Underlying Communication Infrastructure Research Articles

D4: Dynamic, Decentralized, Distributed, Delegation-Based Network Control and Its Applications to Autonomous Vehicles

Connected autonomous vehicles technology are expected to be an important component of Intelligent Transportation Systems (ITS). Several relevant industry standards are being created to prepare for the maturity of connected vehicles with the help of artificial intelligence, cognitive methods, software-hardware and sensor platforms. One of the significant challenges raised by connected vehicles is how the underlying communication infrastructure will be able to efficiently support them. In this paper, we propose the Dynamic, Decentralized, Distributed, Delegation-based (D4) network control plane architecture which aims at providing adequate communication support for connected vehicles. To our knowledge, D4 is the first framework to support on-demand network control decentralization. At its core, D4’s flexible network control delegation framework allows network control to be dynamically distributed on demand to address quality-of-service requirements of different connected vehicle services and applications. We demonstrate the benefits of D4 through a proof-of-concept prototype running on a fully reproducible emulation platform. Experimental results using a variety of real-world scenarios demonstrate that D4 delivers lower latency with minimal additional overhead. We also showcase the benefits of D4 when compared to traditional vehicular ad-hoc network (VANET) approaches.

Nodes selection review for federated learning in the blockchain‐based internet of things

AbstractInternet of Things (IoT) gained momentum these last few years pushed by the emergence of fast and reliable communication networks such as 5G and beyond. IoT depends on collecting information from the environment, leading to a significant increase in the amount of data generated that needs to be transmitted, saved, and analyzed. It is clear that classical deterministic approaches might not be suitable to this complex and fast evolving environment. Hence, machine learning techniques with their ability to handle such a dynamic context, are rising in popularity. In particular, Federated Learning architectures which are better suited to the distributed nature of IoT and its privacy concerns. Besides, to address security risks such as model poisoning, device compromise, and network interception, Blockchain (BC) is seen as the secure and distributed underlying communication infrastructure of choice. This integration of IoT, FL, and BC remains in its early stages and several challenges arise. Indeed, nodes selection to perform resource intensive and critical operations like model learning and transactions validation is a crucial issue considering the strong heterogeneity of the involved devices in terms of resources. In this paper, we propose an original literature review including a taxonomy, a thorough analysis, a comparison of the proposed approaches, along with some open research directions.

Enabling federated learning of explainable AI models within beyond-5G/6G networks

The quest for trustworthiness in Artificial Intelligence (AI) is increasingly urgent, especially in the field of next-generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge amount of devices and will offer innovative services empowered with AI and Machine Learning tools. Nevertheless, private user data, which are essential for training such services, are not an asset that can be unrestrictedly shared over the network, mainly because of privacy concerns. To overcome this issue, Federated Learning (FL) has recently been proposed as a paradigm to enable collaborative model training among multiple parties, without any disclosure of private raw data. However, the initiative to natively integrate FL services into mobile networks is still far from being accomplished. In this paper we propose a novel FL-as-a-Service framework that provides the B5G/6G network with flexible mechanisms to allow end users to exploit FL services, and we describe its applicability to a Quality of Experience (QoE) forecasting service based on a vehicular networking use case. Specifically, we show how FL of eXplainable AI (XAI) models can be leveraged for the QoE forecasting task, and induces a benefit in terms of both accuracy, compared to local learning, and trustworthiness, thanks to the adoption of inherently interpretable models. Such considerations are supported by an extensive experimental analysis on a publicly available simulated dataset. Finally, we assessed how the learning process is affected by the system deployment and the performance of the underlying communication and computation infrastructure, through system-level simulations, which show the benefits of deploying the proposed framework in edge-based environments.

Coupling OMNeT++ and Mosaik for Integrated Co-Simulation of ICT-Reliant Smart Grids

The increasing integration of renewable energy resources requires so-called smart grid services for monitoring, control and automation tasks. Simulation environments are vital for evaluating and developing innovative solutions and algorithms. Especially in smart energy systems, we face a variety of heterogeneous simulators representing, e.g., power grids, analysis or control components and markets. The co-simulation framework mosaik can be used to orchestrate the data exchange and time synchronization between individual simulators. So far, the underlying communication infrastructure has often been assumed to be optimal and therefore, the influence of e.g., communication delays has been neglected. This paper presents the first results of the project cosima, which aims at connecting the communication simulator OMNeT++ to the co-simulation framework mosaik to analyze the resilience and robustness of smart grid services, e.g., multi-agent-based services with respect to adaptivity, scalability, extensibility and usability. This facilitates simulations with realistic communication technologies (such as 5G) and the analysis of dynamic communication characteristics by simulating multiple messages. We show the functionality and benefits of cosima in experiments with 50 agents.

Analytical Design of Synchrophasor Communication Networks with Resiliency Analysis Framework for Smart Grid

The advent of synchrophasor technology has completely revolutionized the modern smart grid, enabling futuristic wide-area monitoring protection and control. The Synchrophasor Communication Network (SCN) is a backbone that supports communication of synchrophasor data among Phasor Measurement Units (PMUs) and Phasor Data Concentrators (PDCs). The operator at the control center can visualize the health of the smart grid using synchrophasor data aggregated at PDCs from several PMUs. Since the core of the SCN is the existing IP network as an underlying communication infrastructure, the synchrophasor data is subjected to attacks that can compromise its security. The attacks, such as denial-of-service (DoS), can result in degradation of performance and even can disrupt the entire operation of the smart grid, if not controlled. Thus, a resilient SCN is a pertinent requirement in which the system continues to operate with accepted levels of performance even in response to the DoS. This article endeavors to propose a comprehensive resiliency framework for the SCN with enhanced resiliency metrics based on hardware reliability and data reliability. The proposed framework is deployed for a SCN pertaining to a practical power grid in India for its resiliency analysis. The proposed work can be regarded as a significant contribution to smart grid technology, as it provides a framework for resiliency analysis covering different aspects such as hardware reliability, data reliability, and parameters validation using the QualNet network simulator. Nevertheless, an analytical design of the hybrid SCN proposed in this work can even be extended to other topological designs of SCN.

The Quantum Internet: Enhancing Classical Internet Services One Qubit at A Time

Nowadays, the classical Internet is mainly envisioned as the underlying communication infrastructure of the Quantum Internet, aimed at providing services such as signaling and coordination messages. However, the interplay between the classical and the quantum Internet is complex and its understanding is pivotal for an effective design of the Quantum Internet protocol stack. The aim of the article is to shed light on this interplay, by highlighting the fact that such an interplay is indeed bidirectional rather than unidirectional. The Quantum Internet exhibits the potential of supporting and even enhancing classical Internet functionalities.

Dynamic signal recovery in distribution grids using compressive lossy measurements

Distribution system state estimation requires reliable aggregation of the measured data. However, the large volume of the measured data imposes a significant stress on the underlying communication infrastructure. With the challenges associated with measurement availability, current distribution systems are typically unobservable. To cope with the unobservability issue, compressive sensing theory allows us to recover system state information from a small number of measurements provided the states of the distribution system exhibit sparsity. In this paper, we evaluate the robustness of an updated Kalman filtered modified compressive sensing (KF-ModCS) technique that dynamically estimates the grid states using a small fraction of measured data. In practice, measurements used for sparsity based state estimation may also be intermittent due to communication network induced losses. To understand the effect of packet losses on KF-ModCS, we provide an upper bound for the expected variances of the state estimation error for a given rate of information loss. This upper bound is further improved if the support set of the sparse signal that characterizes the state dynamics does not change over time and/or the reduced model is observable. Simulations based on two practical data sets collected from actual customers in a distribution grid validate the theoretical results.

Supporting Situational Awareness in VANET Attack Scenarios

The integration of sensors and communication technologies is enabling vehicles to become increasingly intelligent and autonomous. The Internet of Vehicles (IoVs) is built from intelligent vehicles that work collaboratively and interact with the surrounding environment in real time. The underlying communications infrastructure is provided by Vehicular Ad-hoc Networks (VANETs), for vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) communications. The volume of autonomous vehicles (AVs) increases, as well as the level of automation for vehicles. The potential for related incidents and attacks increases as a result. A particular concern is the ability to disseminate alerts and emergency messages effectively and securely via the V2V/V2I nodes, given the diminishing involvement of autonomous vehicle users with the operation of the autonomous vehicles.
 
 With this challenge in mind, this paper investigates the issue of situational awareness for occupants in autonomous vehicles. Building from the concept of VANETs and recognised classification of automation levels, the discussion considers a range of related attack scenarios that could be encountered, each of which illustrates also contexts in which occupants may need to be made aware and take decisions in response. Consideration is then given to resulting support for situational awareness that would be required, particularly highlighting the associated requirements for user responsibility at different levels of automation. The resulting discussion serves to articulate the challenge and serves as a basis for further research to inform the mechanisms to address the resulting requirements.

Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement

Real time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

Evaluation of Communication Infrastructures for Distributed Optimization of Virtual Power Plant Schedules

With the transition towards renewable energy resources, the impact of small distributed generators (DGs) increases, leading to the need to actively stabilize distribution grids. DGs may be organized in virtual power plants (VPPs), where DGs’ schedules must be coordinated to enable the VPP to act as a single plant. One approach to solving this problem is using multi-agent systems (MAS) to offer autonomous, robust, and flexible control methods. The coordination of such systems requires communication between agents. The time required for this depends on communication characteristics, determined by the underlying communication infrastructure. In this paper, we investigate communication influences for the wireless technologies CDMA450 and LTE Advanced on the fully distributed optimization heuristic COHDA, which is used to perform optimized scheduling for a VPP. The use case under consideration is the adaptation of schedules to provide flexibility for regional congestion management for delivery on a regionalized ancillary service market (rAS). We investigate the scalability of the VPP and the effects of disturbances in the communication infrastructure. The results show that the optimization duration of COHDA can be influenced by the underlying communication infrastructure and that this optimization method is applicable to a limited extent for product delivery of rASs.

An Analytical Model for Information Centric Internet of Things Networks in Opportunistic Scenarios

The availability of environmental monitoring data collected by Internet of Things networks can be essential for many critical processes, such as relief operations in disaster areas. The underlying communications infrastructure can be however severely compromised in these scenarios and therefore opportunistic approaches might be needed. Approaches based on information centric networks (ICN), where moving devices forward collected data, have been proposed for opportunistic scenarios but to date, the dynamics of the delivery process in ICNs remain poorly understood. In this paper, we build a family of Markovian models for the delivery process of ICNs in opportunistic scenarios, that allow us to derive the end-to-end delay distribution and the storage ratio in terms of the encounter rate of the moving devices. Furthermore, we investigate how prefetching mechanisms affect the delivery process compared to conventional ICNs. The proposed models are fully validated in a computer simulation environment and demonstrate that the utility of delivery with prefetching reaches its peak in a short time and then decreases at a high rate. Our Markovian models can provide both the insight and quantitative estimations that are needed to design practical ICNs in opportunistic scenarios.

Sparsity Based Approaches for Distribution Grid State Estimation - A Comparative Study

The power distribution grid is typically unobservable due to a lack of measurements. While deploying more sensors can alleviate this issue, it also presents new challenges related to data aggregation and the underlying communication infrastructure. Therefore, developing state estimation methods that enhance situational awareness at the grid edge with compressed measurements is critical. For this purpose, a suite of sparsity-based approaches that exploit the correlation among states/measurements in spatial as well as temporal domains have been proposed recently. This article presents a systematic comparison and evaluation of these approaches. Specifically, the performance and complexity of spatial methods (1-D compressive sensing and matrix completion) and spatio-temporal methods (2-D compressive sensing and tensor completion) are compared using the IEEE 37 and IEEE 123 bus test systems. Additionally, new robust formulations of these sparsity-based methods are derived and shown to be robust to bad data and network parameter uncertainties. Among the sparsity-based approaches, compressive sensing methods tend to outperform matrix completion and tensor completion methods in terms of error performance.

Discrete Spectrum Iteration Based Comprehensive Stability Assessment Method for the Delayed Cyber-Physical System With Electric-Vehicle Frequency Regulation

Nowadays, the increasing penetration of renewable energies often leads to system frequency variation due to the intermittent outputs, which limits the utilization of renewable electricity and brings higher requirements to frequency regulation. Aggregated electric vehicles (EVs) are suggested to be used as good regulation resources because of the vehicle-to-grid (V2G) capability and quick response characteristic. However, the participation of EVs inevitably leads to cyber delays due to their underlying communication infrastructure and scheduling, which may cause instability. To guarantee the system stability, this paper investigates the stability of a grid frequency regulation system with electric vehicle (EV) aggregators embedded by cyber delays in the cyber system. A comprehensive stability assessment method is proposed in this paper based on the discrete spectrum iteration. A stability assessment method flow is designed with only five stages: 1) system initialization and modeling; 2) spectrum transformation; 3) Chebyshev discretization; 4) Krylov subspace projection dimension reduction; 5) Newton correction. Comprehensive case studies are performed on the cyber regulation systems with single, double, and three EV aggregators to extract the stability region and to validate the proposed approach. It is revealed that the controller gain, the ratio between the participation ratios of each aggregator, and that between EV and grid are important factors for determining the stability of the regulation system at a given controller gain. Besides, the criterion of the stability region changing with the three factors is proposed. It is found that the mass utilization of electric vehicles in the frequency control disrupts system stability due to the aggregation delay and thus the stability region can be divided into several intervals and presents periodicity. It is expected that the proposed criteria can help to guide the determination of delay requirements for EV aggregators participating in frequency regulation service.

Virtual Channel aware Scheduling for Real Time Data-Flows on Network on-Chip

The increasing complexity of real-time applications presents a challenge to researchers and software designers. The tasks of these applications usually exchange large volume of data-flows and often need to satisfy real-time constraints. Although the Network on-Chip (NoC) paradigm offers an underlying communication infrastructure that gives more hardware resources, it is unable to safe tasks and data-flows deadlines. In recent works, preemptive wormhole switching with fixed priority has been introduced to meet real-time constraints of real-time applications. However, it suffers some bottleneck such as hardware requirement where none of these works takes account of the number of implemented virtual channels on the router. To alleviate this problem, we propose a novel scheduler for soft real-time data-flows application that takes into account the lack on resource in routers in term of Virtual channels. Experimental results obtained on a benchmark of synthetic and soft real applications have shown the efficiency of our approach in term of real-time constraints satisfaction for data-flow traffics and hardware requirements.

ADYTIA: Adaptive and Dynamic TCP Interface Architecture for heterogeneous networks

SummaryDue to the widespread popularity and usage of Internet of things (IoT)‐enabled devices, there is an exponential increase in the data traffic generated from these IoT devices. Most of these devices communicate with each other using heterogeneous links having constraints such as latency, throughput, and interference from concurrent transmissions. This results in an extra burden on the underlying communication infrastructure to manage the traffic within these constraints between source and destination. However, most of the existing applications use different Transmission Control Protocol (TCP) variants for traffic management between these devices and are dependent on the stage of the sender, irrespective of the application types and link characteristics. Each operating system (OS) has different TCP variant for all applications, irrespective of path characteristics. Hence, a single TCP variant cannot select the best suitable link, which results in degradation in throughput compared to the existing default. Moreover, it cannot use the full capacity of the available link for different applications and network links, especially in heterogeneous network such as IoT. To cope up with these challenges, in this paper, we propose an Adaptive and Dynamic TCP Interface Architecture (ADYTIA). ADYTIA allows the usage of different TCP variants based on application and link characteristics, irrespective of the physical links of the entire path. It allows the usage of different TCP variants based on their design principle across heterogeneous technologies, platforms, and applications. ADYTIA is implemented on NS‐2 and Linux kernel for real testbed experiments. Its ability to select the best suitable TCP variant results in 20% to 80% improvement in throughput compared with the existing default and single TCP variant on Linux and Windows.

Towards optimized exchange topologies in smart distribution grids

The smart grid is a highly relevant application area for distributed algorithms. Many of these algorithms use a predefined topology to control the information exchange between the distributed entities. Consequently, this exchange topology has a strong impact on the performance of the distributed algorithm. For several algorithms their distributed nature is part of the algorithm itself. Furthermore, the properties of the virtual links defined by the exchange topology are determined by the characteristics of the underlying communication infrastructure (CIS). This work aims to design optimized exchange topologies that support certain distributed algorithms that can be used for reactive scheduling in smart distribution grids. For this purpose, supportable algorithms have to be identified and their communication requirements have to be derived. In addition, relevant properties and a suitable degree of abstraction of the CIS have to be determined. Finally it has to be investigated whether properties of the smart grid and the distributed energy resources (DER) and controllable loads are significant factors that can be used to achieve an increased performance of the supported algorithm.

On the Performance of Distributed and Cloud-Based Demand Response in Smart Grid

By locally solving an optimization problem and broadcasting an update message over the underlying communication infrastructure, demand response program based on the distributed optimization model encourage all users to participate in the program. However, some challenging issues present themselves, such as the existence of an ideal communication network, especially, when utilizing wireless communication, and the effects of communication channel properties, like the bit error rate, on the overall performance of the demand response program. To address the issues, this paper first defines a cloud-based demand response (CDR) model, which is implemented as a two-tier cloud computing platform. Then a communication model is proposed to evaluate the communication performance of both the CDR and distributed demand response models. This paper shows that when users are finely clustered, the channel bit error rate is high and the user datagram protocol (UDP) is leveraged to broadcast the update messages, making the optimal solution unachievable. Contradictory to UDP, the transmission control protocol will be caught up with a higher bandwidth and increase the delay in the convergence time. Finally, this paper presents a cost-effectiveness analysis which confirms that achieving higher demand response performance incurs a higher communication cost.

Standards for Major Internet Disruptors: Blockchain, Intents, and Related Paradigms

The six articles in this special section address major issues concerned with evolving standardization processes and underlying technologies in the context of Blockchain for different application domains, showing how distributed ledger technologies can be so disruptive that they can change the Internet as we know it. Software is envisioned to play an unprecedented dominant role in future communication paradigms, with user-defined applications capable of not only communicating with, but also controlling some features of the underlying communication infrastructure in a secure and trustworthy manner. This (r)evolutionary trend toward virtualized and “softwarized” networks enable Internet-based service users and providers, as well as the related stakeholders, to take advantage of resource abstractions and to adopt a programmatic approach to service deployment. In a “game-changing” scenario, a user’s needs can be decoupled and expressed independently of the specific underlying implementable technology, but yet the requested service must meet the expected mutual trustiness and security levels. This trend opens a number of disruptive solutions that can change the Internet as we know it.

A New Mileage Payment for EV Aggregators With Varying Delays in Frequency Regulation Service

Electric vehicle (EV) aggregators participating in frequency regulation services with a large number of EVs may have a delayed response problem due to their underlying communication infrastructure and scheduling. In this paper, we investigate the effect of delays in EV aggregators’ domain on their frequency regulation payments, especially mileage payment. Since the delays affect frequency regulation performance, in order to consider the delay effect on regulation performance, we enhance the conventional load frequency control model by including multiple EV aggregators with varying delays. Under this model, we evaluate the effect of delays in EV aggregators’ domain on their profits under two ISOs’ mileage payments such as PJM and NYISO. Through simulations, it is shown that the profit of EV aggregators increases as the delays increases. The conventional mileage payments did not motivate EV aggregators to reduce the delay in order to improve regulation performance. To solve the problem, we propose a new mileage payment to reduce the delay. We finally show that the proposed payment can provide an incentive to reduce the delay.

ICT Based Performance Evaluation of Primary Frequency Control Support from Renewable Power Plants in Smart Grids

The increased penetration of Renewable Energy Generation (ReGen) plants in future power systems poses several challenges to the stability of the entire system. In future green energy rich power systems, the responsibility for providing ancillary services will be shifted from conventional power plants towards ReGen plants, such as wind and photovoltaic power plants. Frequency control support from the Wind Power Plants (WPPs) is one of the crucial ancillary services in order to preserve operational stability in case of grid disturbances. Among other requirements, the ability to provide fast frequency control support from ReGen plants will highly depend on the underlying communication infrastructure that allows an exchange of information between different ReGen plants and the control centers. This paper, therefore, focuses on the evaluation of the impact of communication and the related aspects to provide online frequency control support from ReGen (with special focus on WPP). The performance evaluation is based on an aggregated WPP model that is integrated into a generic power system model. This generic power system model is specifically designed to assess the ancillary services in a relatively simple yet relevant environment. Several case studies with different wind speeds at a particular wind-power penetration level and communication scenarios are considered to evaluate the performance of power system frequency response. The article provides the Transmission System Operator (TSO) and other communication engineers insights into the importance and various aspects of communication infrastructure for general service coordination between WPPs and specifically primary frequency control coordination from WPPs in future power systems.