Showing papers by "Mohsen Guizani published in 2016"

A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks

Abstract: Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the mobile anchor node assisted localization (MANAL) problem. However, to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.

Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges

Abstract: The rapid advancements in communication technologies and the explosive growth of the Internet of Things have enabled the physical world to invisibly interweave with actuators, sensors, and other computational elements while maintaining continuous network connectivity. The continuously connected physical world with computational elements forms a smart environment. A smart environment aims to support and enhance the abilities of its dwellers in executing their tasks, such as navigating through unfamiliar space and moving heavy objects for the elderly, to name a few. Researchers have conducted a number of efforts to use IoT to facilitate our lives and to investigate the effect of IoT-based smart environments on human life. This article surveys the state-of-the-art research efforts to enable IoT-based smart environments. We categorize and classify the literature by devising a taxonomy based on communication enablers, network types, technologies, local area wireless standards, objectives, and characteristics. Moreover, the article highlights the unprecedented opportunities brought about by IoT-based smart environments and their effect on human life. Some reported case studies from different enterprises are also presented. Finally, we discuss open research challenges for enabling IoT-based smart environments.

Network function virtualization in 5G

Abstract: 5G wireless technology is paving the way to revolutionize future ubiquitous and pervasive networking, wireless applications, and user quality of experience. To realize its potential, 5G must provide considerably higher network capacity, enable massive device connectivity with reduced latency and cost, and achieve considerable energy savings compared to existing wireless technologies. The main objective of this article is to explore the potential of NFV in enhancing 5G radio access networks' functional, architectural, and commercial viability, including increased automation, operational agility, and reduced capital expenditure. The ETSI NFV Industry Specification Group has recently published drafts focused on standardization and implementation of NFV. Harnessing the potential of 5G and network functions virtualization, we discuss how NFV can address critical 5G design challenges through service abstraction and virtualized computing, storage, and network resources. We describe NFV implementation with network overlay and SDN technologies. In our discussion, we cover the first steps in understanding the role of NFV in implementing CoMP, D2D communication, and ultra densified networks.

Advanced spectrum sharing in 5G cognitive heterogeneous networks

Abstract: Spectrum utilization, energy consumption, and cost efficiency are three key performance metrics that should be jointly investigated in developing a sustainable 5G system. Advanced spectrum sharing can enhance both the spectral efficiency and energy efficiency in a cost-effective manner, which is expected to perform much better than conventional networks. In this article, we survey cognitive and cooperative spectrum sharing, and classify a multi-level spectrum exploitation, coordination, and utilization framework from both technical and economic perspectives. We specifically concentrate on spectrum trading and leasing, spectrum mobility, relaying, routing, and harvesting. Finally, a spectrum flowing scheme is proposed for 5G cognitive heterogeneous cellular networks, which improves both spectral and energy efficiency.

On WiFi Offloading in Heterogeneous Networks: Various Incentives and Trade-Off Strategies

Abstract: Due to the rapid development of wireless access technologies and smart terminals, mobile data traffic is continuously increasing, which is expected to lead to an explosive growth of data in heterogeneous networks especially cellular networks. It is significant for network operators to expand the capacity of cellular networks to avoid congestion and overload so as to guarantee users’ satisfaction. Given that contemporary terminals are capable of both WiFi and cellular networks, WiFi offloading is envisioned as a promising solution to utilize the various benefits of WiFi and cellular networks to migrate traffic from cellular networks to WiFi networks. This paper surveys the state-of-the-art progress in the field of WiFi offloading. After discussing the requirements from the emerging 5G technology regarding the coexistence of WiFi and cellular networks, selecting and switching schemes are presented. The bandwidth and capacity of WiFi networks are usually excellent, whereas the coverage and energy efficiency may be unacceptable. We elaborate on several existing solutions of WiFi offloading schemes and discuss how the parameters of several kinds of heterogeneous networks affect the offloading decision. We also illustrate how multiple networks cooperate in heterogeneous networks in order to balance the offloading performance. We classify current various incentives of WiFi offloading into five categories: 1) capacity; 2) cost; 3) energy; 4) rate; and 5) continuity. Improving the capacity is the basic incentive, which can be further classified in terms of delay techniques. From operators’ and users’ perspectives, we also investigate various state-of-the-art incentives of WiFi offloading such as minimizing cost, saving energy consumption, and improving rate. Furthermore, WiFi offloading schemes that attempt to enhance continuity to deal with frequent disruption problems are further investigated, especially for vehicular scenarios. Finally, future research directions and challenges for WiFi offloading strategies are presented in various incentives of WiFi offloading.

Reinforcement learning for resource provisioning in the vehicular cloud

Abstract: This article presents a concise view of vehicular clouds that incorporates various vehicular cloud models that have been proposed to date. Essentially, they all extend the traditional cloud and its utility computing functionalities across the entities in the vehicular ad hoc network. These entities include fixed roadside units, onboard units embedded in the vehicle, and personal smart devices of drivers and passengers. Cumulatively, these entities yield abundant processing, storage, sensing, and communication resources. However, vehicular clouds require novel resource provisioning techniques that can address the intrinsic challenges of dynamic demands for the resources and stringent QoS requirements. In this article, we show the benefits of reinforcement-learning-based techniques for resource provisioning in the vehicular cloud. The learning techniques can perceive long-term benefits and are ideal for minimizing the overhead of resource provisioning for vehicular clouds.

Replisom : Disciplined Tiny Memory Replication for Massive IoT Devices in LTE Edge Cloud

Abstract: Augmenting the long-term evolution (LTE)-evolved NodeB (eNB) with cloud resources offers a low-latency, resilient, and LTE-aware environment for offloading the Internet of Things (IoT) services and applications. By means of devices memory replication, the IoT applications deployed at an LTE-integrated edge cloud can scale its computing and storage requirements to support different resource-intensive service offerings. Despite this potential, the massive number of IoT devices limits the LTE edge cloud responsiveness as the LTE radio interface becomes the major bottleneck given the unscalability of its uplink access and data transfer procedures to support a large number of devices that simultaneously replicate their memory objects with the LTE edge cloud. We propose Replisom ; an LTE-aware edge cloud architecture and an LTE-optimized memory replication protocol which relaxes the LTE bottlenecks by a delay and radio resource-efficient memory replication protocol based on the device-to-device communication technology and the sparse recovery in the theory of compressed sampling. Replisom effectively schedules the memory replication occasions to resolve contentions for the radio resources as a large number of devices simultaneously transmit their memory replicas. Our analysis and numerical evaluation suggest that this system has significant potential in reducing the delay, energy consumption, and cost for cloud offloading of IoT applications given the massive number of devices with tiny memory sizes.

Cooperative earth observation through complex space information networks

Abstract: Space-based information networking (SBIN) was proposed to broaden the observation area and realize continuous information acquisition for Earth observation It is corroborated to be able to enhance the detection and transmission capabilities of the current single Earth observation satellite To achieve this goal, there are many new challenges for the SBIN to implement a cooperative observation and transmission scheme First, to establish this comprehensive and heterogeneous space network, the design of the network architecture plays a key role Meanwhile, how to transmit the Earth observation data back to the satellite ground station in due time can cause routing problems for the SBIN Moreover, modeling and solving the planning and scheduling problems for the SBIN are complex issues because of the differences among the satellite and inter-satellite link state performance, the users’ demands, and the uncertain space environment In this article, we introduce and survey the aforementioned three issues from the perspectives of cooperative observation of the SBIN In particular, we first discuss the current space-based networking technology and inter-satellite routings Then we address the cooperative Earth observation model and show our research results

Cooperation for spectral and energy efficiency in ultra-dense small cell networks

Abstract: Extensive deployment of small cells in heterogenous cellular networks introduces both challenges and opportunities. Challenges come with reuse of limited frequency resources, which always introduce both intra- and inter-interference among small cells and macrocells. The opportunities refer to more potential inter- and intra-tier cooperation gains, in particular for ultra-dense heterogeneous and small cell networks. In addition to current spectral efficiency optimization, energy efficiency will also be a critical performance requirement for future green communications, especially when small cells are densely deployed to enhance the user’s quality of experience. In this article, potential cooperation gains are explored via a cooperative bargaining game to counter challenges of mitigating interference and saving energy, thus improving both spectral and energy efficiency. We survey the current optimization and trade-offs of spectral and energy efficiency, and introduce the basics of cooperative game theory. Then a utility function is presented with spectral and energy efficiency coupled together. Furthermore, we present the bargaining cooperative game theoretic framework to explore potential cooperation gains. Moreover, two applications are investigated for the dedicated and co-channel deployment cases, including cooperative relay with spectrum leasing and cooperative capacity offload. Finally, we conclude the article with potential challenges of the presented cooperative framework and some thoughts for future research directions.

Green Routing Protocols for Wireless Multimedia Sensor Networks

Abstract: Wireless multimedia sensor networking (WMSN) is an efficient technology and has been widely used in multimedia data transport and applications. The key to the success of multimedia data transport is the transmission quality. Real-time critical multimedia requires efficient routing for data delivery with guaranteed QoS. However, satisfying the stringent QoS requirements of multimedia transmission usually translates to high energy consumption. How to efficiently minimize the energy consumption while ensuring QoS requirements is an acute problem. Therefore, in this article, we call routing protocols that can balance out the trade-off between network lifetime and QoS requirements “green routing protocols.” First, a detailed survey of existing routing protocols for WMSNs is presented, which are classified into two categories based on network structures. Moreover, the performance of existing routing protocols is compared in detail. Finally, future research issues of green routing protocols in WMSNs are presented and carefully discussed.

Joint Power Coordination for Spectral-and-Energy Efficiency in Heterogeneous Small Cell Networks: A Bargaining Game-Theoretic Perspective

Abstract: Extensive deployment of small cells in heterogenous cellular networks introduces both challenges and opportunities. Challenges come with the reuse of the limited frequency resource for improving spectral efficiency, which always introduces serious mutual inter- and intracell interference between or among small cells and macrocells. The opportunities refer to more potential chances of inter- and intratier cooperations among small cells and macrocells. Energy efficiency will be a critical performance requirement for future green communications, especially when small cells are densely deployed to enhance the quality of user’s experience. We exploit the potential cooperation diversities to combat the interference and energy management challenges. To capture the complicated interference interaction and also the possible coordination behavior among small cells and macrocells, this paper proposes a novel bargaining cooperative game (BCG) framework for energy efficient and interference-aware power coordination in a dense small cell network. In particular, a new adjustable utility function is employed in the BCG framework to jointly address both the spectral efficiency and energy efficiency issues. Using the BCG framework, we then derive the closed-form power coordination solutions and further propose a joint interference-aware power coordination scheme (Joint) with the considerations of both interference mitigation and energy saving. Moreover, a simplified algorithm (Simplified) is presented to combat the heavy signaling overhead, which is one of the significant challenges in the scenario of extensive deployment of small cells. Finally, numerical results are provided to illustrate the effectiveness of the proposed Joint and Simplified schemes.

Cloud of Things for Sensing-as-a-Service: Architecture, Algorithms, and Use Case

Abstract: We propose Cloud of Things for sensing-as-a-service: a global architecture that scales up cloud computing by exploiting the global sensing resources of the Internet of Things (IoT) to enable remote sensing. Cloud of Things enables in-network distributed processing of sensors data offered by the globally available IoT devices and provides a global platform for meaningful and responsive data analysis and decision making. We propose a distributed sensing resource discovery and virtualization algorithms that efficiently deploy virtual sensor networks on top of a subset of the selected IoT devices. We show, through analysis and simulations, the potential of the proposed solutions to realize virtual sensor networks with minimal physical resources, reduced communication overhead, and low complexity. We also design an uncoordinated, distributed algorithm that relies on the selected sensors to estimate a set of parameters without requiring synchronization among the sensors. Our simulations show that the proposed estimation algorithm, when compared to conventional alternating direction method of multipliers (ADMMs), reduces communication overhead significantly without compromising the estimation error. In addition, the convergence time, though increases slightly, is still linear as in the case of conventional ADMM.

Delay-Aware Energy Optimization for Flooding in Duty-Cycled Wireless Sensor Networks

Abstract: Flooding, by which the sink node broadcasts messages to the entire network, is an important and common operation in wireless sensor networks (WSNs). The emerging synchronous duty-cycled wakeup schedules together with the unreliable communication of WSNs post new challenges for efficient broadcast protocol design, and the existing methods are not appropriate to address this problem. This paper proposes a delay-aware energy-optimized flooding algorithm (DEF) tailored for synchronous duty-cycled WSNs, which can act as an enhanced scheme for most flooding trees. DEF globally adjusts a constructed flooding tree, to maximize the energy efficiency improvement while following the delay constraint. To this end, we first remodel the flooding problem in the new context mathematically. Then, we introduce a routing metric, which fully utilizes the features of synchronous duty-cycled WSNs for energy optimization, and design an effective delay-aware tree adjusting approach. Extensive evaluation results demonstrate that DEF could save considerable energy, while the flooding delay keeps unchanged or even decreases slightly. In addition, a modified minimum spanning tree (MMST) is proposed to indicate the approximate energy lower bound. Compared with MMST, DEF achieves comparable energy efficiency and better latency performance.

Partial Relay Selection for Hybrid RF/FSO Systems with Hardware Impairments

Abstract: In this paper, we investigate the performance analysis of dual hop relaying system consisting of asymmetric Radio Frequency (RF)/Free Optical Space (FSO) links. The RF channels follow a Rayleigh distribution and the optical links are subject to Gamma-Gamma fading. We also introduce impairments to our model and we suggest Partial Relay Selection (PRS) protocol with Amplify-and-Forward (AF) fixed gain relaying. The benefits of employing optical communication with RF, is to increase the system transfer rate and thus improving the system bandwidth. Many previous research attempts assuming ideal hardware (source, relays, etc.) without impairments. In fact, this assumption is still valid for low-rate systems. However, these hardware impairments can no longer be neglected for high-rate systems in order to get consistent results. Novel analytical expressions of outage probability and ergodic capacity of our model are derived taking into account ideal and non- ideal hardware cases. Furthermore, we study the dependence of the outage probability and the system capacity considering, the effect of the correlation between the outdated CSI (Channel State Information) and the current source-relay link, the number of relays, the rank of the selected relay and the average optical Signal to Noise Ratio (SNR) over weak and strong atmospheric turbulence. We also demonstrate that for a non- ideal case, the end-to-end Signal to Noise plus Distortion Ratio (SNDR) has a certain ceiling for high SNR range. However, the SNDR grows infinitely for the ideal case and the ceiling caused by impairments no longer exists. Finally, numerical and simulation results are presented.

Software-Defined Network Forensics: Motivation, Potential Locations, Requirements, and Challenges

Abstract: The separation of the control plane from the data plane of a switch enables abstraction of a network through a logically centralized controller. The controller functions as the “brain” of a software-defined network. However, centralized control draws attackers to exploit different network devices by hijacking the controller. Security was initially not a key characteristic of SDN architecture, which left it vulnerable to various attackers. The investigation of such attacks in the newly emerging SDN architecture is a challenging task. Therefore, a comprehensive forensic mechanism is required to investigate different forms of attacks by determining their root cause. This article discusses an important area in SDN security, SDN forensics, which until now has received minimal focus. We compare traditional network forensics with SDN forensics to highlight the key differences between them. A brief motivation for SDN forensics is presented to emphasize its significance. Moreover, the potential locations with possible evidence against attackers are identified in SDN. Key requirements are highlighted for SDN forensics with respect to baseline investigation procedures. Finally, we identify challenges in SDN forensics by highlighting potential research areas for researchers, investigators, and academicians.

Proactive Multipath TCP for Seamless Handoff in Heterogeneous Wireless Access Networks

Abstract: Multipath TCP (MPTCP) is a new evolution of TCP that enables a single MPTCP connection to use multiple TCP subflows transparently to applications. Each subflow runs independently allowing the connection to be maintained if endpoints change; essential in a dynamic network. Differentiating between congestion delay and delay due to handoffs is an important distinction overlooked by transport layer protocols. Protocol modifications are needed to alleviate handoff induced issues in a growing mobile culture. In this paper, findings are presented on transport layer handoff issues in currently deployed networks. MPTCP as a potential solution to addressing handoff- and mobility-related service continuity issues is discussed. Finally, a handoff-aware cross-layer-assisted MPTCP (CLA-MPTCP) congestion control algorithm is designed and evaluated.

Efficient Virtual Network Embedding With Backtrack Avoidance for Dynamic Wireless Networks

Abstract: We develop an efficient virtual network embedding (VNE) algorithm, termed B ird -VNE, for mobile wireless networks. B ird -VNE is an approximation algorithm that ensures a close to optimal virtual embedding profit and acceptance rate while minimizing the number of virtual network migrations resulting from the mobility of wireless nodes. B ird -VNE employs a constraint satisfaction framework by which we analyze the constraint propagation properties of the VNE problem and design constraint processing algorithms that efficiently narrow the solution space and avoid backtracking as much as possible without compromising the solution quality. Our evaluation results show that the likelihood that B ird -VNE results in backtracking is small, thus demonstrating its effectiveness in reducing the search space. We analytically and empirically verify that B ird -VNE outperforms existing VNE algorithms with respect to computational efficiency, closeness to optimality, and its ability to avoid potential migrations in mobile wireless networks.

Securing software defined wireless networks

Abstract: Software defined wireless networking (SDWN) is a new paradigm of wireless networking, physically separating the data and control planes of various elements in the wireless infrastructure. Similar to its wired counterpart, SDWN is expected to introduce a wide range of benefits to the operation and management of wireless networks. Security is always important to any network. On one hand, SDWN enables new security mechanisms. On the other hand, some new threats are introduced due to the separation of the control and data planes and the introduction of the logically centralized controller. In this article, we discuss its security threat vectors as well as design issues in making it secure. Also, we analyze the security requirements of SDWN, and then summarize the security attacks and countermeasures in this area and suggest some future research directions.

Advanced Activity-Aware Multi-Channel Operations1609.4 in VANETs for Vehicular Clouds

Abstract: The Dedicated Short Range Communication (DSRC) technology has been used in Vehicular communication to enable short-lived safety and non-safety applications based on Vehicle to Vehicle (V2V) communications over the Control Channel (CCH) and Vehicle to Infrastructure (V2I) communications over the Service Channels (SCHs) in Vehicular Ad hoc Networks (VANETs). With the under-utilized advanced computation, communication and storage resources in On-Board Units (OBUs) of modern vehicles, Vehicular Clouds (VCs) are used to manage coalitions of affordable resources in Vehicles in order to host infotainment applications used by other vehicles on the move. In this paper, we introduce an Advanced Activity-Aware (AAA) scheme for Multi-Channel Operations based on 1609.4 in MAC Protocol in Wireless Access in Vehicular Environments (WAVE). The AAA aims at dynamically achieving an optimal setup of Control Channel Interval (CCHI) and Service Channel Interval (SCHI) by reducing the inactivity interval while maintaining a default Synchronization Interval (SI) between all vehicles. We evaluate the performance of our proposed scheme through real-time simulation of vehicular cloud load and VANET communications using NS3. The simulation results indicate that our proposed scheme increases significantly the throughput and reduces the average delay of uploaded packets of non-safety applications from the VC to the Road Side Unit (RSU) while maintaining a V2V communication for safety similar to that of the 1609.4 standard.

Distributed Learning-Based Cross-Layer Technique for Energy-Efficient Multicarrier Dynamic Spectrum Access With Adaptive Power Allocation

Abstract: This paper proposes energy and cross-layer aware resource allocation techniques that allow dynamic spectrum access (DSA) users, by means of learning algorithms, to locate and exploit unused spectrum opportunities effectively. Specifically, we design private objective functions for DSA users with multiple channel access and adaptive power allocation capabilities. We also propose simple two-phase heuristics for allocating spectrum and power resources among users. The proposed heuristics split the spectrum and power allocation problem into two subproblems, and solve each of them separately. The spectrum allocation problem is solved, during the first phase using learning. Two procedures to learn the channel selection are proposed and compared in terms of optimality, scalability, and robustness. The power allocation, on the other hand, is formulated as a real optimization problem and solved, during the second phase, by traditional optimization solvers. Simulation results show that energy and cross-layer awareness and multiple channel access capability improve the performance of the system in terms of the per-user average rewards received from accessing the dynamic spectrum access system. In addition, the two proposed methods for channel selection via learning represent a tradeoff between optimality, scalability, and robustness.

Sink mobility aware energy-efficient network integrated super heterogeneous protocol for WSNs

Abstract: In this paper, we propose Balanced Energy-Efficient Network Integrated Super Heterogeneous (BEENISH), improved BEENISH (iBEENISH), Mobile BEENISH (MBEENISH), and improved Mobile BEENISH (iMBEENISH) protocols for heterogeneous wireless sensor networks (WSNs). BEENISH considers four energy levels of nodes and selects cluster heads (CHs) on the base of residual energy levels of nodes and average energy level of the network, whereas iBEENISH dynamically varies the CHs selection probability in an efficient manner leading to increased network lifetime. We also present a mathematical sink mobility model and validate this model by implementing it in BEENISH (resulting in MBEENISH) and iBEENISH (resulting in iMBEENISH). Finally, simulation results show that BEENISH, MBEENISH, iBEENISH, and iMBEENISH protocols outperform contemporary protocols in terms of stability period, network lifetime, and throughput.

An Accountable, Privacy-Preserving, and Efficient Authentication Framework for Wireless Access Networks

Abstract: The convergence of wireless access networks significantly changes the way we live and work, bringing us closer to the goal of computing anywhere at any time. Security, privacy, accountability, and efficiency issues are of most concern in the deployment of such networks. Despite the need and importance, little research has been conducted on designing accountable and privacy-preserving authentication schemes for wireless access networks, not to mention schemes that can simultaneously and efficiently provide accountability and privacy protection without involving any trusted third party. This motivates us to develop a novel authentication framework, namely APEA , that integrates a new key management protocol, i.e., an adapted construction of short group signature (SGS) and batch verification, as an effective approach to simultaneously achieve the four goals without involving any trusted third party. Experiments using our implementation on laptop PCs demonstrate that APEA is feasible in practice.

Efficient Usage of Renewable Energy in Communication Systems Using Dynamic Spectrum Allocation and Collaborative Hybrid Powering

Abstract: In this paper, we introduce a new green resource allocation problem using hybrid powering of communication systems from renewable and nonrenewable sources. The objective is to efficiently allocate the power delivered from the different micro-grids to satisfy the network requirements. Minimizing a defined power cost function instead of the net power consumption aims to encourage the use of the available renewable power through collaboration between the base stations within and outside the different micro-grids. The different degrees of freedom in the system, ranging from assignment of users to base stations, possibility of switching the unnecessary base stations to the sleep mode, dynamic power allocation, and dynamic allocation of the available bandwidth, allow us to achieve important power cost savings. Since the formulated optimization problem is a mixed integer-real problem with a nonlinear objective function, we propose to solve the problem using the branch and bound (B&B) approach, which allows to obtain the optimal or a suboptimal solution with a known distance to the optimal. The relaxed problem is shown to be a convex optimization which allows to obtain the lower bound. For practical applications with large number of users, we propose a heuristic solution based on decomposing the problem into two subproblems. The users-to-base stations assignment is solved using an algorithm inspired from the bin-packing approach while the bandwidth allocation is performed through the bulb-search approach. Simulation results confirm the important savings in the nonrenewable power consumption when using the proposed approach and the efficiency of the proposed disjointed algorithms.

Network security analyzing and modeling based on Petri net and Attack tree for SDN

Abstract: Due to the widespread research on Software Defined Networks (SDNs), its security has received much attention recently. But most of those attempts consider SDN security from the OpenFlow perspective. To the best of our knowledge, none so far has paid attention to the security analysis and modeling of Forwarding and Control planes Separation Network Structure (FCSNS) in SDN. Therefore, this paper provides a different approach to network security based on Petri net and Attack tree models. Our objective is to analyze the FCSNS security via the combination of model and state. This method represents the network structure and state transferring by way of Petri net. In addition, it introduces the security analysis method of STRIDE to build up the Attack tree model. Finally, we analyze FCSNS via the combination of Petri net and Attack tree model and present the results. Our results are very promising in using such models to achieve such security objectives.

QoE-Oriented Resource Efficiency for 5G Two-Tier Cellular Networks: A FemtoCaching Framework

Abstract: Video streaming applications and services (VASs) consume an enormous amount of scarce resources in mobile devices and cellular wireless networks due to the demand for high data rates of video streaming. The limited resource of wireless media and unreliable nature of wireless channels in cellular networks make VASs challenging to deliver videos at high quality of experience (QoE). Therefore, in this paper, we propose a femtocaching framework of QoE-oriented resource efficiency optimization for high performance of cooperative VASs over 5G two-tier cellular networks, where the collaboration between macro base stations (BSs) and femtocells are exploited to efficiently deliver videos to mobile users (MUs). Our proposed framework aims at solving two problems. The first problem is how to cache the videos in femtocells to minimize the bandwidth resource consumed at the BSs and wasted at femtocells while guaranteeing high hit rate and utilizing the available storage resource of femtocells. The second one is how to encode the videos into descriptions and assign them to each femtocell for transmission, so as to minimize the reconstructed distortion of received videos for high playback quality at the MUs. The simulation results are further provided to demonstrate the benefits of the proposed framework.

Study of Vehicular Cloud during traffic congestion

Abstract: The Vehicular Ad-Hoc Network has many advantages in the development of road infrastructures and the field of technology Recently, many research groups suggest to apply the concept of Vehicular Cloud by leveraging the under-used physical resources of cars In this paper, we discuss the exploitation of vehicular storage capabilities during a traffic jam We propose a scheme which permits to create a Vehicular Data Center (VDC) on a road segment (RS) Each participated car will contain a specific data item during its residence time on the RS Once it will leave the RS, a local retrieval should be executed So, each leaving car will transfer its content to the newly arrived car on the RS and so on This process will continue so that data items can be available on the RS But to maintain the data transfer cycle, we have to study some constraints: The participation of drivers, the storage capability of the available car, the existence of an empty car and the transmission time issue

An Advanced Energy Consumption Model for terrestrial Wireless Sensor Networks

Abstract: Energy is one of the most precious resource in Wireless Sensor Networks (WSNs) which is mainly consumed in communication, sensing and processing. Performance evaluation of WSN routing protocols primarily rely on simulation-based studies. Most of these studies only assume oversimplified First Order Radio Model (FORM) and ignore node's energy consumed in sensing and processing. This paper presents an Advanced first order Energy Consumption Model (A-ECM) for terrestrial WSNs. Unlike FORM, A-ECM factors in essential energy guzzlers of wireless transmission and reception (i.e., coding rate, bit rate and decoding) besides sensing and processing. The performance of A-ECM is validated through simulations which demonstrate the effectiveness of A-ECM for realistic scenarios.

Peak shaving through optimal energy storage control for data centers

Abstract: We propose efficient control strategies for deciding the amount of energy that a battery needs to charge/discharge over time with the objective of minimizing the Peak Charge and the Energy Charge components of the Data Center (DC) electricity bill. We consider first the case where the DC's power demands throughout the whole billing cycle are known and we present an optimal peak shaving control strategy for a battery that has certain leakage and conversion losses. We then relax this assumption and propose an efficient battery control strategy when we only know predictions of the DC's power demands in a short duration in the future. Several comparative studies are conducted based on real traces from a Google DC in order to validate the proposed techniques.

Hadoop Based Real-Time Intrusion Detection for High-Speed Networks

Abstract: The rate of data generation is enormously growing due to the number of internet users and its speed. This increases the possibility of intrusions causing serious financial damage. Detecting the intruders in such high-speed data networks is a challenging task. Therefore, in this paper, we present a high-speed Intrusion Detection System (IDS), capable of working in Big Data environment. The system design contains four layers, consisting of capturing layer, filtration and load balancing layer, processing layer, and the decision-making layer. Nine best parameters are selected for intruder flows classification using FSR and BER, as well as by analyzing the DARPA datasets. Among various machine learning approaches, the proposed system performs well on REPTree and J48 using the proposed features. The system evaluation and comparison results show that the system has better efficiency and accuracy as compare to existing systems with the overall 99.9 % true positive and less than 0.001 % false positive using REPTree.