Upper-layer Protocols Research Articles

QUIC Throughput and Fairness over Dual Connectivity

Dual Connectivity (DC) is an important lower-layer feature accelerating the transition from 4G to 5G that also is expected to play an important role in standalone 5G radio networks. However, even though the packet reordering introduced by DC can significantly impact the performance of upper-layer protocols, no prior work has studied the impact of DC on QUIC. In this paper, we present the first such performance study. Using a series of throughput and fairness experiments, we show how QUIC is affected by different DC parameters, network conditions, and whether the DC implementation aims to improve throughput or reliability. Results for two QUIC implementations (aioquic, ngtcp2) and two congestion control algorithms (NewReno, CUBIC) are presented under both static and highly time-varying network conditions Our findings provide network operators with insights and understanding into the impacts of splitting QUIC traffic in a DC environment. With reasonably selected DC parameters and increased UDP receive buffers, QUIC over DC performs similarly to TCP over DC and achieves optimal fairness under symmetric link conditions when DC is not used for packet duplication. The insights can help network operators provide modern users with better end-to-end service when deploying DC.

A Novel Packet End-to-End Delay Estimation Method for Heterogeneous Networks

The estimation of the end-to-end delay in modern communication networks is of high importance to support multiple services but also for the management of the network resources. In this paper, we propose an end-to-end delay model and estimation methodology for heterogeneous networks. The estimation method allows the computation of the end-to-end delay distribution parameters when a small number of end-to-end delay samples is available through probe packets. The proposed technique is evaluated for different datasets, including networks operating with multiple access technologies and different upper-layer protocols, so the heterogeneity of the networks and protocols can be taken into account. The evaluation results show that the Generalized Extreme Value distribution can be used to approximate the end-to-end delay and high accuracy is achieved even when only a small number of probe packets is available. Finally, the estimation error confirms the effectiveness of the proposed method for a broad range of network scenarios.

(Semi-)Automatically Parsing Private Protocols for In-Vehicle ECU Communications

In-vehicle electronic control unit (ECU) communications generally count on private protocols (defined by the manufacturers) under controller area network (CAN) specifications. Parsing the private protocols for a particular vehicle model would be of great significance in testing the vehicle’s resistance to various attacks, as well as in designing efficient intrusion detection and prevention systems (IDPS) for the vehicle. This paper proposes a suite of methods for parsing ECU private protocols on in-vehicle CAN network. These methods include an algorithm for parsing discrete variables (encoded in a discrete manner, e.g., gear state), an algorithm for parsing continuous variables (encoded in a continuous manner, e.g., vehicle speed), and a parsing method based on upper-layer protocols (e.g., OBD and UDS). Extensive verifications have been performed on five different brands of automobiles (including an electric vehicle) to demonstrate the universality and the correctness of these parsing algorithms. Some parsing tips and experiences are also presented. Our continuous-variables parsing algorithm could run in a semi-automatic manner and the parsing algorithm from upper-layer protocols could execute in a completely automatic manner. One might view the results obtained by our parsing algorithms as an important indicator of penetration testing on in-vehicle CAN network.

Understanding commercial 5G and its implications to (Multipath) TCP

In this paper, we perform an empirical study on commercial 5G. Unlike previous works studying 5G in early deployments, we focus on fully deployed 5G networks that already serve massive numbers of users, and in particular, we perform controlled experiments to analyze TCP and multipath TCP (MPTCP) performances and behaviors over 5G. Our results show that 5G faces a dilemma in maintaining in-network buffer for TCP traffic: on one hand, TCP packets are less likely to accumulate within the network, thanks to the high data rate of 5G radio; but on the other hand, with TCP performance highly sensitive to signal quality, when signal becomes poor abruptly in mobile environment, the in-network buffer easily overflows, leading to packet loss bursts. We also confirm that employing MPTCP can aggregate capacities on 5G and 4G paths, but under the current deployment model where 5G and 4G base stations co-locate and share the same core network, MPTCP does not necessarily enhance communication reliability. In addition to active measurement experiments, we leverage a speedtest service to evaluate commercial 5G from a nationwide perspective. By exploiting over 13k crowdsourced speedtest results reported from 197 cities in China, we find that there exist considerable regional differences on 5G performances across the nation, and with the 4G co-locating deployment model, the 5G networks in some populous metropolitan areas have inferior performances. Our study provides insights for people to understand commercial 5G and to optimize upper-layer protocols and applications over 5G.

Device Discovery and Context Registration in Static Context Header Compression Networks

Due to the limited bandwidth of Low-Power Wide-Area Networks (LPWAN), the application layer is currently often tied straight above the link layer, limiting the evolution of sensor networks distributed over a large area. Consequently, the highly efficient Static Context Header Compression (SCHC) standard was introduced, where devices can compress the IPv6 and upper layer protocols down to a single byte. This approach, however, assumes that every compression context is distributed before deployment, again limiting the evolution of such networks. Therefore, this paper presents two context registration mechanisms leveraging on the SCHC adaptation layer. This is done by analyzing current registration solutions in order to find limitations and optimizations with regard to very constrained networks. Both solutions and the current State-of-The-Art (SoTA) are evaluated in a Lightweight Machine to Machine (LwM2M) environment. In such situation, both developed solutions decrease the energy consumption already after 25 transmissions, compared with the current SoTA. Furthermore, simulations show that Long Range (LoRa) devices still have a 80% chance to successfully complete the registration flow in a network with a 50% Packet Error Ratio. Briefly, the work presented in this paper delivers bootstrapping tools to constrained, SCHC-enabled networks while still being able to reduce energy consumption.

Authenticating On-Body IoT Devices: An Adversarial Learning Approach

By adding users as a new dimension to connectivity, on-body Internet-of-Things (IoT) devices have gained considerable momentum in recent years, while raising serious privacy and safety issues. Existing approaches to authenticate these devices limit themselves to dedicated sensors or specified user motions, undermining their widespread acceptance. This paper overcomes these limitations with a general authentication solution by integrating wireless physical layer (PHY) signatures with upper-layer protocols. The key enabling techniques are constructing representative radio propagation profiles from received signals, and developing an adversarial multi-player neural network to accurately recognize underlying radio propagation patterns and facilitate on-body device authentication. Once hearing a suspicious transmission, our system triggers a PHY-based challenge-response protocol to defend in depth against active attacks. We prove that at equilibrium, our adversarial model can extract all information about propagation patterns and eliminate any irrelevant information caused by motion variances and environment changes. We build a prototype of our system using Universal Software Radio Peripheral (USRP) devices and conduct extensive experiments with various static and dynamic body motions in typical indoor and outdoor environments. The experimental results show that our system achieves an average authentication accuracy of 91.6%, with a high area under the receiver operating characteristic curve (AUROC) of 0.96 and a better generalization performance compared with the conventional non-adversarial approach.

Reversal operator to compensate polarization random drifts in quantum communications.

A quantum bit error rate (QBER) based algorithm for polarization random drift compensation is proposed. For a transmission window of 8 ms, for instance in aerial fiber installations, the algorithm overhead is below 1%. In an extreme turbulent situation, where the transmission window is as shorter as 0.8 ms, the overhead is still below 10%. Besides being able to operate smoothly, even in a very extreme situation, the algorithm overhead is also insensitive to the length of the communication system. It is upper layer protocol agnostic, and it is based on the mapping of the QBER on the Poincaré sphere. The algorithm finds the polarization reversal operator, which results in much lower overhead contrary to the blind methods currently used. The algorithm reverts the polarization random drift performing two QBER estimations and applying three rotations, at most. The uncertainty on the two QBER estimations defines an area over the sphere surface that is related with upper-layer protocols QBER threshold.

Survivability Aware Channel Allocation in WSN for IoT applications

The Proliferation of the Internet of Things applications like healthcare monitoring services and others has accelerated the demand for wireless networks of tiny devices. Network congestion escalates as the number of field devices with wireless connectivity increases. An efficient medium access control strategy that provides a reliable channel by reducing the packet collision is paramount in these congested network topologies. MAC protocols should evaluate properties of the links before allowing nodes to access the shared medium. Network survivability is an important attribute to be considered in IoT scenarios and has multiple stratifications; path, link, and node survivability. Protocols at various layers of protocol stack should operate jointly to prolong the network survivability. This work develops a Survivability Aware Channel Allocation (SACA) technique which is a fuzzy-based mechanism that enables the network components to adapt the preferences to get the channel access. It works along with upper layer protocols with a cross-layer design to prioritize medium access strategies. Simulation results suggest that the proposal works better in terms of network throughput and packet delivery rate and improves the reliability of the network. The new method operates at every node and tries to control performance degradation as the network density expands.

IEEE Access Special Section Editorial: Underwater Wireless Communications and Networking

Underwater wireless communications (UWC) has been playing an important role in marine activities for the second half of the 20th century. Ranging from military purposes in its early stages to today’s industrial and non-profit applications such as environmental monitoring, oceanographic data collection, disaster monitoring, and underwater resource exploration, there has been a growing interest in the realization of underwater wireless networks. However, practical applications often require significant data bandwidth. Such requirements are not always met by the design of current UWC systems, which are challenged by the unique and harsh conditions of underwater communication channels, including for example severe attenuation, multipath dispersion, and limited capability to exploit channel resources. Recently, many academic and industrial researchers have worked on the improvement of UWC systems by augmenting them with state-of-the-art information and communication technologies. There have been reports of new results and insight on the fundamental theories and practical implementations of UWC systems, i.e., UWC channel models and estimation, digital signal processing, advanced transceiver design, multiple access (MAC), and routing and upper-layer protocols, aswell as successful cross-layer design implementations.

Modeling Network-Controlled Device-to-Device Communications in SimuLTE.

In Long Term Evolution-Advanced (LTE-A), network-controlled device-to-device (D2D) communications allow User Equipments (UEs) to communicate directly, without involving the Evolved Node-B in data relaying, while the latter still retains control of resource allocation. The above paradigm allows reduced latencies for the UEs and increased resource efficiency for the network operator, and is therefore foreseen to support several services, from Machine-to-machine to vehicular communications. D2D communications introduce research challenges that might affect the performance of applications and upper-layer protocols, hence simulations represent a valuable tool for evaluating these aspects. However, simulating D2D features might pose additional computational burden to the simulation environment. To this aim, a careful modeling is required to reduce computational overhead. In this paper, we describe our modeling of network-controlled D2D communications in SimuLTE, a system-level LTE-A simulation library based on OMNeT++. We describe the core modeling choices of SimuLTE, and show how these allow an easy extension to D2D communications. Moreover, we describe in detail the modeling of specific problems arising with D2D communications, such as scheduling with frequency reuse, connection mode switching and broadcast transmission. We document the computational efficiency of our modeling choices, showing that simulation of D2D communications is not more complex than simulation of classical cellular communications of comparable scale. Results show that the heaviest computational burden of D2D communication lies in estimating the Sidelink channel quality. We show that SimuLTE allows one to evaluate the interplay between D2D communication and end-to-end performance of UDP- and TCP-based services. Moreover, we assess the accuracy of using a binary interference model for frequency reuse, and we evaluate the trade-off between speed of execution and accuracy in modeling the reception probability.

Electrophysiological evaluation of Tourette syndrome and prediction of treatment outcome

In the future generation mission-centric tactical network, 3D UAV mesh network will play a crucial role for its several advantages. However, any adversarial node with the 3D movement capability poses a significant threat to these networks as the adversary can position itself to attack the crucial links. An adaptive beamnulling antenna is used to spatially filter out signal coming from a certain direction that can maintain the links active without requiring additional spectrum. However, determining the beamnull region is very challenging for jammer with mobility. This paper presents a distributed mechanism where nodes measure the jammer’s direction in a discrete interval and determine the optimal beamnull for the next interval. Kalman filter based tracking mechanism is used to estimate the most likely trajectory of the jammer from noisy observation of the jammer’s position. A beam null border is determined by calculating confidence region of jammer’s current and next position estimates. An optimization goal is presented to determine the optimal beam null that minimizes the number of deactivated links while maximizing the higher value of confidence for keeping the jammer inside the null. The framework works in the physical layer and can work with any upper layer protocol. The survivability of a 3D mesh network with a mobile jammer is studied through simulation that validates an 96.65% reduction in the number of jammed nodes.

Comparative study of congestion notification techniques for hop‐by‐hop‐based flow control in data centre Ethernet

Data centre Ethernet (DCE) is a budding research area that has received considerable attention from the ICT sector. The traditional DCEs are considered unreliable despite being widely used in modern day data centres. In Ethernet intermediate layer 2 switching devices, the outgoing traffic is faster than the incoming traffic and therefore results in packet drops. Ethernet reliability is provided by the upper layer protocols, which is outlaw to the initial concept of the network. As such, various congestion notification (CN) techniques for hop-by-hop-based flow control have been proposed for layer 2 devices to address the issue of silent packet drops. However, a simulation-based evaluation of IEEE standards that solely focus on CN techniques remains lacking. This study investigates CN techniques for layer 2 devices that employ a hop-by-hop-based flow control. It also highlights the challenges confronting CN techniques in determining the optimal buffer threshold. In addition, FCoE protocol and its relation to CN are emphasized. A simulation-based evaluation of IEEE standards (IEEE 802.3x and IEEE 802.1Qbb) is performed on a hop-by-hop-based flow control with the traditional IEEE 802.3 Ethernet under different traffic loads. The parameters, such as throughput, end-to-end delay, and buffer space utilization, are evaluated through a simulation-based comparison.

LinkForecast: Cellular Link Bandwidth Prediction in LTE Networks

Accurate cellular link bandwidth prediction can benefit upper-layer protocols significantly. In this paper, we investigate how to predict cellular link bandwidth in LTE networks. We first conduct an extensive measurement study in two major commercial LTE networks in the US, and identify five types of lower-layer information that are correlated with cellular link bandwidth. We then develop a machine learning based prediction framework, LinkForecast , that identifies the most important features (from both upper and lower layers) and uses these features to predict link bandwidth in real time. Our evaluation shows that LinkForecast is lightweight and the prediction is highly accurate: At the time granularity of one second, the average prediction error is in the range of 3.9 to 17.0 percent for all the scenarios we explore. We further investigate the prediction performance when using lower-layer features obtained through standard APIs provided by the operating system, instead of specialized tools. Our results show that, while the features thus obtained have lower fidelity compared to those from specialized tools, they lead to similar prediction accuracy, indicating that our approach can be easily used over commercial off-the-shelf mobile devices.

Securing On-Body IoT Devices By Exploiting Creeping Wave Propagation

On-body devices are an intrinsic part of the Internet-of-Things (IoT) vision to provide human-centric services. These on-body IoT devices are largely embedded devices that lack a sophisticated user interface to facilitate traditional pre-shared key-based security protocols. Motivated by this real-world security vulnerability, this paper proposes SecureTag, a system designed to add defense in depth against active attacks by integrating physical layer (PHY) information with upper-layer protocols. The underpinning of SecureTag is a signal processing technique that extracts the peculiar propagation characteristics of creeping waves to discern on-body devices. Upon overhearing a suspicious transmission, SecureTag initiates a PHY-based challenge-response protocol to mitigate attacks. We implement our system on different commercial off-the-shelf wearables and a smartphone. Extensive experiments are conducted in a lab, apartments, malls, and outdoor areas, involving 12 volunteer subjects of different age groups, to demonstrate the robustness of our system. Results show that our system can mitigate 96.13 % of active attack attempts while triggering false alarms on merely 5.64 % of legitimate traffic.

Distributed adaptive beam nulling to survive against jamming in 3D UAV mesh networks

In the future generation mission-centric tactical network, 3D UAV mesh network will play a crucial role for its several advantages. However, any adversarial node with the 3D movement capability poses a significant threat to these networks as the adversary can position itself to attack the crucial links. An adaptive beamnulling antenna is used to spatially filter out signal coming from a certain direction that can maintain the links active without requiring additional spectrum. However, determining the beamnull region is very challenging for jammer with mobility. This paper presents a distributed mechanism where nodes measure the jammer’s direction in a discrete interval and determine the optimal beamnull for the next interval. Kalman filter based tracking mechanism is used to estimate the most likely trajectory of the jammer from noisy observation of the jammer’s position. A beam null border is determined by calculating confidence region of jammer’s current and next position estimates. An optimization goal is presented to determine the optimal beam null that minimizes the number of deactivated links while maximizing the higher value of confidence for keeping the jammer inside the null. The framework works in the physical layer and can work with any upper layer protocol. The survivability of a 3D mesh network with a mobile jammer is studied through simulation that validates an 96.65% reduction in the number of jammed nodes.

Asynchronous and Selective Transmission for DeWiring of Building Management Systems

In this paper, we show a design and implementation of a (partial) wireless building management system (BMS). Compared to the existing wired BMS, a wireless system can be much cheaper and more flexible in deployment. There are existing studies on smart and wireless BMS. Our design differs from others as the latter usually takes a re-arch approach and develops a brand new suite of protocols. However, it can take a considerably long time for re-standardization and adoption by vendors. Our design does not intend to tear down the full suite of upper layer protocols. We thus face difficulties as we need to maintain the upper layer protocols in operation and support their data traffic. The key ideas of our approach are an asynchronous-response framework to maintain the control plane of the upper layer protocols intact, and a modular design to prioritize and schedule data flow to handle link quality and throughput variations. We implemented the proposed design into a real system and evaluated the system by comprehensive experiments with real BMS controllers and software. In addition, we conducted a field deployment by integrating our system with the BMS in FG-building of The Hong Kong Polytechnic University. The system operated smoothly during 5-h deployment.

Field classification-based novel fuzzing case generation for ICS protocols

An industrial control system combined with IT is not a special thing; however, cyber security in this field does not mature. Therefore, vulnerability analysis techniques for protocols used in this field are clearly needed. In this paper, we propose a novel test case generation technique for a fuzzing test that can be used for various industrial control system protocols. The proposed fuzzing test is designed for generating a cross-field fuzzing test case because of field dependencies, a characteristic of industrial control system protocols. Additionally, we focus on multilayer testing because the weaknesses of lower layer protocols are inherited by upper layer protocols.

Design, implementation, and evaluation of an XG-PON module for the ns-3 network simulator

10-gigabit-capable Passive Optical Network (XG-PON), one of the latest standards of optical access networks, is regarded as one of the key technologies for future Internet access networks. This paper presents the design and evaluation of our XG-PON module for the ns-3 network simulator. This module is designed and implemented with the aim to provide a standards-compliant, configurable, and extensible module that can simulate XG-PON with reasonable speed and support a wide range of research topics. These include analyzing and improving the performance of XG-PON, studying the interactions between XG-PON and the upper-layer protocols, and investigating its integration with various wireless networks. In this paper, we discuss its design principles, describe the implementation details, and present an extensive evaluation on both functionality and performance.

Impact of IEEE 802.11n/ac PHY/MAC High Throughput Enhancements on Transport and Application Protocols—A Survey

Since the inception of IEEE 802.11 wireless local area networks (WLANs) in 1997, wireless networking technologies have tremendously grown in the last few decades. The fundamental IEEE 802.11 physical (PHY) and medium access control (MAC) protocols have continuously been enriched with new technologies to provide the last mile wireless broadband connectivity to end users. Consequently, several new amendments of the basic IEEE 802.11 gradually came up in the forms of IEEE 802.11a, IEEE 802.11b, and IEEE 802.11g. More recently, IEEE 802.11n, IEEE 802.11ac, and IEEE 802.11ad are introduced with enhanced PHY and MAC layers that boost up physical data rates to the order of Gigabit per second. So, these amendments are generally known as high throughput WLANs (HT-WLANs). In HT-WLANs, PHY layer is enhanced with multiple-input multiple-output antenna technologies, channel bonding, short guard intervals, enhanced modulation and coding schemes. The MAC sublayer overhead is reduced by introducing frame aggregation and block acknowledgement technologies. However, several existing studies reveal that, many a time, the aforesaid PHY and MAC enhancements yield negative impact on various upper layer protocols, that is end-to-end transport and application layer protocols. As a consequence, a large number of researchers have focused on improving the coordination among PHY/MAC and upper layer protocols. In this survey, we discuss impact of HT-WLAN PHY and MAC layer enhancements on various transport and application layer protocols. This paper also summarizes several research works that use aforesaid enhancements effectively to boost up data rate of end-to-end protocols. We also point out limitations of the existing researches and list down different open challenges that can be meaningfully explored for the development of the next generation HT-WLAN technologies.

Hypermedia APIs for the Web of Things

The Web of Things is a new and emerging concept that defines how the Internet of Things can be connected using common Web technologies, by standardizing device interactions on upper-layer protocols. Even for devices that can only communicate using proprietary vendor technologies, upper-layer protocols can generally provide the necessary contact points for a high degree of interoperability. One of the major development issues for this new concept is creating efficient hypermedia-enriched application programming interfaces (APIs) that can map physical Things into virtual ones, exposing their properties and functionality to others. This paper does an in-depth comparison of the following six hypermedia APIs: 1) the JSON Hypertext Application Language from IETF; 2) the Media Types for Hypertext Sensor Markup from IETF; 3) the Constrained RESTful Application Language from IETF’; 4) the Web Thing Model from Evrythng; 5) the Web of Things Specification from W3C; and 6) the Web Thing API from Mozilla.