OPEN CALL 2

Call objectives
Building and operating a mobile broadband (MBB) testbed is the key goal of the MONROE project. Such a testbed, however, cannot be built without the feedback of the experimenters who will be the main users of it. Therefore, external users are in the core of the MONROE project. The experimenters selected through the second open call will be allowed to run active/passive measurements as well as propose protocol experiments, which require active traffic generation and SW support from the MONROE consortium. They can further propose SW extensions to the platform as well as HW extensions to the infrastructure.

Call information
Project full name: MONROE–Measuring Mobile Broadband Networks in Europe
Project number: 644399
Call identifier: MONROE-OC2
Call name: Second MONROE Open Call for Experiments and Extensions
Total budget: 1,500,000 Euros
Number of proposals to be funded: up to 15
Maximum funding per proposal: 100,000 Euros
Number of partners per proposal: The target number of participants per proposal is maximum 2.
Type of participants: The profile of participants is academics, industry or SMEs active in research and/or development of mobile broadband technologies, protocols and/or applications. The rules of participation are the same as for any H2020 proposal.
Duration of the experiment: The maximum allowed duration of each experiment is 12 Months.
Language of the proposal: English
Proposal submission: through the EasyChair conference system: MONROE-OP2
Call deadline: Friday, December 2, 2016 at 17:00h CET (Brussels time)
Notification of acceptance: Wednesday, February 1, 2017
Starting date: March, 2017

Proposal Template: MONROE Second Open Call applicants must use this Proposal Template (in Word format)

Detailed Call InformationCall Announcement

Contact: info@monroe-project.eu

 

UPDATE: OPEN CALL RESULTS

We have funded the following 15 proposal from a total number of 52 proposals received during the second open call:

  • Characterizing Carrier Grade NATs in Mobile Broadband Networks: CGNWatcher, Scientific Excellence, Universidad Carlos III de Madrid, Spain.

Deploying Carrier Grade NATs (CGNs) enables Mobile Broadband Network operators to provide Internet access services to a very large number of customers with a limited amount of public IP addresses. However, CGNs impose a number of functional and potentially performance penalties. In the CGNwatcher project we will develop a measuring tool that executes a number of active tests to fully characterize CGN deployments in Mobile Broadband Networks. The CGNwatcher tool will systematically test for over 40 behavioural requirements for NATs defined by the Internet Engineering Task Force (IETF) and also for multiple CGN performance metrics. The metrics will be designed to work in cascaded-NAT scenarios, isolating the characteristics of the different NATs along the path whenever is possible. As part of the project, we will deploy CGNwatcher in MONROE and perform large measurement campaigns to characterize the real CGN deployments of the ISPs serving the MONROE nodes. Additionally, we will deploy CGNwatcher in a crowdsourcing platform, in order to complement the data set obtained through MONROE and extract some conclusions of how representative is MONROE of other regions of the Internet in terms of CGN deployments. The measurement results obtained through CGNwatcher will be relevant to application and protocol developers to inform their design about how to overcome the limitations imposed by CGNs. The information retrieved though CGNwatcher will be also useful for experimenters using MONROE, as CGNs may have an important impact in the feasibility of experiments and can potentially bias the results if not accounted for. As part of the project, we will disseminate the results through academic publications and demonstrations and we will promote the adoption of the proposed metrics in the IETF in order to obtain a standardized set of metrics for CGN characterisation.

  • Network Neutrality in Mobile Broadband: NeutMon, University of Pisa, Italy.

EU-wide rules concerning net neutrality are one of the major achievements towards the Digital Single Market. According to these rules, blocking, throttling, and discrimination of traffic by Internet Service Providers (ISPs) is not allowed. All traffic has to be treated equally, and no form of traffic prioritization can be enforced (with few exceptions: preserving the integrity of the network, managing temporary congestions, and compliance with legal obligations). So far, research on net neutrality focused on the wired part of the Internet. However, in recent years, smartphones and tablets have become the preferred choice for accessing a large number of networked services and applications, from social networks to video streaming. The NeutMon project is aimed at studying net neutrality in a mobile broadband context. The main goals of the project are: i) collecting a set of measurements related to net neutrality in mobile broadband using the MONROE infrastructure; ii) developing methods for analysing such data and thus inferring the neutrality level of mobile broadband operators. Collected data will include the most important network metrics (e.g. bandwidth, delay) with traffic belonging to different classes (e.g. file sharing, HTTP). Also the path at both router and autonomous system level will be collected and analysed. As far as the analysis of data is concerned, it is important to note that currently available techniques may be not well suited to operate in a scenario with mobile broadband access. As known, wireless networks are more prone to large fluctuations than wired ones: performance levels may vary significantly in a short interval as a consequence of interferences, mobility, and environmental factors. Effective techniques for the evaluation of neutrality in these settings have to incorporate these concepts from the beginning and must be able to distinguish deliberate traffic engineering from the peculiar variability of the considered environment.

  • Reconstruction of operator policies in MBB networks for improved user experience: RECON, Eötvös Loránd University, Hungary.

The complex Internet infrastructure plays a crucial role in determining end-to-end experiences of the users. The current Internet connects around 2 billion users through a global communication infrastructure that consists of thousands of service providers of different business types. A significant fraction of the users connect to the Internet through mobile broadband networks; using their notebooks, tablets and smart-phones. With the advent of 3G and 4G, a huge number of mobile applications have emerged with a wide range of requirements against the networking infrastructure. Ensuring high Quality of Experience has utmost importance for application developers. However, it is also well-known that network operators apply various policies in different layers of networking, affecting end-to-end traffic characteristics and eventually the observed Quality of Experience. Reconstructing and understanding these policies may help developers to make their applications compliant with the network and thus improve the provided QoE for end users. Such information can also be important for decision makers and supervisory bodies to get feedback about applied traffic management policies and practices, as well as the level of network neutrality to check their compliance with local regulations. In this project, we aim at developing a methodology and toolboxes (as extensions) for MBB networks to reconstruct operator policies applied in Network, Transport and Application Layers, following a way of reverse engineering. In network layer, we will mainly investigate intra and inter-domain routing policies with special focus on the stability of network paths and on the topology changes of mobile end-hosts. In transport layer, UDP and TCP functionality (e.g., UDT, MPTCP, ECN, TCP Fast Open) of different network paths will be tested through active measurements. The system allows experimenters to measure wide diversity of paths and can help determine whether a proposed solution has the required support or functionality from the MBB ecosystem. In application layer, operators often apply traffic differentiation—giving better (or worse) performance to certain classes of Internet traffic. This also provides vital information for the net-neutrality debate.

  • Experimental validation of REM-based machine learning algorithms for SON using MONROE nodes: MONROE-SON, RED Technologies SAS, France and Instituto Politécnico de Castelo Branco, Portugal.

SON (Self-Organizing Network) technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of equipment and troubleshooting during operation. This can significantly reduce the cost of the mobile operator’s services. Mobile operators are keen to capitalize on SON to minimize rollout delays and operational expenditures associated with their ongoing LTE deployments. SON ecosystem is increasingly witnessing convergence with other technological trends such as LSA (Licensed Shared Access), a technology that enable mobile operators to temporarily increase the available bandwidth by using portions of the radio spectrum previously reserved for other uses. Learning and prediction of network behavior are key enablers towards the implementation of the SON paradigm. In this experiment we will use advanced machine learning algorithms to predict network congestion for a specific cell\time of the day by leveraging on priori measurements from MONROE nodes, and then activate the LSA mechanism to increase LTE capacity based on a demand-driven approach. The experiment will start by using measurements from MONROE nodes in Oslo and Madrid for selecting and tuning a machine learning algorithm able to predict cell congestion. After that, two additional MONROE nodes will be deployed in a central district in Paris, adding an extra European capital to the MONROE federation. Radio Environment Maps with a real network deployment in Paris will be use to validate the automatic activation of LSA bands in case of capacity outage. The machine learning API developed in this project will be open source and available for future MONROE use, as a software extension, able to extract useful insights from the huge amount of data generated by MONROE experiments. The outcome of this project will have a strong impact on the LSA standardization process in ETSI RRS (Reconfigurable Radio Systems) where RED Technologies is an active contributor.

  • Multi-homing with Ephemeral Clouds on the Move: MEC, University of Macedonia, Greece.

A main research challenge in 5G Networks is an efficient synergy of the mobile network edge with nearby cloud deployments that achieves ultra-low latency and high bandwidth, while enabling innovative applications. However, in high-mobility environments is not easy to deploy traditional clouds nearby. Furthermore, such technologies use full-scale operating systems with unneeded most of their codebase (e.g., a web server may require 50MB but reserve a 20GB virtual machine). We suggest that Unikernel Virtual Machines (UVMs) fit this context very well, since they have a very small size and rapid boot-up times, i.e., can be responsive to dynamic changes in the network conditions. The MONROE project offers unique experimentation capabilities utilizing both highly-mobile environments and real operational Mobile Broadband (MBB) networks. In MEC, we complement the MONROE platform with lightweight cloud capabilities residing in the mobile nodes. We plan to experiment with: (i) Intelligent orchestrated cloud resources that improve mobile communication and adapt to the conditions of the MBB networks, (ii) Multi-homing capabilities that consider resource offloading to the nearby cloud resources, and (iii) Novel forecasting mechanisms for the dynamic network conditions. The above will be demonstrated with three novel scenarios utilizing the MONROE platform and our SWN test-bed (i.e., Web Load Balancing, Ephemeral VMs Orchestration and Internet of Things).

The MEC project extends the MONROE platform with the following aspects:

  • The Lightweight Edge Cloud and the Multi-Homing Decision Engine realizing a Unikernel- based cloud and handling multi-homing decisions, respectively.
  • The Orchestrator supporting decision engines for multi-homing strategies and UVMs orchestration along with a Prediction Engine forecasting the evolution of the network conditions.
  • A number of showcase components, such as a Web Load-Balancing Controller, a UVM Repository and an IoT controller.
  • Visualization tools showing both the wireless/mobile and lightweight cloud contexts, as well as performance measurements.

 

  • Programmable and Robust Smart Grid Data and Control: RASnet, DAI-Labor, TU Berlin, Germany.

The main motivation of our project “Programmable and Robust Smart Grid Data and Control” (RASnet) is driven by our current systems research of ICT for Low-Voltage grids and its open question of how to properly make use of all available data-links between the electrical grid and its operator. To ensure a robust operation of a low-voltage grid with significant proportion of renewable energy sources within the required power-quality specifications, operators need to be able to observe the dynamic power quality state and gain control of its generation sources, both in the time domain of milliseconds. The figure below illustrates the clear mismatch between locations with renewable energy generation and available broadband ICT.

With our proposed RASnet project we aim to analyze the potential integration of current 3G/4G networks in a productive broadband network of a rural Wireless ISP (WISP), Evernet, with significant renewable energies. We want to extend our current research infrastructure placed in the WISP network in such a way that the current set of uplinks (dsl, vdsl, satellite) is extended to consider and integrate 3G/4G network links as additional uplink connections to increase the grid operator’s main goal of a robustness monitoring and control channel to his grid.

The goals of the RASnet research proposal are:

  • Integration of 5 Monroe nodes into the productive WISP infrastructure from Evernet, which serves ~130 households across 5 villages based on Linux OpenWrt-WiFi-routers, including 13 Photovoltaic-systems and 2 Windparks.
  • Performing long-term measurement trials to analyse the performance of rural 3G and 4G networks in order to consider them as alternative uplinks to monitor and control the electrical grid state with low latency via a robust feedback channel
  • Analysing Monroe data-traces to generate proper input parameters for our SDN controller about available latency and data-rate in order to increase overall goal of providing a programmable path for ultra-robust data and control access to the Smart Grid operator.
  • Extracting and disseminating meaningful and generalized insights for 5G research community on attaining ultra-reliable and low-latency communications using SDN-based aggregation of heterogeneous access technologies.

 

  • Towards, end-to.end Multipath TCP, Université catholique de Louvain, Belgium.

Multipath TCP, defined in [RFC6824], is one of the major protocols that can really exploit the path diversity that exists in today’s mobile and broadband networks. During the last years, a growing number of use cases have been developed above this new protocol [IETFJournal]. Until now, Multipath TCP has mainly been used on proxies applications that are unaware of the new capabilities brought by Multipath TCP, with one notable exception. We expect that in the coming years applications will be tuned to interact directly with Multipath TCP. In this project, our objective is to prepare this evolution by enhancing test tools to correctly interact with Multipath TCP through the enhanced socket API and by extensively testing it in the MONROE testbed. More precisely, we aim at measuring and possibly improving the Multipath TCP implementation in the Linux kernel for two use cases that are important for mobile nodes:

  • Short request/responses such as those corresponding to applications using voice recognition
  • Audio and Video streaming applications

We will then exploit the lessons learned from these measurements to improve the enhanced API for Multipath TCP and contribute to its standardization within the IETF.

  • Smart City Security Monitoring Platform: Cloud Eyes, Institute of Bioorganic Chemistry of the Polish Academy of Sciences, Poznań Supercomputing and Networking Center (PSNC), and TechInnowacje sp. z o.o., Poland.

Cloud Eyes is a Smart City Security Monitoring Platform enabling real-time video surveillance using WiFi and mobile broadband (MBB) networks, with dynamic adaption of transmission parameters. It is designed to provide monitoring from buses, trams, trains, robots and places where connection using a wired network is not possible. Before going to the market, we need to perform validation of the platform in a real-world MBB environment. That is why we will use the MONROE testbed to deploy Cloud Eyes in a distributed system of mobile and stationary nodes connected via various wireless networks, and to measure the key network metrics and the corresponding video quality. Our goal is to determine the correlation between Quality of Service and Quality of Experience, define encoding and transmission profiles for various network conditions and enhance our smart adaptive algorithms, making Cloud Eyes a market-ready solution running on heterogeneous wireless networks. Our product is beyond the state-of-the-art of currently available monitoring solutions as it allows for continuous, real-time surveillance, utilising both WiFi and MBB networks, whereas our competitors’ solutions rely only on WiFi and are not capable of continuous, real-time monitoring. Our product takes advantage of the full capacity of MBB and overcomes problems of varying transmission quality by using dynamic adaptation. PSNC will organise and take part in dissemination and demonstration events to attract customers such as transportation companies, city authorities and law enforcement institutions. As PSNC specializes in network technologies and has been using pan-European testbeds in many projects, it can provide valuable feedback about the MONROE testbed to the consortium. PSNC envisions to negotiate with the consortium the possibilities of using the testbed to complement other laboratory facilities that we currently offer to companies in the region. Such commercial offering can help to ensure sustainability of the testbed after the project ends.

  • Optimization of QoE of Mobile Broadband Services through Machine Learning: OPTIMAL, Modio Computing SP, Greece & Paris Descartes University (PDU), France.

Resource allocation within a mobile broadband (MBB) environment remains a challenging topic as it faces highly dynamic user demand and volatile network conditions while it must ensure an acceptable Quality of Experience (QoE) in the provided services without over-provisioning network resources. To solve this problem, we propose the implementation and experimental validation of a novel approach to intelligent resource allocation within MBB environments. Our approach enables the dynamic adaptation of resources to users’ demands effectively preventing possible degradation of the QoE of the service before this manifests to the client-side and becomes noticeable by the end users. In the proposed experiment, we will validate our approach using video streaming as the use case, which is one of the most popular and resource-demanding MBB services. Our methodology composes of 4 stages:

  1. collection of metrics from the MONROE testbed and calculation of KPIs,
  2. correlation of the KPIs to a measurable form of QoE,
  3. prediction of future KPIs based on existing KPIs and the correlation model and
  4. the generation of resource allocation actions both in the node (client-side) and in the server to improve the QoE.

Our methodology includes state-of-the- art techniques for large-scale data correlation and employs machine-learning algorithms to forecast the degradation of QoE and the generation of suitable provisioning actions to prevent this degradation. Our approach shares some common aspects with autoscaling techniques employed by cloud providers to optimize the resource allocation. Furthermore resource autoscaling using computational intelligence is currently an active research topic in 5G infrastructures. We believe that our experiment will contribute to both MBB and 5G research, thus promoting the sustainability of the MONROE testbed.

  • Fast and Lightweight Capacity Benchmarking of Mobila Broadband Networks in MONROE: FaLiCaB, TU WIEN / Institute of Telecommunications (TUW), A1 Telekom Austria AG (A1), Austria.

The capacity of the connecting network links mainly defines the quality of service for an end user. There are several parameters affecting network communication links, an important one being the available end‐to‐end bandwidth. Several different approaches for measuring the network link capacity exist in industry, standardization and the scientific community. However, their implementations are resource demanding and require a long measurement time. Both properties do not deal well with the challenges found in mobile broadband networks, especially when targeting a distributed measurement system. Bandwidth measurements in cellular wireless networks, with traffic reactive nature, nomadic end users, tariff data rate limitations and highly dynamic shared resources, is a challenging task. The goal of FaLiCaB is to integrate a packet dispersion based solution extended by parameter estimation into the MONROE platform. The new method needs validation in a nomadic setup. The MONROE platform offers a unique opportunity for the FaLiCaB consortium. The project will implement an estimation method for link capacity with packet dispersion into the MONROE system. The validation will use static MONROE nodes to allow for a fair comparison between new and existing methodologies. The new module will run in a large measurement campaign on mobile MONROE nodes validating the approach for moving end users. Finally, the project will use the MONROE metadata to understand the impact of events on the results from different layers, allowing an augmentation of the capacity estimator via passively monitored parameters. The module will be cross‐validated with nodes locally positioned in Austria and equipped with unlimited SIM cards from A1. The MONROE project will gain the major mobile operator in another European country with FaLiCaB. The TUW will provide its performance test setup. The MONROE project will benefit from a new module for volume lightweight and fast bandwidth estimation suitable for crowdsourced measurement systems.

  • Network Self-Optimization based on End-To-End measurements: eSON, Universidad de Málaga (UMA), Spain.

eSON proposes an experiment that studies the effect of Self-Organizing Network (SON) functions on End-To-End (E2E) performance of Mobile Broadband (MBB) terminals. SON functions automatically adjust the configuration of the Radio Access Network (RAN) and the core of cellular networks based on network measurements and Artificial Intelligence (AI) algorithms, saving costs and reducing downtimes. The proposed experiment will take E2E measurements in the MONROE nodes in two scenarios: a baseline where no SON algorithms are present in the cellular network, and an enhanced network where self-optimization algorithms will be applied. The MONROE platform will allow to perform experiments in real conditions. However, in order to carry out the self-optimization experiments, access to the Operation, Administration & Management (OAM) of the cellular network is required in order to change network configuration parameters. To cope with this requirement, eSON also proposes a HW extension to the MONROE platform which adds an experimental LTE network to the platform. This extension will permit the execution of the current proposal, and it will also significantly increase the scope of the possible MONROE experiments from terminal-end only to full end-to-end. With this addition, experimenters can measure and control the behavior of the RAN network, core and even remote services. The proposed addition is an LTE small-cell network with 12 picocells and 14 terminals, which also includes a co-located WiFi network. The installation includes the core network and management HW. On the software side, a management platform is installed in the network, with plans to integrate it into the MONROE platform. eSON complements the capabilities of the MONROE platform of performing experiments in real conditions with new capabilities in controlled scenarios. In addition, it will allow to study not only the end nodes, but also the effects of the RAN and core networks in the E2E performance.

  • Dynamic Pricing in HetNets: DAPHNE, University of Thessaly (UTH), Greece.

Contemporary mobile devices are equipped with multiple radio access capabilities. In parallel, mobile network providers densify their deployments in urban areas, aiming to provide higher network capacity, improved QoS and enhanced end-user perceived QoE. In such environments, the role of Mobile Broadband Networks (2G/3G/4G and beyond) and WiFi technologies (IEEE 802.11 a/g/n/ac) is dominant. Nevertheless, in such highly heterogeneous environments several questions may arise, regarding which technology or combination of technologies should the end-user use and when it should handoff to another available in-range technology. Moreover, such decisions may widely affect the performance of other users operating inside the same cell. Towards addressing these questions, we propose our experiment for DynAmic Pricing in HetNEts (DAPHNE). DAPHNE will develop a framework based on pricing methods (Flat Rate Pricing, Paris Metro Pricing with dynamic pricing, Paris Metro Pricing with dynamic pricing and multiple traffic classes per UE) that will dynamically assign prices for using each network. Given the remaining cells capacities and the end-user demands, DAPHNE will appropriately let all the end clients to be distributed among all the technologies that are available inside the Heterogeneous Network (HetNet) environment. DAPHNE will be evaluated over the MONROE facilities, taking advantage of the rich MBB experimental ecosystem that they provide, as a means to experimentally derive a framework that can be directly applied to future 5G networks.

  • Traffic and Data Offloading in Mobile Networks: TTOff, University Politehnica of Bucharest, Romania.

The growing consumption of data by mobile devices has put a strain on mobile networks. With the increasing number of Wi-Fi-capable nodes, traffic offloading between mobile broadband (MBB) and Wi-Fi has been gaining steady traction. End-users offload traffic for cost control and better throughput, while operators do it for congestion and traffic load control. However, offloading should provide users with a seamless experience while they use applications on their devices, which should make smart decisions about keeping data flows on preferred networks, while optimizing resources to improve user experience. Many solutions send all traffic to Wi-Fi when available, few looking for other metrics such as mobility-related, and quality of service (QoS) and quality of experience (QoE) parameters. Our goal is to develop mechanisms to determine the best possible use of available networks, by intelligently switching traffic between MBB and Wi-Fi (over access points), or opportunistically through devices in proximity. In this context, to carry out experiments on a large-scale measurement platform is a very attractive opportunity to mitigate technological risks associated with traffic offloading. In the experiment, we will measure and evaluate key performance indicators (KPIs) of providing offloading through MONROE. We aim to implement a software extension to MONROE, to understand the impact of mobility (derived from context information collected by mobile nodes, ranging from throughput to location or contact history) over the offloading decision, and analyze the impact of offloading over real-life situations, by observing traffic patterns, broadband and Wi-Fi network behavior (in terms of throughput, congestion, etc.). The results will help us propose and implement solutions for offloading, that will be evaluated over the MONROE testbed, with results proving valuable to network operators and application developers. Furthermore, the integration of MONROE and TTOff can contribute to sustaining the MONROE platform by engaging future experiments.

  • Characterising Mobile Content Networks in the Wild: CaMCoW, Queen Mary University of London (QMUL), UK.

Mobile broadband (MBB) networks have seen dramatic increases in both capacity and uptake. Characterising user-facing network performance, however, can be challenging because it depends on the particular services being accessed by the subscriber. For example, a user accessing YouTube will receive different performance based on the provisioning and network distance between the access network and the nearest YouTube server. This is not simple – it is a product of both the MBB network and YouTube’s interconnection and capacity planning strategies. Little substantive work exists on exploring the behaviour of user-facing services in MBB networks. This deficiency is particularly critical in MBB networks due to their relative dynamism, and less developed (IXP) peering models (compared to wireline infrastructures). CaMCoW will address this gap. It will exploit the MONROE testbed to measure the ways in which popular content services (e.g., Netflix, Google) have approached deploying and interconnecting their infrastructures for access by MBB subscribers. It will measure the deployment of these services and how MBB users are given access to them. We will correlate these deployment strategies with the Quality of Experience users can expect, to formulate and inform best practice. We will integrate data generated via CaMCoW with other (wireline) measurement studies we are performing in this area to gain a comprehensive view of wired and wireless behaviour. Through this, CaMCoW will (1) Explain how content services are currently provisioned and interconnected for access by MBB networks; (2) Provide data and analysis to describe the performance of each services and how it relates to their given deployment strategies; (3) Offer recommendations for improving user Quality of Experience when accessing these services from MBB networks; and (4) Generate detailed feedback for the MONROE consortium, e.g., bug fixing, improving accessibility for new users, streamlining measurement data collection, techniques for better automation of experiments.

  • Feasibility study of latency-critical connected vehicle applications in MONROE: FELICIA, SICS Swedish ICT, Sweden.

Next generation connected vehicles and cooperative intelligent transport systems (C-ITS) have great potential to make road traffic safer, more efficient, greener, and available to more people. However, these systems also place extensive demands on the mobile network infrastructure. The mobile networks need to handle me-critical applications combined with uploads of large data volumes from moving vehicles. We propose a measurement study to identify possibilities and limitations in the existing mobile networks for supporting C-ITS applications. We will also study the possible gain of using multiple accesses and multi-path transport in the end-points for these type of applications, separating me- critical and bulk data into different paths. The study will be done through measurement experiments where we emulate traffic representing a range of vehicular applications with different requirements on latency and capacity, and measure their performance. The traffic models are developed in dialogue with automotive industry representatives. The MONROE platform gives great possibilities for conducting these vehicular measurements and experiments in a controlled, repeatable and vendor- and operator-independent manner, and at large scale in heterogeneous environments. The platform also supports multi-path experiments and enables comparative studies between operators and between different locations that otherwise would be difficult to achieve. We see our proposed experiment as the first step in making the MONROE platform an important experimental platform for connected vehicle applications, and so of great interest for the automotive industry, telecom operators and researchers in this area. This will contribute to the sustainability of the MONROE platform.