the well-known network-based CMM protocol Proxy Mobile IPv6 (PMIPv6). There is no significant difference between network-based DMM and PMIPv6 in terms of handover latency and packet loss. Because vehicles change their roadside unit frequently in this context, the IP addresses of mobile users (MUs) require fast IP handover management to configure a new IP address without disrupting ongoing sessions. Thus, this paper proposes the Fast handover for network-based DMM (FDMM) based on the Fast Handover for PMIPv6 (PFMIPv6). Several modifications to PFMIPv6 are required to adapt this protocol to DMM. This paper specifies the necessary extensions to support the scenario in which an MU has old IP flows and hence has multiple anchor entities. In addition, the analytic expressions required to evaluate and compare the handover performance of the proposed FDMM and the IETF network-based DMM have been derived. The numerical results show that FDMM outperforms the IETF network-based DMM in terms of handover latency, session recovery and packet loss at the cost of some extra signaling.

Fusion of confusion and diffusion: a novel image encryption approach

Abstract: Recently, the development of confidentiality and authenticity ensured by image encryption has been one of the key advancements in the field of secured wireless communication. The proposed work focuses on providing confusion, diffusion and permutation inherently in the system. The input grayscale image is shuffled by employing the Henon algorithm and subsequently separated into 8 bit planes. With the aid of a secret key of 256 bits, chaotic sequences are generated for each bit plane. Later, the logistic map is adapted on the chaotic sequences to obtain the scrambled image. Furthermore, this image is shuffled with Zaslavskii and Hilbert Space Filling Curve algorithms, which establishes the confusion stage. To incorporate the diffusion stage, a self-invertible matrix is generated by a latin square image cipher and a secret key. This matrix and the scrambled image underwent the Hill cipher to build the encrypted image followed by a row-column transformation to ensure multifold security. The proposed compound activities of encryption are successfully implemented on the laboratory virtual instrumentation engineering workbench 2013 platform. Noticeably, the established processes of image encryption are tested in the universal software radio peripheral environment and transceived via an additive white Gaussian noise (AWGN) channel. More specifically, the influence of natural and unnatural (cropping attack) noise on the characteristics of the encrypted image while sharing through AWGN channel has been investigated. Security analysis is performed by computing the unified average changing intensity, number of pixels change rate, correlation value, large key space to defy brute force attack, strong key sensitivity and uniform gray value distribution on encryption.

Smart heterogeneous networks: a 5G paradigm

Abstract: An exponential growth in data demand on wireless networks and wireless link capacity approaching its theoretical limits, bound us to find new solutions and innovative network designs to handle the enormous amount of traffic. In this paper, we discuss long term evolution-advance (LTE-A) heterogeneous networks (HetNets) being a most effective solution to break this wireless cellular capacity crunch. LTE-A HetNets provide adequate increase in capacity by utilizing multi-tier architecture consisting of different type of cells i.e macro cell, small cell, relay and device to device. However this increase in capacity comes with certain challenges in HetNets outlined in this article. Considering inter cell interference coordination (ICIC) as biggest challenge in LTE-A HetNets, this article surveys state of the art LTE-A HetNets deployments with focus on ICIC. Effective ICIC techniques allow further substantial capacity increase. We give state of the art ICIC on air-interface as well as backhaul strategies for effective ICIC in LTE-A HetNets. Operators perspective of LTE-A HetNets with some insight to future of 5G LTE-A HetNets is provided. We also provide simulation results to show how LTE-A HetNets lead to realize ambitious targets of 5G technology in terms of capacity.

Analytical modelling of multiservice switching networks with multiservice sources and resource management mechanisms

Abstract: This article proposes a new analytical method of determining occupancy distribution and blocking probability in multiservice switching networks with admission control mechanisms and resource management mechanisms. The proposed method is a universal one, which allows for determining blocking probability using the same model, regardless of the type of admission control mechanisms and resource management mechanisms. The versatility of the method is demonstrated in the article for two selected mechanisms, i.e. a threshold mechanism and a resource reservation mechanisms. The switching networks under consideration are offered multiservice traffic streams, generated by the so-called multiservice sources, according to Erlang, Engset and Pascal distributions. The proposed method is based on a generalised way of determining traffic characteristics for inter-stage links of switching networks with resource and call management mechanisms. Particular attention is given to determining the influence of the introduced mechanisms in outgoing links of the switching network on the traffic properties of inter-stage links of the network. The results of analytical calculations are then compared with the results obtained in digital simulation for a number of selected switching networks.

Active queue management algorithm based on data-driven predictive control

Abstract: Model predictive control (MPC) is a popular strategy for active queue management (AQM) that is able to incorporate physical and user defined constraints. However, the current MPC methods rely on explicit fluid model of TCP behavior with input time delay. In this paper, we propose a novel AQM algorithm based on data-driven predictive control, called Data-AQM. For Internet system with large delay, complex change and bad disturbance, data-driven predictive controller can be obtained directly based on the input---output data alone and does not require any explicit model of the system. According to the input---output data, the future queue length in data buffer, which is the basis of optimizing drop probability, is predicted. Furthermore, considering system constraints, the control requirement is converted to the optimal control objective, then the drop probability is obtained by solving the optimal problem online. Finally, the performances of Data-AQM are evaluated through a series of simulations.