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To provide a new level of reliability, latency, and support a massive number of users and smart objects, a new 5G multi-services air interface needs to be addressed for the factory of the future (FoF). However, there are limitations in providing connectivity to a dynamic machine in a factory due to several strict industrial automation requirements. In particular, the strict wireless communication latency and reliability requirements are the major challenges to enable the Industry 4.0 vision. In this paper, a PHY-MAC layer cross-layer model that combines a semi-persistent scheduling at the medium access control layer and NOMA at the physical layer has been proposed to address the limitations. The work extensively investigates the performance of the factory of the future with various considerations of 5G spectrums (in this case 3.5 GHz and 28 GHz), speeds and frequency diversity. In addition, the packet error rate (PER), outage probability and throughput in MAC are evaluated in terms of network density deployment (sparse, moderate, dense), different kinds of speed; 0 km/h, 3 km/h, 7 km/h and 10 km/h, under two 5G frequency spectrums. Through extensive simulations, the considered 5G system parameters produced better results in terms of reliability, where the results showed that the frequency diversity outperformed non-diversity by 2 dB. In a sparse network, the PER results showed better results compared to the dense network density by 2 dB (MMSE), 8 dB (LS-Linear) and 2 dB (LS-Spline). Besides that, robotics in sparse network density and stationary exhibited the best PER results, which is as low as 10−7. Moreover, the performance of mid-band frequency outperformed the high-band frequency by 1.8dB (MMSE) in dense condition and 1.5 dB (MMSE) in sparse deployment at PER = 10−6. Hence, this study could be a useful insight for the factory of the future services that are utilizing a 5G mid-band spectrum as well as a high-band spectrum.

In this paper, we propose a new deep Q-network (DQN) design for quality-of-service (QoS) multicast routing (DQMR) protocol to establish efficient QoS multicast (EQM) trees in cognitive radio mobile ad hoc networks (CR-MANETs). An EQM tree is a shortest-path multicast tree with minimum end-to-end (E2E) cost (a combination of queuing size ratio and link stability) subject to QoS constraints such as queuing size ratio, link stability, number of hops, number of time slots and avoiding the licensed channel of primary users. Particularly, we propose an NP-complete optimization problem such that its feasible solution is an EQM tree. To address this problem, we design a new DQN model and a new game-based model to form EQM trees in real-time by offline training instead of online training as done in previous papers. Moreover, the DQMR protocol is also guaranteed to have high stability, low routing delay, low control overhead, and high packet delivery ratio (PDR). Furthermore, one more new contribution of the paper is that exact closed-form expressions for the E2E queuing delay of a multicast routing tree are also derived assuming random waypoint mobility and the reference point group mobility models to compare with simulation results of routing delay. Simulation results show that the DQMR protocol outperforms multicast ad hoc on-demand distance vector routing protocol in terms of routing delay, control overhead, and PDR.

Detecting the frequency of the pest occurrence is always a time consuming and laborious task for agriculture. This paper attempts to solve the problem through the combination of deep learning and pest detection. We propose an entire-and-partial feature transfer learning architecture to perform pest detection, classification and counting tasks which can reach the final goal for detecting the frequency of pest occurrence. In the partial-feature transfer learning, different fine-grained feature map are strengthened by using the weighting scheme of the entire-feature transfer learning. Finally, the cross-layer of the entire-feature network is combined with the multi-scale feature map. The entire-feature transfer learning approach enhances the feature map by creating a shortcut topology for the input and output layers to reduce the gradient disappearance problem which is common to deep networks. The experimental results show that the detection accuracy can be significantly improved and the accuracy can reach 90.2%.

Internet-connected Internet of Things (IoT) devices are exploding, which pose a significant threat for their management and security protection. IoT device identification is a prerequisite for discovering, monitoring, and protecting these devices. Although the existing proactive identification methods based on protocol fingerprint can discover and identify large-scale IoT devices, the fingerprint granularity is difficult to meet the requirements of security risk assessment for large-scale IoT devices. Since IoT devices usually support multiple network protocols for specific collection and control tasks, we propose a cross-layer protocol fingerprint to achieve large-scale fine-grained devices identification instead of traditional single protocol fingerprint. We first design a probing scheme for gathering HTTP and TCP cross-layer packets. Then we select the specific field of the HTTP and TCP protocols based on the diversity and consistence of field value. Finally, we utilize convolutional neural network (CNN) and long-term memory network (LSTM) to extract and construct feature fingerprint of these specific fields, and achieve a fine-grain IoT devices identification with high accuracy. The experimental results show that our identification accuracy of devices model reaches 96.6%, the recall rate reaches 97.4%.

As a promising communication paradigm in the 5G era, IEEE 802.11ad 60GHz mmWave communication has many desirable properties, including high bandwidth, narrow beam, high transmission quality, and low mutual-interference. However, recently revealed Man-in-the-middle (MITM) attack can endanger the security and privacy of mmWave communication systems. Existing MITM attack detection solutions, established on ideal assumptions, neglect the fact that a MITM attacker can change its transmitting power and make it hard to be detected. In this backdrop, a cross-layer location consistency-based MITM detection and localization algorithm is introduced in this paper. Firstly, we propose a positioning algorithm based on the information of the physical layer with a directional antenna sector propagation model; secondly, based on the information at the MAC layer, we propose a MITM attack detection scheme and a sector consistency check algorithm; thirdly, a MITM attack detection and localization algorithm using cross-layer information is proposed. Simulation results have shown that the proposed algorithm can effectively detect the MITM attack and its positioning error is less than 0.53m in typical parameter settings.

The mobile Internet is becoming increasingly complex with a wide diversity of end systems (including wearables and automobiles), the co-presence of multiple devices with collaboration potential, and the growth of user-generated application traffic fueled by improved mobile sensors and wireless access. As the Internet evolves along with these trends, the increased complexity of different components and protocol layers makes it more challenging to achieve high network utilization and meet the diverse QoE requirements for mobile applications. As a result, despite the richness of various network resources, the performance of today’s mobile applications still falls behind expectations. To address this challenge, in this dissertation, I demonstrate that with a better understanding of the various components and different protocol layers of the increasingly complex mobile Internet, we can identify unique performance problems and leverage such knowledge to develop network transport protocols with cross-device awareness and application adaptation strategies with cross-layer considerations for better mobile app performance. Specifically, to understand the interaction between multiple mobile devices and its impact on end-to-end performance, we conduct an empirical study on wearable networking, where wearables oftentimes rely on their paired smartphones for Internet access. Based on our measurement findings, we develop cross-device network transport management solutions for improving wearable networking performance. To better support multi-device collaboration in a more general setting, we develop MPBond, a distributed multipath transport system for efficient network-level collaboration among personal mobile devices, with cross-device connection management and packet scheduling. To explore opportunities on the mobile application design, we build Livelyzer, a generalized measurement tool for characterizing commercial live video streaming upstream ingest performance under mobile networks. Based on our measurements, we identify deficiencies in broadcasting app rate adaptation, and propose network-aware adaptation strategies to improve the same. We also investigate another emerging mobile application, vehicular sensing for autonomous driving, where we build Harbor, a cross-layer system architecture for collaborative vehicular sensor data sharing, with adaptive usage of V2V and V2I network resources.

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Cross-layer reliability is becoming the preferred solution when reliability is a concern in the design of a microprocessor-based system. Nevertheless, deciding how to distribute the error management across the different layers of the system is a very complex task that requires the support of dedicated frameworks for cross-layer reliability analysis. This paper proposes SyRA, a system-level cross-layer early reliability analysis framework for radiation induced soft errors in memory arrays of microprocessor-based systems. The framework exploits a multi-level hybrid Bayesian model to describe the target system and takes advantage of Bayesian inference to estimate different reliability metrics. SyRA implements several mechanisms and features to deal with the complexity of realistic models and implements a complete tool-chain that scales efficiently with the complexity of the system. The simulation time is significantly lower than micro-architecture level or RTL fault-injection experiments with an accuracy high enough to take effective design decisions. To demonstrate the capability of SyRA, we analyzed the reliability of a set of microprocessor-based systems characterized by different microprocessor architectures (i.e., Intel x86, ARM Cortex-A15, ARM Cortex-A9) running both the Linux operating system or bare metal. Each system under analysis executes different software workloads both from benchmark suites and from real applications.

Reducing collisions in UHF RFID systems is a crucial problem. In most anti-collision designs, the reader has to estimate the number of tags within its reading range during the interrogation process. Most of the approaches estimate the number of tags with observations in multiple time slots. Since estimation error varies along with the initial frame length and the number of tags, system efficiency is affected by both of them. To reduce the sensitiveness to them and improve system efficiency, we propose a novel MAC-PHY cross-layer anti-collision algorithm based on Bayesian inference. Specifically, each frame is allowed to end at an early stage and a slot-by-slot estimator is proposed. Benefit from its slot-by-slot nature, system efficiency is more stable and independent on the initial frame length and very close to the upper bound of dynamic framed slotted ALOHA (DFSA) algorithm. The performance of the proposed method is compared with the state-of-the-art algorithms through numeric simulations. The results show that the proposed solution significantly outperforms the compared ones.

Due to rapid growth of multimedia traffic used over the mobile ad-hoc networks (MANETs), to keep up with the progress of this constraints MANETs protocols becoming increasingly concerned with the quality of service. In view of the random mobility nodes in MANET, TCP becomes more unreliability in case of higher energy consumption and packet loss. In this paper we proposed a new optimization approach to enhance decision making of TCP based on some changes of IEEE 802.11 MAC uses cross layer approach. The aim is to minimize the impact of retransmissions of packet lost and energy consumption in order to analysed and chose the appropriate routing protocol for TCP that can be enhance QoS MANET. Our simulation results based QoS study using NS3 show that, our proposed achieves better performance of TCP in MANETs significantly, and also improved the throughput, energy consumption and facilitates the traffic transmission over routing protocol.

Peer-to-Peer (P2P) energy trading platforms are being actively designed, tested and operated by engineers, power distribution companies and prosumers. The assurance of the accountability of the conduct of different stakeholders through a robust trust management mechanism is imperative in such platforms. The usage of blockchain, as an underlying technology, can ensure numerous properties such as immutability, transparency and traceable execution of transactions, in addition to ensuring trust establishment among different entities of the system. Few blockchain-based decentralized energy trading platforms have been designed in the literature to build trust about the platform and among prosumers. However, none of these proposals have considered human-in-the-loop in the trust establishment process. Moreover, these solutions have considered trust only at a particular layer of blockchain, such as at the application or consensus layer. To bridge this gap, this paper presents a novel cross-layer trust-based consensus protocol that considers human-in-the-loop and employs fuzzy logic to address the issue of vagueness of trust values by offering human interpretable trust level. The experiment results demonstrate the efficiency and effectiveness of our proposed protocol in comparison to established consensus mechanisms. The analysis also shows the protocol is immune against selfish mining, 51% and Sybil attacks.

Considering that networks based on New Radio (NR) technology are oriented to provide services of desired quality (QoS), it becomes questionable how to model and predict targeted QoS values, especially if the physical channel is dynamically changing. In order to overcome mobility issues, we aim to support the evaluation of second-order statistics of signal, namely level-crossing rate (LCR) and average fade duration (AFD) that is missing in general channel 5G models. Presenting results from our symbolic encapsulation point 5G (SEP5G) additional tool, we fill this gap and motivate further extensions on current general channel 5G. As a matter of contribution, we clearly propose: (i) anadditional tool for encapsulating different mobile 5G modeling approaches, (ii) extended, wideband, LCR, and AFD evaluation for optimal radio resource allocation modeling, and (iii) lower computational complexity and simulation time regarding analytical expression simulations in related scenario-specific 5G channel models. Using our deterministic channel model for selected scenarios and comparing it with stochastic models, we show steps towards higherlevel finite state Markov chain (FSMC) modeling, where mentioned QoS parameters become more feasible, placing symbolic encapsulation at the center of cross-layer design. Furthermore, we generate values within a specified 5G passband, indicating how it can be used for provisioningoptimal radio resource allocation.

Inerter-based vibration control systems have been developed rapidly in recent years. However, previous studies mainly focus on the development of new devices and parameter optimization strategies, while ignoring the improvements in the utilization efficiency of the inerter system that the bracing system and novel installation methods may bring. In this paper, a cross-layer installed cable-bracing inerter system (CICBIS) is proposed to improve the utilization efficiency of the inerter system, which can cross more layers and is suitable for shear-type multi-degree-of-freedom (MDOF) structures. A demand-based cable-bracing inerter system (CBIS) design method is developed. The mass enhancement and utilization efficiency improvement of the inerter system caused by the cross-layer installation are quantified through calculating the effective inerter-mass ratio of the CBIS-equipped MDOF structure. A 10-story benchmark structure is used to verify the control performance of the CICBIS and the design method. The analysis results show that the proposed design method can exert the cable-bracing system&rsquo, s adjustability and the damping enhancement of the inerter system. The CICBIS can reduce the total apparent mass and damping coefficient requirements of the inerter systems without increasing the control force. It means that the proposed design method is effective, and the CICBIS has a high efficiency.

Due to their proven efficiency, machine-learning systems are deployed in a wide range of complex real-life problems. More specifically, Spiking Neural Networks (SNNs) emerged as a promising solution to the accuracy, resource-utilization, and energy-efficiency challenges in machine-learning systems. While these systems are going mainstream, they have inherent security and reliability issues. In this paper, we propose NeuroAttack, a cross-layer attack that threatens the SNNs integrity by exploiting low-level reliability issues through a high-level attack. Particularly, we trigger a fault-injection based sneaky hardware backdoor through a carefully crafted adversarial input noise. Our results on Deep Neural Networks (DNNs) and SNNs show a serious integrity threat to state-of-the art machine-learning techniques., Accepted for publication at the 2020 International Joint Conference on Neural Networks (IJCNN)

The recent advancements of wireless technology and applications make downlink scheduling and resource allocations an important research topic. In this paper, we consider the problem of downlink scheduling for multi-user scalable video streaming over orthogonal frequency division multiple access (OFDMA) channels. The video streams are precoded using a scalable video coding (SVC) scheme. We propose a fuzzy logic-based scheduling algorithm, which prioritises the transmission to different users by considering video content, and channel conditions. Furthermore, a novel analytical model and a new performance metric have been developed for the performance analysis of the proposed scheduling algorithm. The obtained results show that the proposed algorithm outperforms the content-blind/channel aware scheduling algorithms with a gain of as much as 19% in terms of the number of supported users. The proposed algorithm allows for a fairer allocation of resources among users across the entire sector coverage, allowing for the enhancement of video quality at edges of the cell while minimising the degradation of users closer to the base station.

TCP and TLS are among the most essential protocols in today's Internet. TCP ensures reliable delivery of data while TLS secures the data transfer. Following the layered model, TLS was designed to be as independent as possible from the underlying transport protocol. This paper revisits this assumption and demonstrates the various benefits that a closer integration between TCP and TLS brings. We implement a first TCPLS prototype that demonstrates the feasibility of this integration. We show its usefulness on different use cases such as the benefit of bandwidth aggregation during a connection migration, and discuss several open research directions.

IoT concept took a part in everyday lives. Environments became smart, suggestive, recognizing, and adopting to its user needs. However, energy efficiency, interoperability, security, and other issues are restricting the number of use-cases and ways the technology can be used. To cope with these issues, cross-layer approach in standard architectures is necessary. This way, information propagating from one layer to the another can significantly influence overall performances—it is necessary to understand and implement all the significant details that may enable and improve specific applications. Moreover, tremendous evolution in data acquisition and transfer is needed to consider efficient hardware and innovative software architectures that still need to be developed to make it a reality. This mostly introduces distributed intelligence for a reliable and effective processing of the information about the physical world that should provide a complete knowledge to the top running applications. These are related to the efficient usage of radio technologies usual referred as in outdoor, indoor, urban, rural environments, its ranges, and battery/battery-less usage. In addition, communication protocols should handle IoT requirements for multiple device, low-power, real-time operations, or satisfying timely consumer needs. Some further challenges involve efficient device discovery schemes, sleep-mode management, application requirements, security issues, or other power constraints.

The latest 6TiSCH standard enables highly reliable industrial monitoring and control applications through deterministic wireless communications and efficient allocation of radio resources among wireless nodes. However, much of these benefits are tied to the ability of the scheduler in orchestrating communication over individual links in an efficient and a non-conflicting manner. The state-of-the-art 6TiSCH scheduling algorithms only tackle the scheduling problem at the MAC layer with an assumption of having an optimal routing layer. Moreover, to the best of our knowledge, no solution so far has taken content-specific scheduling into account. This paper proposes CONCISE, which is a content-centric cross-layer scheduling solution. CONCISE creates content-independent routing topologies and schedulers, resulting in an overlaid routing structure and multiple content-based schedules. Further, CONCISE addresses in-network processing and data aggregation with the objective of reducing network traffic. Performance evaluation demonstrates that CONCISE can effectively reduce inner layer network traffic by up to 65%. As a result, it can provide up to 50% delay reduction and achieve significantly higher packet delivery ratio, compared with existing scheduling solutions. Initial proof of concept is implemented and evaluated in Contiki OS.

This paper investigates the cross-layer optimization for anti-jamming in the network and MAC layers, in which the jammer can adjust the jamming policies to maximize the jamming effectiveness. The joint problem of routing selection, channel allocation, and power control is formulated as a Stackelberg game. The jammer leads the game by choosing the optimal jamming power and channels. The user follows by selecting the optimal nodes and corresponding channels, and adjusts its transmitting power to meet the communication requirement. Then, based on Q-learning, a cross-layer anti-jamming learning algorithm is proposed to obtain the Stackelberg equilibrium. Finally, simulation results are presented to verify the effectiveness of the proposed algorithm.

Mobile ad hoc network (MANET) is among the networks which do not require any infrastructure to put nodes in communication. Due to its own nature, it is used by several applications. Even though it's a network that is extremely challenging and mostly when TCP is applied. In this paper, we have proposed a new improvement in the TCP algorithm that employed fuzzy logic to predict packet loss and avoid congestion. Specifically, we have used tree metrics such as stability, energy, and signal strength to use in fuzzy logic systems. To accomplish our approach, we have established some modifications based on a cross-layer. The results of the relevant simulation performed by NS3 demonstrated that our approach globally improves the performance of TCP in MANET. Precisely reduce the packet overhead and energy consumption also enhance throughput.

In this paper, a resource allocation algorithm in two-way orthogonal frequency division multiplexing (OFDM) based cognitive radio networks with quality of experience (QoE) and power consumption guarantees is proposed. We define the overall QoE perceived by secondary users (SUs) per power consumption as QoEW. The power consumption model consists of fixed circuit power, dynamic circuit power, and transmit power which depends on the efficiency of the power amplifiers at different terminals. Under the constraint of total maximum transmit power, the optimization objective is to maximize QoEW while meeting the minimum QoE demands of SUs and maintaining interference threshold limitations of multiple primary users. The resource allocation problem is formulated into a nonlinear fractional programming and transformed into an equivalent convex optimization problem via its hypograph form. Based on the Lagrange dual decomposition method and cross-layer (CL) optimization architecture, this convex optimization problem is separately solved in the physical layer and the application layer. The optimal QoEW is achieved through the proposed CL alternate iteration algorithm. Numerical simulation results demonstrate the impacts of system parameters on QoEW and the effectiveness and superiority of the proposed algorithm.

The demand for pervasive wireless access and high data rate services are expected to grow significantly in the near future. In this context, the deployment of Heterogeneous Networks (HetNets) will enable important capabilities, such as high data rates and traffic offloading, providing dedicated capacity to homes, enterprises, and urban hotspots. Despite HetNet technology will be beneficial for future wireless systems in many ways, the massive cells diffusion has as a consequence an exponential increase of the backhaul traffic that can create congestion and collapse the backhaul network. Virtualization of networks and radio access allows the implementation of complex and efficient decisional processes for radio and network resource optimization, but the interaction between lower and upper layers during resource allocation decisions is still mostly unexplored. In this paper we propose an artificial intelligence based approach, with two interdependent decisional cores exchanging information, one aware of physical layer aspects and the other controlling pure network resources. The two iterative procedures aim at jointly optimizing the distribution of the traffic in the backhaul network and the users cell association, with the goals of minimizing the unsatisfied users data rate requests and minimizing the energy consumption reducing the number of activated cells, respectively.

Large content providers, known as hyper-giants, are responsible for sending the majority of the content traffic to consumers. These hyper-giants operate highly distributed infrastructures to cope with the ever-increasing demand for online content. To achieve 40 commercial-grade performance of Web applications, enhanced end-user experience, improved reliability, and scaled network capacity, hyper-giants are increasingly interconnecting with eyeball networks at multiple locations. This poses new challenges for both (1) the eyeball networks having to perform complex inbound traffic engineering, and (2) hyper-giants having to map end-user requests to appropriate servers. We report on our multi-year experience in designing, building, rolling-out, and operating the first-ever large scale system, the Flow Director, which enables automated cooperation between one of the largest eyeball networks and a leading hyper-giant. We use empirical data collected at the eyeball network to evaluate its impact over two years of operation. We find very high compliance of the hyper-giant to the Flow Director’s recommendations, resulting in (1) close to optimal user-server mapping, and (2) 15% reduction of the hyper-giant’s traffic overhead on the ISP’s long-haul links, i.e., benefits for both parties and end-users alike.

International audience; Lack of coordination between network layers limits the performance of most proposed solution for new challenges posed by wireless networks. To overcome such limitations, cross-layer physical and medium access (PHY-MAC) design for multi-input-multi-output orthogonal frequency division multiple access system in heterogeneous networks (HetNETs) is proposed. In this paper, we formulate an optimization problem for hybrid beamforming, in a multiuser HetNET scenario aiming to maximize the total system throughput. Furthermore, analog beamforming is selected from a codebook containing a limited number of candidates for steering vectors. The proposed problem is non-convex and hard to solve. Thus it is relaxed by transforming it into a subtraction form of two convex funcions. Afterward we apply a group of well-known metaheuristic algorithms to calculate the normalized hybrid beamforming vectors. The optimal solution is obtained using an exhaustive search (ES) algorithm that provides an ideal solution, but with high complexity. In addition, zero-forcing-based approach (ZFA), matched filter (MF), and QR-based approach (QR) are applied to get quick sub-optimal solutions. Hence, we analyze the performance of our systems using the throughput metric. The simulation results show that QR algorithm outperforms ZFA and MF in low and middle signal-to-noise ratio (SNR) regime, while ZFA outperforms QR and MF at higher SNRs. Moreover, QR is close to the optimal solution ES.

Wireless sensor networks with mobile collectors or sinks face some challenges regarding the data collection process and the continuous connectivity and delivering of data while the mobile sink is moving throughout the network. These challenges increase as the network grows. For this aim, we propose in this paper a cross-layer routing protocol which supports mobility for large-scale wireless sensor networks, which we name CLR-MSPH. We adapt CLR-MSPH for the hierarchical architecture of the network, and it performs on cluster-based wireless sensor networks where the network is organized in clusters. Our proposed protocol deals with the problem of handover data after the mobile sink leaves the radio range of cluster head without sending all data stored in the cluster head&rsquo, s buffer. We also introduce a mobility model for the mobile sink for a better data collection process. CLR-MSPH is considered as an extending implementation of BMAC protocol with handover mechanism (BMAC-H). In order to prove the efficiency of the proposed protocol, we compare CLR-MSPH to BMAC-H, where we adapted BMAC-H to perform in cluster-based wireless sensor networks. The simulation results show that CLR-MSPH performs better than BMAC-H in terms of packets reception rate, energy, and latency.

JIF=2.924; International audience; There is nowadays a growing demand in vehicular communications for real-time applications requiring video assistance. The new state-of-the-art high-efficiency video coding (HEVC) standard is very promising for real-time video streaming. It offers high coding efficiency, as well as dedicated low delay coding structures. Among these, the all intra (Al) coding structure guarantees minimal coding time at the expense of higher video bitrates, which therefore penalizes transmission performances. In this work, we propose an original cross-layer system in order to enhance received video quality in vehicular communications. The system is low complex and relies on a multiple description coding (MDC) approach. It is based on an adaptive mapping mechanism applied at the IEEE 802.11p standard medium access control (MAC) layer. Simulation results in a realistic vehicular environment demonstrate that for low delay video communications, the proposed method provides significant video quality improvements on the receiver side. (C) 2019 Elsevier GmbH. All rights reserved.

A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications.

A reliable energy-efficient routing protocol plays a key role in underwater data transmission. In the face of acoustic communication challenges in underwater wireless sensor networks (UWSNs), including long propagation delay, topology change, limited energy, and communication voids, we propose RECRP, a Reliable Energy-efficient Cross-layer Routing Protocol to achieve high data delivery rate. RECRP is a location-free single-copy protocol. The information of the physical layer such as Doppler scale shift measurement, Received Signal Strength Indication (RSSI), etc. are adopted to estimate the distance, thus no extra hardware is needed for localization. Moreover, the overhead introduced by redundant packets is avoided with the single-copy mechanism. To improve the two-hop packet delivery rate and balance energy consumption among adjacent nodes, an optimal max–min method is proposed that dynamically controls transmission power and channel frequency. Furthermore, a surface to bottom routing establishment method is also adopted to handle communication voids. Compared with depth-based routing (DBR) and hop-by-hop vector-based forwarding (HH-VBF) , RECRP is more energy-efficient with a higher delivery rate.

International audience; Nowadays, multimedia contents are widely used for various applications to ensure personal and public services. These contents are transferred through different kind of networks, from classical Adhoc networks to the recent Internet of Things (IoT). However, regardless the deployed network, the main goal remains the same: ensuring a better QoE and lower latency especially for emergency traffic. This domain attracts many research activities. In this paper, we tackle this challenging issue and we propose a cross-layer scheme to handle video streaming over wireless sensor networks. Our starting point is to provide a carrier sense aware disjoint multi-path routing protocol able to transmit efficiently video and regular data from many sources to a unique base station (BS). This protocol will cooperate with the application layer in order to provide a frame-aware solution to assign high priority to the most important frames and low priority for the least important ones. This priority concerns mainly the path that will be used by the frames and the queuing policy that will be applied. Our queuing policy involves enqueuing, de-queuing and congestion solving function in order to reduce video latency and enhance the reliability. Our scheme is explained through a theoretical study with illustrative examples. Many simulations have been conducted, they demonstrate improvements of some performance indicators such as packet data rate, delay, loss packet rate and user experience.

In this paper we present GREENROUTES, an energy-aware routing protocol for Energy Harvesting-based ("green") Wireless Sensor Networks that leverages self-powered technologies for eliminating the need of energy storage device replacement. GREENROUTES combines energy harvesting and wake-up radios with semantic addressing. Semantic addressing capabilities are effectively used to enhance communication by allowing nodes to selectively wake-up a suitable subset of neighboring nodes. This subset is determined by the distance of nodes from the sink, and, greedily, by the residual energy along routes to the sink. The performance of GREENROUTES has been compared to that of the Energy Harvest Wastage-Aware (EHWA) routing solution in scenarios where all nodes harvest energy from the same source, either sun or wind. Results show that GREENROUTES achieves a packet delivery ratio significantly higher (up to 40%) than EHWA, while delivering packets faster and for less power.

In this paper, compressed sensing (CS) theory is utilized in a medium-access control (MAC) scheme for wireless sensor networks (WSNs). We propose a new, cross-layer compressed sensing medium-access control (CL CS-MAC) scheme, combining the physical layer and data link layer, where the wireless transmission in physical layer is considered as a compress process of requested packets in a data link layer according to compressed sensing (CS) theory. We first introduced using compressive complex requests to identify the exact active sensor nodes, which makes the scheme more efficient. Moreover, because the reconstruction process is executed in a complex field of a physical layer, where no bit and frame synchronizations are needed, the asynchronous and random requests scheme can be implemented without synchronization payload. We set up a testbed based on software-defined radio (SDR) to implement the proposed CL CS-MAC scheme practically and to demonstrate the validation. For large-scale WSNs, the simulation results show that the proposed CL CS-MAC scheme provides higher throughput and robustness than the carrier sense multiple access (CSMA) and compressed sensing medium-access control (CS-MAC) schemes.

Propagation models are used to abstract the actual propagation characteristics of electromagnetic waves utilized for conveying information in a compact form (i.e., a model with a small number of parameters). The correct modeling of propagation and path loss is of paramount importance in wireless sensor network (WSN) system design and analysis [1]. Most of the important performance metrics commonly employed for WSNs, such as energy dissipation, route optimization, reliability, and connectivity, are affected by the utilized propagation model. However, in many studies on WSNs, overly simplistic and unrealistic propagation models are used. One of the reasons for the utilization of such impractical propagation models is the lack of awareness of experimentally available WSN-specific propagation and path-loss models. In this article, necessary succint background information is given on general wireless propagation modeling, and salient WSN-specific constraints on path-loss modeling are summarized. Building upon the provided background, an overview of the experimentally verified propagation models for WSNs is presented, and quantitative comparisons of propagation models employed in WSN research under various scenarios and frequency bands are provided.

According to large coverage of satellites, there are various channel states in a satellite broadcasting network. In order to introduce an efficient rateless transmission method to satellite multimedia broadcasting/multicast services with finite-length packets, a cross-layer packet transmission method is proposed with Luby transform (LT) codes for efficiency in the network layer and low density parity check (LDPC) codes for reliability in the physical layer jointly. The codewords generated from an LT encoder are divided into finite-length packets, which are encoded by an LDPC encoder subsequently. Based on noise and fading effects of satellite channels, the LT packets received from an LDPC decoder either have no error or are marked as erased, which can be modeled as a binary erasure channels (BECs). By theoretical analysis on LT parameters and LDPC parameters, the relationships between LDPC code rates in the physical layer and LT codes word lengths in the network layer are investigated. With tradeoffs between the LT codes word lengths and the LDPC code rates, optimized cross-layer solutions are achieved with a binary search algorithm. Verified by simulations, the proposed solution for cross-layer parameters design can provide the best transmission mode according to satellite states, so as to improve throughput performance for satellite multimedia transmission.

In IEEE 802.15.4/ZigBee Wireless Sensor Networks (WSNs) a specific node (called the PAN coordinator or sink) controls the whole network. When the network operates in a multi-hop fashion, the position of the PAN coordinator has a significant impact on the performance: it strongly affects network energy consumption for both topology formation and data routing. The development of efficient self-managing, self-configuring and self-regulating protocols for the election of the node that coordinates and manages the IEEE 802.15.4/ZigBee WSN is still an open research issue. In this paper we present a cross-layer approach to address the problem of PAN coordinator election on topologies formed in accordance with the IEEE 802.15.4. Our solution combines the network formation procedure defined at the MAC layer by the IEEE 802.15.4 standard with a topology reconfiguration algorithm operating at the network layer. We propose a standard-compliant procedure (named PAN coordinator ELection -PANEL) to self-configure a IEEE 802.15.4/ZigBee WSN by electing, in a distributed way, a suitable PAN coordinator. A protocol implementing this solution in IEEE 802.15.4 is also provided. Performance results show that our cross-layer approach minimizes the average number of hops between the nodes of the network and the PAN coordinator allowing to reduce the data transfer delay and determining significant energy savings compared with the performance of the IEEE 802.15.4 standard.

Part 1: Memory: Non-Volatile, Solid State Drives, Hybrid Systems; International audience; Flash memory has been widely deployed in modern storage systems. However, the density improvement and technology scaling would decrease its endurance and I/O performance, which motivates the search to improve flash performance and reduce cell wearing. Wearing reduction can be achieved by lowering the threshold voltages, but at the cost of slower reads. In this paper, the access hotness characteristics are exploited for read performance and endurance improvement. First, with the understanding of the reliability characteristics of flash memory, the relationship among flash cell wearing, read latency and bit error rate is introduced. Then, based on the hotness information provided by buffer management, the threshold voltages of a cell for write-hot data are decreased for wearing reduction, while these for read-hot data are increased for read latency reduction. We demonstrate analytically through simulation that the proposed technique achieves significant endurance and read performance improvements without sacrificing the write throughput performance.

The rapid development of wireless communication imposes several challenges to support QoS for real-time multimedia applications such as video stream applications. Researchers tackled these challenges from different points of view including the semantics of the video to achieve better QoS requirements. The main goal of this research is to extend the UDP protocol to realize a distributed sequential mapping scheme (DSM) with a cross-layer design and evaluate its accuracy under different network conditions. In DSM, the perceived quality of a multi-layer video is addressed by mapping each video layer into channel resources represented as queues or access categories (ACs) existing in IEEE 802.11e MAC layer. The experiments reported the efficiency of this scheme with the presence of different composite traffic models covering most known traffic scenarios using Expected Reconstructed Video Layers (ERVL) and packet loss rate as accuracy measures. In Experiments without ongoing traffic, ERVL continuously reported high values, while ERVL values dramatically vary when introducing ongoing different composite traffic models together with the testing video sessions between nodes. 2016 IEEE. Scopus

The growth of wireless networks has resulted in part from requirements for connecting people and advances in radio technologies. Wireless sensor networks are an example of these networks in which a large number of tiny devices interacting with their environments may be inter-networked together and accessible through the Internet. As these devices may be scattered in an unplanned way, a routing protocol is needed. The RPL protocol is the IETF proposed standard protocol for IPv6-based multi-hop WSN. RPL requires that communication paths go through a central router which may provide suboptimal paths, not considering the characteristics of the applications the nodes run. In this paper is proposed an Application-Driven extension to RPL which enables to increase the WSN lifetime by limiting the routing and forwarding functions of the network mainly to nodes running the same application. As nodes may join a network at a non predictable time, they must be synchronized with respect to their application duty cycles. Therefore, nodes have to wake up and sleep in a synchronized way. In this paper it is also proposed such synchronization mechanism. The results confirm that the proposed solutions provide lower energy consumption and lower number of packets exchanged than the conventional RPL solution, while maintaining fairness and the packet reception ratio high. info:eu-repo/semantics/publishedVersion

The need for energy-efficient routing and data gathering protocols in large-scale environments becomes very challenging. Hierarchical routing in WSNs is a very important topic. It has been widely investigated relative to energy efficiency based routing protocols. LEACH (Low Energy Adaptive Clustering Hierarchy algorithm) is the pioneering cluster routing protocol in WSNs. However, it is not suitable for large scale network and wireless channel conditions are ignored during packet forwarding. To address this issue, we proposed a novel multi-hop clustering cross layer protocol based on LEACH. It considers both the SNR of different links and the residual energy of sensor nodes. Simulation results in terms of the average energy consumption, the network lifetime and the Packet Delivery Ratio show clearly the outperformance of the proposed algorithm versus the conventional LEACH.

The use of wireless networks has spread further than simple data transfer to delay sensitive and loss tolerant multimedia applications. Over the past few years, wireless multimedia transmission across Wireless Local area Networks (WLANs) has gained a lot of attention because of the introduction of technologies such as Bluetooth, IEEE 802.11, 3G, and WiMAX. The IEEE 802.11 WLAN has become a dominating technology due to its low cost and ease of implementation. But, transmitting video over WLANs in real time remains a challenge because it imposes strong demands on video codec, the underlying network, and the Media Access Control (MAC) layer. This paper presents a cross-layer mapping algorithm to improve the quality of transmission of H.264 (a recently-developed video coding standard of the ITU-T Video Coding Experts Group) video stream over IEEE 802.11e-based wireless networks. The major goals of H.264 standard were on improving the rate distortion and the enhanced compression performance. Our proposed cross-layer design involves the mapping of H.264 video slices (packets) to appropriate access categories of IEEE 802.11e according to their information significance. We evaluate the performance of our proposed cross-layer design and the results obtained demonstrate its effectiveness in exploiting characteristics of the MAC and application layers to improve the video transmission quality.

Distributed Queuing Collision Avoidance (DQCA) is an efficient MAC protocol designed for infrastructure Wireless LANs. In this paper, four algorithms are proposed that alter the FIFO scheduling order of DQCA in order to meet specific network requirements. The proposed schemes combine the efficiency of opportunistic scheduling with the QoS provisioning through service differentiation. The opportunistic policy encourages transmissions at higher rates when the channel condition is good and is implemented through a cross-layer dialogue between the PHY and the MAC layers. The key idea of service differentiation is to assign priorities to traffic flows with different requirements in order to provide QoS guarantees. The throughput, delay and jitter performance of the proposed schemes has been evaluated through simulations for a scenario with heterogeneous traffic of voice, video, best-effort and background data traffic flows.

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN., 17 pages, 12 figures; Open Access at http://www.mdpi.org/sensors/papers/s8074265.pdf

International audience; In Single-Input Single-Output (SISO) wireless multi-hop networks, when two or more stations attempt to transmit at the same time in the same vicinity area, a collision will occur. In this case, the collided packets are discarded and then retransmitted later. In order to deal with collision and to maximize the system's throughput, we propose a new cross-layer design based on multiple transmit and receive antennas (MIMO) capabilities, called MIMOMAX. Transmit filter, receive filter and channel state information (CSI) are exchanged between the PHY and MAC layers to optimize the scheduling of simultaneous transmissions on the same channel. The performance evaluation is conducted using OPNET simulation tool. The results obtained through extensive simulations are compared with those of IEEE 802.11b/g/n single-hop and multi-hop wireless networks. We show that MIMOMAX is less efficient (low throughput and long delays) for single-hop networks. This is due to an under-utilization of channel Degrees of Freedom (DoFs). However, it always performs better (high throughput and low packet delay) than the 802.11b/g/n wireless multi-hop networks: up to 30\% and 87\% as improvements in network throughput compared to the IEEE 802.11n and IEEE 802.11g networks respectively. In addition, we illustrate that MIMOAX is robust and resists to the early network saturation problem.

In this work we focus on the application of an intra-flow linear random coding scheme over wireless mesh networks. We propose a cross-layer technique to balance the load between relaying nodes, considering the quality of the wireless links. We assess the performance of our proposal by means of an extensive simulation campaign carried out over the ns-3 platform, exploiting a channel model based on a Hidden Markov Process, which accurately mimics the bursty behavior that is observed over real indoor channels. The results show the benefits of the proposed cross-layer technique. In addition, we also discuss the trade-off (between accuracy and overhead) that needs to be considered when obtaining the information that such scheme rely on. Our simulations yield a 10% performance gain when exploiting the link quality information, as it is already obtained by various routing protocols.

Cross-layer Radio Resource Management (CL-RRM) has been recently investigated by quite a few research groups in wireless communications. In the specific satellite-networking environment, the paper presents an overview of different CL-RRM techniques devoted to dynamic bandwidth allocation, whose interactions span the physical, data link, network and transport layers, in various combinations. A multi-service setting is considered, in the presence of variations in both traffic and channel conditions. Regarding the latter, bit and coding rate adaptation are adopted as fade countermeasure, and their effect on the higher layers is modelled as a bandwidth reduction. Traffic models and methodologies for dynamic bandwidth allocation and performance optimization are discussed. Numerical examples are presented to highlight throughput/fairness trade-offs for long-lived TCP connections that share multiple channels with different fading depth. Copyright © 2006 John Wiley & Sons, Ltd.

International audience; In this paper, we propose a cross-layer analytical model for the study of Network Coding (NC)- based Automatic Repeat reQuest (ARQ) Medium Access Control (MAC) protocols in correlated slow faded (shadowed) environments, where two end nodes are assisted by a cluster of relays to exchange data packets. The goal of our work is threefold: i) to provide general Physical (PHY) layer theoretical expressions for estimating crucial network parameters (i.e., network outage probability and expected size of the active relay set), applicable in two-way communications, ii) to demonstrate how these expressions are incorporated in theoretical models of the upper layers (i.e., MAC), and iii) to study the performance of a recently proposed NC-aided Cooperative ARQ (NCCARQ) MAC protocol under correlated shadowing conditions. Extensive Monte Carlo experiments have been carried out to validate the efficiency of the developed analytical model and to investigate the realistic performance of NCCARQ. Our results indicate that the number of active relays is independent of the shadowing correlation in the wireless links and reveal intriguing trade-offs between throughput and energy efficiency, highlighting the importance of cross-layer approaches for the assessment of cooperative MAC protocols.

International audience; New mobile technology generations succeed in achieving high goodput, which results in diverse applications profiles exploiting various resource providers (Wifi, 4G, 5G, . . . ). Badly set parameters on one of the network component may severely impact on the transmission delay and reduce the quality of experience. The cross layer impact should be investigated on to assess the origin of latency. To run cross-layer (from physical layer to application layers) simulations, two approaches are possible: (1) use physical layer models that may not be exhaustive enough to drive consistent analysis or (2) use real physical traces. Driving realistic measurements by using real physical (MAC/PHY) traces inside network simulations is a complex task. We propose to cope with this problem by introducing Cross Layer InFormation Tool (CLIFT), that translates real physical events from a given trace in order to be used inside a network simulator such as ns-2. Our proposal enables to accurately perform analysis of the impact of link layer reliability schemes (obtained by the use of real physical traces) on transport layer performance and on the latency. Such approach enables a better understanding of the interactions between the layers. The main objective of CLIFT is to let us study the protocols introduced at each layer of the OSI model and study their interaction. We detail the internal mechanisms and the benefits of this software with a running example on 4G satellite communications scenarios.

Next-Generation Networks (NGNs), comprising for example, B4G and 5G cellular systems, will support Quality of Service (QoS) over a heterogeneous wired and wireless IP-based infrastructure. A relative model of service differentiation in DiffServ architecture is a scalable solution for delivering multimedia traffic. However, the dynamic nature of radio channels makes it difficult to achieve the target quality provisioning working separately at the IP and lower layers, as in the classical approach. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control. The objective is to implement a PDM on the whole at the network interface, as relevant for the end-users. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal with respect to both the classical and the open loop approaches. Considerations on the required functionality and possible deployment scenarios highlight the scalability and backward compatibility of the designed solution.

As systems-on-chip increase in complexity, the underlying technology presents us with significant challenges due to increased power consumption as well as decreased reliability. Today, designers must consider building systems that achieve the requisite functionality and performance using components that may be unreliable. In order to do so, it is crucial to understand the close interplay between the different layers of a system: technology, platform, and application. This will enable the most general tradeoff exploration, reaping the most benefits in power, performance and reliability. This paper surveys various cross layer techniques and approaches for power, performance, and reliability tradeoffs are technology, circuit, architecture and application layers. © 2013 Elsevier B.V. All rights reserved.

International audience; Transport layer performance in IEEE 802.11 multihop wireless networks (MHWNs) has been greatly challenged by wireless medium characteristics and multihop nature which induce several types of packet loss including collision, random channel errors and route failures. In this paper, we propose a novel rate control scheme, called Bi-Metric Rate Control (BMRC), which regulates efficiently the source rate in MHWNs. BMRC's design is based on two MAC metrics: the Medium Access Delay used to detect the network contention level, and the Average Transmission Time used to estimate the effective packet sending rate by which the network will not be overloaded. The simulation results show that the adapted mechanism introduces significant performance improvement in terms of fairness, packet loss rate and delay in MHWNs.

International audience; The evolution of the Internet has been mainly promoted in recent years by the emergence and proliferation of wireless access networks towards a global ambient and pervasive network accessed from mobile devices. These new access networks have introduced new MAC layers independently of the legacy “wire-oriented” protocols that are still at the heart of the protocol stacks of the end systems. This principle of isolation and independence between layers advocated by the OSI model has its drawbacks of maladjustment between new access methods and higher-level protocols built on the assumption of a wired Internet. In this paper, we introduce and deliver solutions for several pathological communication behaviors resulting from the maladjustment between WLAN MAC and higher layer standard protocols such as TCP/IP and UDP/IP. Specially, based on an efficient analytical model for WLANs bandwidth estimation, we address in this paper the two following issues: (1) Performance degradation due to the lack of flow control between the MAC and upper layer resulting in potential MAC buffer overflow; (2) Unfair bandwidth share issues between various type of flows. We show how these syndromes can be efficiently solved from neutral “cross layer” interactions which entail no changes in the considered protocols and standards.