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Vehicles will be wirelessly connected in the future and they will be able to exchange information with other vehicles and their surroundings for safer and more efficient driving. 5G communication systems have introduced advanced functionalities and radio solutions to support connected, cooperative, and automated mobility (CCAM) services with demanding Quality of Service (QoS) requirements. However, interoperability among involved stakeholders, seamless connectivity and the uninterrupted delivery of real-time services across borders are issues that should be carefully analyzed for the realization of crossborder CCAM services. This paper provides an overview of key standardization bodies by analyzing recent work on key technologies to provide cross-border connectivity services for CCAM. Standardization gaps and regulatory barriers that may affect fast and efficient adoption of 5G-enabled CCAM services, are also discussed.

The transformative Internet-of-Vehicles (IoV) paradigm comes inadvertently with challenges which involve security vulnerabilities and privacy breaches. In this context, denial-of-service (DoS) attacks may perniciously affect the normal operation of IoV systems by causing extensive periods of network unavailability where legitimate vehicles are prevented from accessing vehicular services. In this paper, we offer an in-depth vulnerability assessment of 5G-enabled IoV systems when DoS attack variants are launched at multiple network domains. We further evaluate the resilience of an IoV-tailored authentication mechanism against DoS attacks under various configurations. A data-driven detection scheme is also proposed to address DoS variants in the radio access network, which take the form of false data injection attacks on the exchanged vehicular information. Our performance assessment with the aid of an open-source dataset reveals that the proposed scheme is able to accurately detect DoS traffic originated from malicious vehicles. © 2022 IEEE.

Emerging vehicle-to-everything (V2X) services rely on the secure exchange of periodic messages between vehicles and between vehicles and infrastructure. However, transmission of false/incorrect data by malicious vehicles may pose important security perils. Therefore, it is essential to detect safety-threatening erroneous information and mitigate potentially detrimental effects on road users. In this paper, we assess the effectiveness of a reinforcement learning (RL) approach for misbehaviour detection in V2X scenarios using an open-source dataset. Considering the case of sudden-stop attacks, the performance of RL-based detection is evaluated over commonly used detection metrics. Our research outcomes reveal that misbehaving vehicles can be accurately detected by exploiting real-time position and speed patterns., Grant numbers : 2014 SGR 1551 - Grup de Tecnologies de Comunicacions and SPOT5G - Single Point of attachment communications heterogeneous mobile data networks (TEC2017-87456-P) projects.© 2021 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.

Vehicle-to-everything (V2X) communications enable real-time information exchange between vehicles and infrastructure, which extends the perception range of vehicles beyond the limits of on-board sensors and, thus, facilitating the realisation of cooperative, connected, and automated mobility (CCAM) services that will improve road safety and traffic efficiency. In the context of CCAM, the successful deployments of cooperative intelligent transport system (C-ITS) use cases, with the integration of advanced wireless communication technologies, are effectively leading to make transport safer and more efficient. However, the evaluation of multi-vendor and multi-protocol based CCAM service architectures can become challenging and complex. Additionally, conducting on-demand field trials of such architectures with real vehicles involved is prohibitively expensive and time-consuming. In order to overcome these obstacles, in this paper, we present the development of a standards-compliant experimental vehicular on-board unit (OBU) that supports the integration of multiple V2X protocols from different vendors to communicate with heterogeneous cloud-based services that are offered by several original equipment manufacturers (OEMs). We experimentally demonstrate the functionalities of the OBU in a real-world deployment of a cooperative collision avoidance service infrastructure that is based on edge and cloud servers. In addition, we measure end-to-end application-level latencies of multi-protocol supported V2X information flows to show the effectiveness of interoperability in V2X communications between different vehicle OEMs.

The fifth generation (5G) of communication networks aims to accelerate the adoption of incipient vertical industries which will leverage innovative smart applications and services such as Cooperative, Connected and Automated Mobility. One of the objectives globally within that area is reducing to zero the number of fatal vehicle accidents. Unfortunately, human errors are the main cause of them, where vulnerable road users (VRUs) are involved in half of the cases. A possible approach to reduce accidents is estimating the probability of collision between two vehicles based on their estimated trajectories. These trajectories are usually tracked on-board using sophisticated devices such as cameras and LiDAR. However, VRUs are generally not equipped with such equipment and, ideally, VRUs carry smartphones with active geolocation capabilities based on satellite-based positioning systems. In this paper, we propose a novel vehicular service based on a regression algorithm to predict trajectories by uniquely using Cartesian coordinates. We compare different types of regression techniques in terms of prediction time window, position accuracy and processing time using Weka. Results show that the Alternating Model Tree (AMT) technique can predict the next position with an error of less than 3.2 centimeters, increasing up to 1 meter when predicting the next 5 positions with a period of 1 second between consecutive positions. In this case, a prediction time window of 5 s is processed within 1.25 milliseconds. AMT resulted as the lowest complex and most accurate algorithm in a multiple-step prediction position. © 2021 IEEE.

Cooperative, connected and automated mobility (CCAM) across Europe requires harmonized solutions to support cross-border seamless operation. The possibility of providing CCAM services across European countries has an enormous innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of real-time services pose technical challenges which 5G technologies aim to solve. The situation is particularly challenging given the multi-country, multi-operator, multi-telco-vendor, multi-car-manufacturer and cross-network-generation scenario of any cross-border scenario. Motivated by this, the 5GCroCo project, with a total budget of 17 million Euro and partially funded by the European Commission, aims at validating 5G technologies in the Metz-Merzig-Luxembourg cross-border 5G corridor considering the borders between France, Germany and Luxembourg. The activities of 5GCroCo are organized around three use cases: (1) Tele-operated Driving, (2) high-definition map generation and distribution for automated vehicles and (3) Anticipated Cooperative Collision Avoidance (ACCA). The results of the project help contribute to a true European transnational CCAM. This paper describes the overall objectives of the project, motivated by the discussed challenges of cross-border operation, the use cases along with their requirements, the technical 5G features that will be validated and provides a description of the planned trials within 5GCroCo together with some initial results.

This demo presents the instantiation of a high level architecture proposed by INSPIRE-5Gplus to manage secured End-to-End (E2E) Network Slices. Network Slices are associated with Security Service Level Agreement (SSLA) to enhance the security on the virtual deployed resources, thus securing the created E2E Secure Network Slices. The proposed secured network slicing architecture is validated against a vehicular scenario, based on Anticipated Cooperative Collision Avoidance use case. In this scenario, we propose to detect false vehicular messages through a novel SSLA based on an Intrusion Detection System. The demo provides measurement of significant metrics such as mean time to detect, mean time to contain, and transaction speed.

Cross-border scenarios are of extreme importance in current research work on 5G networks for connected vehicles. Network services and applications for connected vehicles, which are in specific cases expected to run on Mobile Edge Computing (MEC) infrastructure, might experience problems through country borders due to inter-domain. Given that cross-border scenarios typically imply a change of network operator, deployed MEC services need to work in such environments and, where applicable, different entities need to synchronize their input/output vehicular messages and work seamlessly in such a multi-operator context. One of most significant MEC services is vehicular message brokering. It consists on the controlled publishing and notification mechanisms to create awareness to all subscribed vehicles concerning their position as well as other significant events that may arise, such as hazardous events. This paper presents an architecture and method for vehicular message exchange, based on current Intelligent Transport Systems (ITS) standards, and proposes a novel hierarchical message brokering approach with the purpose of solving cross-domain scenarios, which can be applied not only in the aforementioned cross-border case but also in other scenarios where there is no single domain (i.e., with multiple vendors). Message Queuing Telemetry Transport (MQTT) servers are used in a hierarchical approach (locating a parent MQTT broker in a public cloud) in order to demonstrate the feasibility of using them for cross-border scenarios. Latency results are obtained in order to evaluate the performance penalty of the proposed solution.

The reliable acquisition of monitoring information is critical for several industrial use cases relying on wireless sensor network deployments. However, missing sensor measurements are typical in industrial systems empowered by cellular connectivity due to the stochastic nature of the wireless channel. In this paper, we propose a sensor data reconstruction scheme that exploits the hidden data dynamics to accurately estimate the missing measurements. Based on an analytical framework for the network model and a closed-form expression for the outage probability, the impact on the reconstruction error performance is thoroughly explored. Considering a dataset with high spatiotemporal correlation in the sensor observations, our proposed scheme is shown to outperform two baseline data recovery methods in terms of reconstruction error for various network configurations. In addition, despite the presence of imperfect cellular connectivity, our proposed scheme exhibits high event-detection accuracy.

Cooperative, connected and automated mobility(CCAM) services along different countries require cross-bordersolutions to support seamless delivery of services in a multi-operator, multi-telco-vendor, and multi-car-manufacturer sce-nario. The H2020 5GCroCo project will trial 5G technologies inthe European cross-border corridor along France, Germany andLuxembourg, as well as in five small-scale trial sites. 5GCroCoanalyses three cross-border use cases: tele-operated driving, high-definition map generation and distribution for autonomous vehi-cles, and anticipated cooperative collision avoidance (ACCA). Thispaper presents the infrastructure, control architecture, backendsoftware, and end-to-end service orchestration of the cross-borderACCA use case deployed in the Barcelona small-scale trial site., Grant numbers : AURORAS - Autonomic and disaggregated optical networks leveraging edge computing and photonic technologies (RTI2018-099178-B-I00).

Future 5G systems have set a goal to support mission-critical Vehicle-to-Everything (V2X) communications and they contribute to an important step towards connected and automated driving. To achieve this goal, the communication technologies should be designed based on a solid understanding of the new V2X applications and the related requirements and challenges. In this regard, we provide a description of the main V2X application categories and their representative use cases selected based on an analysis of the future needs of cooperative and automated driving. We also present a methodology on how to derive the network related requirements from the automotive specific requirements. The methodology can be used to analyze the key requirements of both existing and future V2X use cases.

Massive machine-type communication (mMTC) is expected to revolutionize the fifth-generation (5G) and beyond-5G systems by enabling connectivity for a high number of low-rate low-power devices with sporadic activity patterns. To realize the full potential of mMTC, radical enhancements are required for the radio access design and the architecture of current cellular systems. In this paper, we discuss the mMTC peculiarities in the context of emerging energy and automotive use cases. We identify key mMTC challenges that hinder efficient and scalable connectivity in the smart grid and in vehicular communication. Representative technical enablers are then proposed aiming to tackle the massive connectivity limitations in various scenarios. The performance assessment of the presented approaches reveals the superior performance compared to the benchmark schemes while useful insights can be drawn for the design principles of future mMTC protocols. Finally, we discuss some key technology trends relevant to mMTC that are expected to provide a roadmap for the design of novel solutions to evolve Dost-5G connectivity.

The ubiquitous Vehicle-to-Everything (V2X) connectivity enables successful deployments of emerging vehicular services around the world. However, geographical cross-border scenarios are challenging for vehicular services deployments over heterogeneous infrastructure and at the same time vehicles to maintain seamless service connectivity across borders. In this paper, we present the development and validation of an experimental vehicle On-Board Unit (OBU) for the execution of Anticipated Cooperative Collision Avoidance (ACCA) services in cross-border scenarios. The OBU flexibly supports the integration of different V2X protocols to communicate with heterogeneous cloud-based services offered by different Original Equipment Manufacturers (OEMs) within the ACCA service infrastructure.

©2017 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. In this paper, we consider a wireless machine-to-machine network composed of end-devices with energy harvesters that periodically transmit data to a gateway. While energy harvesting allows for perpetual operation, the uncertain amount of harvested energy may not guarantee fully continuous operation due to temporary energy shortages. This fact needs to be addressed at the medium access control layer. We thus investigate the performance of an energy harvesting-aware contention tree-based access (EH-CTA) protocol, which uses a tree-splitting algorithm to resolve collisions and takes energy availability into account. We derive a theoretical model to compute the probability of delivery and the time efficiency. In addition, we conduct a performance comparison of EH-CTA using an EH-aware dynamic frame slotted-ALOHA (EH-DFSA) as a benchmark. We determine the parameters that maximize performance and analyze how it is influenced by the amount of harvested energy and the number of end-devices. Results reveal the superior performance of EH-CTA over EH-DFSA. While EH-DFSA requires an estimate of the number of contending end-devices per frame to adapt the frame length, EH-CTA uses short and fixed frame lengths, which enables scalability and facilitates synchronization as the network density increases.

The vision of cooperative, connected and automated mobility (CCAM) across Europe can only be realized when harmonized solutions that support cross-border traffic exist. The possibility of providing CCAM services along different countries when vehicles drive across various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of services along borders also poses interesting technical challenges. The situation is particularly innovative given the multi-country, multi-operator, multi-telco-vendor, and multi-car-manufacturer scenario of any cross-border layout. This paper introduces the challenges associated to a cross-border deployment of communication technologies through the analysis of three use cases: tele-operated driving, high-definition map generation and distribution for autonomous vehicles, and anticipated cooperative collision avoidance. Furthermore, a set of 5G solutions have been identified to ensure that CCAM services can be supported efficiently in cross-border scenarios. Faster handover of a data connection from one operator to another, generalized inter-mobile edge computing (MEC) coordination, and quality of service (QoS) prediction are some of the solutions that have been introduced to reduce the uncertainties of a real 5G cross-border deployment.

Even before 5G is rolled out, Mobile Edge Computing (MEC) can be considered as a key driver towards the deployment of vehicular use cases, which pose stringent latency and bandwidth requirements to the underlying Vehicle-to-Everything (V2X) communication infrastructure. In this paper, we present a MEC-enabled cooperative Collision AVoidance (CAV) service designed to anticipate the detection and localization of road hazards by extending vehicles’ perception range beyond the capabilities of their own sensors. The CAV service is a software application that runs on MEC servers allocated at the roadside and at Mobile Network Operators’ (MNO) infrastructures. The CAV service receives ETSI ITS-G5 standard-compliant messages transmitted by vehicles: periodic Cooperative Awareness Messages (CAM), which include the position, velocity and direction of the vehicle; and event-triggered Decentralized Environmental Notification Messages (DENM), which include the position of detected road hazards. The CAV service creates a distributed dynamic map using all the received information, and sends unicast messages to each vehicle with the relevant information within its collision risk area. We have implemented and validated the operation of the CAV service using vehicles’ On-Board Units (OBU) based on OpenC2X, an open-source experimental platform supporting the ETSI ITS-G5 standard.

This paper introduces an industrial cyber-physical system (CPS) based on the Internet of Things (IoT) that is designed to detect rare events based on machine learning. The framework follows the following three generic steps: (1) Large data acquisition / dissemination: A physical process is monitored by sensors that pre-process the (assumed large) collected data and send the processed information to an intelligent node (e.g., aggregator, central controller); (2) Big data fusion: The intelligent node uses machine learning techniques (e.g., data clustering, neural networks) to convert the received ("big") data to useful information to guide short-term operational decisions related to the physical process; (3) Big data analytics: The physical process together with the acquisition and fusion steps can be virtualized, building then a cyber-physical process, whose dynamic performance can be analyzed and optimized through visualization (if human intervention is available) or artificial intelligence (if the decisions are automatic) or a combination thereof. Our proposed general framework, which relies on an IoT network, aims at an ultra-reliable detection/prevention of rare events related to a pre-determined industrial physical process (modelled by a particular signal). The framework will be process- independent, however, our demonstrated solution will be designed case-by-case. This paper is an introduction to the solution to be developed by the FIREMAN consortium. Post-print / Final draft

The vision of cooperative, connected and automated mobility (CCAM) along Europe can only be realized when harmonized solutions that support cross-border traffic exist. The possibility of providing CCAM services along different countries when vehicles traverse various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of real-time services along borders also pose technical challenges which 5G technologies promise to solve. The situation is particularly challenging given the multi-country, multi-operator, multi-telco-vendor, multi-car-manufacturer, and cross-generation scenario of any cross-border layout. Motivated by this, the 5GCroCo project, with a total budget of 17 million Euro and partially funded by the European Commission, aims at validating 5G technologies in the Metz-Merzig-Luxembourg cross-border corridor, traversing the borders between France, Germany and Luxembourg. 5GCroCo validation will focus on three use cases: 1) tele-operated driving, 2) high definition map generation and distribution for automated vehicles, and 3) Anticipated Cooperative Collision Avoidance. The results will help reduce the uncertainties associated with eV2X communications across borders in Europe in preparation of commercial 5G deployment.

In this paper, we experimentally evaluate and compare the robustness against interference of the OQPSK-DSSS (Offset Quadrature Phase Shift Keying-Direct Sequence Spread Spectrum) and the SUN-OFDM (Smart Utility Network-Orthogonal Frequency Division Multiplexing) physical layers, as defined in the IEEE 802.15.4-2015 standard. The objective of this study is to provide a comprehensive analysis of the impact that different levels of interference produce on these modulations, in terms of the resulting PDR (Packet Delivery Ratio) and depending on the length of the packet being transmitted. The results show that the SUN-OFDM physical layer provides significant benefits compared to the ubiquitous OQPSK-DSSS in terms of interference robustness, regardless of the interference type and the packet length. Overall, this demonstrates the suitability of choosing the SUN-OFDM physical layer when deploying low-power wireless networks in industrial scenarios, especially taking into consideration the possibility of trading-off robustness and spectrum efficiency depending on the application requirements. View Full-Text

This paper focuses on capabilities enabled by 5G connectivity in the cooperative, connected and autonomous cars, and elaborates on two technical enablers. One of the technical enablers consists of a beamformed broadcast/multicast technology that builds on adaptive and robust beam management techniques at the air interface. The other proposed technical component aims to improve the end-to-end architectural design of 5G networks to enable efficient broadcast and multicast transmissions for vehicle-to-anything services. Finally, the key results of multicast and broadcast technical components are described and ongoing and future areas of work and research are detailed.

In Software Defined Networks (SDN) a Controller installs forwarding rules or queries the status of network devices through a separate control channel using the OpenFlow protocol. Such queries may ask for instantaneous metrics, like port status, packet error rate, or transmitted packets. In turn, the Controller uses these metrics, or context, to condition forwarding rules. As network conditions change over time, forwarding rules are set to expire if not used (or matched) during a configurable idle timeout. Consequently, they are erased from the flow table, forcing a query to the Controller every time a packet for which there is no forwarding rule arrives at the network device. This work presents experimental results showing the delay increase produced by timing out forwarding rules of periodic flows, such as the generated by sensors in IoT deployments. Furthermore, it proposes and experimentally evaluates a pro-active forwarding rule installation mechanism able to reduce such delay by 90%, easing the implementation of context-aware forwarding strategies for IoT.

The request for the provision of services relying on Machine to Machine (M2M) communications have increased a lot over the last years. This has led to the introduction of M2M communications also in the SatCom area. In this context, the design of ultra-low power terminals becomes indispensable. In this paper, a feasibility study for assessing the implementation of an innovative energy efficient technique for ultra-low power M2M SatCom terminals is proposed. By Ieveraging on the E-SSA (Enhanced Spread Spectrum ALOHA) protocol, the newly proposed technique jointly exploits the use of multiple Spreading Factors (SFs) for transmission together with a smart transmission manager which is able optimize the use of energy harvesting by dynamically deciding when and how to transmit data. The proposed solution has been tested in different SatCom scenarios, demonstrating its effectiveness in terms of overall throughput and energy consumption.

There are several use cases that claim the need for a connected car. Among them there is the need for connectivity between vehicles and information sources, or V2V and V2X exchanges for accident prevention. In order to cope with the need for novel applications running on top of an interconnected network, the concept of fog computing appears as a realistic solution for both intra-car and inter-car data processing and decision making. This paper describes the proposed architecture and experimental evaluation of an innovative proof-of-concept (PoC) for a connected car, modeled with YANG, which can be remotely controlled using SDN/NFV and fog computing technologies. As an example, the remote control of the car might be based on a service application running on a fog node, which can be located close to a road side unit (RSU). We also propose a fog architecture in order to enable cooperative perception between connected cars. Finally, the performance evaluation uses a RESTCONF server installed in a Raspberry Pi aboard of a small car. This server is responsible for the sensors and actuators of the car and allows for its remote control from a user terminal (e.g., a smartphone, tablet, or laptop) and through the fog node, running a control application as a service.

The realization of advanced electrical grid functionalities, e.g., phasor measurement unit (PMU) information acquisition in wide-area monitoring systems (WAMS), requires a scalable and reliable underlying communication technology. Cellular networks, e.g., LTE/LTE-A systems, appear as a promising option to facilitate the smart grid evolution. However, the effect of LTE communication constraints on power system state estimation (SE) has not been thoroughly addressed in the literature. In this paper, we investigate the impact of the LTE random access channel (RACH) reliability on the transmitted PMU measurements and, consequently, on the SE accuracy. In particular, we assess the SE performance based on the achieved reliability per PMU attained with i) increasing number of contending devices in the system, i.e., smart meters and PMUs, and ii) varying cell coverage range. Numerical results demonstrate that, under different network and traffic configurations, SE accuracy can be significantly affected by the RACH reliability levels. Useful insights can thus be drawn for a reliability-aware design of a power system state estimator in LTE-based WAMS.

The final publication is available at Springer via http://dx.doi.org/10.1007/s11036-015-0575-6 The 3GPP is working towards the definition of service requirements and technical solutions to provide support for energy-efficient Machine Type Communications (MTC) in the forthcoming generations of cellular networks. One of the envisioned solutions consists in applying group management policies to clusters of devices in order to reduce control signaling and improve upon energy efficiency, e.g., multicast Over-The-Air (OTA) firmware updates. In this paper, a Multi-Radio Cooperative Retransmission Scheme is proposed to efficiently carry out multicast transmissions in MTC networks, reducing both control signaling and improving energy-efficiency. The proposal can be executed in networks composed by devices equipped with multiple radio interfaces which enable them to connect to both a cellular access network, e.g., LTE, and a short-range MTC area network, e.g., Low-Power Wi-Fi or ZigBee, as foreseen by the MTC architecture defined by ETSI. The main idea is to carry out retransmissions over the M2M area network upon error in the main cellular link. This yields a reduction in both the traffic load over the cellular link and the energy consumption of the devices. Computer-based simulations with ns-3 have been conducted to analyze the performance of the proposed scheme in terms of energy consumption and assess its superior performance compared to non-cooperative retransmission schemes, thus validating its suitability for energy-constrained MTC applications.

The reliable support of event-driven massive machine-type communication (MTC) requires radical enhancements in the standard LTE random access channel (RACH) procedure to avoid performance degradation due to a high probability of collision in the preamble transmission. In this paper, we investigate the relation between the cell size and the number of preambles generated from a single or multiple root sequences and we study their impact on the achieved reliability. Based on an analytical expression of the RACH reliability per cell, we introduce an interference- and load-aware cell-planning mechanism that efficiently allocates the root sequences among multiple cells and regulates the traffic load to guarantee reliable support of MTC. In addition, we propose a realistic traffic model that accurately captures the event-driven nature of MTC traffic. Finally, a performance evaluation of a power distribution automation scenario with MTC-overload reveals the superior performance of our proposed mechanism in terms of RACH reliability against benchmarking network-deployment schemes.

In this paper, we propose device-to-device (D2D) communication over dedicated cellular resources, i.e., D2Doverlay mode, as a key enabling technology for reliable information exchange in power distribution grids. Motivated by the stringent requirements of substation automation traffic, we jointly address two fundamental issues: i) the seamless transition from cellular (i.e., communication via the base station) to D2Doverlay mode for smart grid entities upon detection of a surge of channel access attempts, and ii) the efficient orthogonal resource partition for cellular and D2D links. An analytical framework capturing the event-driven nature of substation automation traffic and both phases of uplink communication is introduced and the joint problem of mode selection and resource allocation (MSRA) is formulated as a sum-rate maximization problem. A dynamic heuristic MSRA mechanism is then proposed that adaptively allocates uplink resources for D2D links to prevent spectrum under-utilization and guarantees a minimum rate requirement for cellular users. The performance of our proposed scheme is evaluated through extensive simulations under different performance criteria and numerical results demonstrate the rate gains of a dynamic switch between D2D-overlay and conventional cellular mode for substation automation traffic., Grant numbers : This work has been funded by project CELLFIVE (TEC2014-60130-P).© 2017 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.

This paper evaluates the performance of a burst transmission mechanism using microsleep operation to support high energy efficiency in IEEE 802.11 Wireless Local Area Networks (WLANs). This mechanism is an implementation of the IEEE 802.11ac Transmission Opportunity Power Save Mode (TXOP PSM). A device using the TXOP PSM-based mechanism can switch to a low-power sleep state for the time that another device transmits a burst of data frames to a third one. This operation is called microsleep and its feasibility strongly depends on the time and energy consumption that a device incurs in the transitions from and to the sleep state. This paper accounts for the impact of these transitions in the derivation of an analytical model to calculate the energy efficiency of the TXOP PSM-based mechanism under network saturation. Results obtained show that the impact of the transition requirements on the feasibility of microsleep operation can be significant depending on the selected system parameters, although it can be reduced by using burst transmissions. When microsleep operation is feasible, the TXOP PSM-based mechanism can improve the energy efficiency of other legacy mechanisms by up to 424% under high traffic loads.

Smart and connected devices can improve industrial processes, and generate new and better services. While this premise is well understood within the ICT industry, there is a challenge in extending this knowledge to vertical industries. The potential of the Internet of Things lies in the interaction among industries working together toward value co-creation. Firms need to look beyond their internal business models and explore cooperative perspectives to define new business opportunities. In this article, we look into the relevance of vertical cooperation in the area of IoT and highlight the need to develop new value networks that leverage this cooperation and enable the creation of new business models. To lead our discussions, we use the examples of two major building blocks of smart cities: intelligent transport systems and health and well being services based on connected devices and solutions.

Power distribution networks are often widely distributed to accommodate electrical power feeds to dense cities while monitoring and control systems typically require extensive information exchange among numerous intelligent electronic devices. Using the existing network infrastructure, cellular technology appears as a key enabler for the support of large-scale metering deployments and wide-area monitoring systems. In this paper, we evaluate the performance of the contention-based random-access mechanism of LTE networks for real-time monitoring and metering applications. In particular, the impact of smart grid traffic is investigated in terms of access delay and outage probability under different network configurations and traffic characteristics. Simulations of realistic network-overload scenarios demonstrate that the random-access channel of LTE/LTE-A is prone to congestion when a high number of smart grid devices attempt for network access, while the bursty nature of monitoring traffic results in even higher performance degradation., Grant numbers : This work has been funded by projects CellFive (TEC2014-60130-P) and the Catalan Government (2014-SGR-1551).

This paper provides a view to Peer-to-Peer (P2P) approach for smart grid operation adopted in P2P-SmarTest project. It provides an overview on solutions proposed for distributed P2P energy trading, P2P grid control and wireless communication enabling the proposed P2P operation. The paper proposes some business models that can be adopted in a P2P setting. We also outline the barriers and enablers against and for adopting local or regional P2P based electricity operations.

Energy efficiency is one of the main challenges of Machine-to-Machine (M2M) networks, since they aim at connecting devices with limited access to power sources and operate without human intervention. It has been shown in the past that the use of short-range cooperation between wireless devices equipped with multiple Radio Access Technologies (RATs) can achieve energy savings and extend the lifetime of cellular wireless networks. Devices with cellular connectivity can become temporary gateways to provide energy-constrained devices within the short-range cluster with access to the long range cellular infrastructure. To this end, the devices need to discover their neighbours using their short-range radio interface to identify and select potential gateway candidates. Existing neighbour discovery mechanisms perform poorly in terms of delay and energy consumption to maintain, continuously at each device, complete neighbourhood information, and thus may not be suitable for energy-constrained M2M networks. In this paper, we focus on distributed neighbour discovery mechanisms that are initiated dynamically and spontaneously by a single device to discover only its single-hop neighbours. We formulate accurate delay and energy models of three discovery mechanisms based on frame slotted-ALOHA and contention tree algorithms, and compare their performance in terms of delay and energy consumption. (C) 2013 Elsevier B.V. All rights reserved.

Recent standardization efforts on low-power wireless communication technologies, including time-slotted channel hopping (TSCH) and DASH7 Alliance Mode (D7AM), are starting to change industrial sensing applications, enabling networks to scale up to thousands of nodes whilst achieving high reliability. Past technologies, such as ZigBee, rooted in IEEE 802.15.4, and ISO 18000-7, rooted in frame-slotted ALOHA (FSA), are based on contention medium access control (MAC) layers and have very poor performance in dense networks, thus preventing the Internet of Things (IoT) paradigm from really taking off. Industrial sensing applications, such as those being deployed in oil refineries, have stringent requirements on data reliability and are being built using new standards. Despite the benefits of these new technologies, industrial shifts are not happening due to the enormous technology development and adoption costs and the fact that new standards are not well-known and completely understood. In this article, we provide a deep analysis of TSCH and D7AM, outlining operational and implementation details with the aim of facilitating the adoption of these technologies to sensor application developers. info:eu-repo/semantics/publishedVersion