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Resource Allocation for Network Slicing in Mobile Networks
Get PDFThis paper provides a survey of resource allocation for network slicing. We focus on two classes of existing solutions: ( ) reservation-based approaches, which allocate resources on a reservation basis, and ( ) share-based approaches, which allocate resources based on static overall shares associated to individual slices. We identify the requirements that a slice-based resource allocation mechanism should satisfy, and evaluate the performance of both approaches against these requirements. Our analysis reveals that reservation-based approaches provide a better level of isolation as well as stricter guarantees, by enabling tenants to explicitly reserve resources, but one must pay a price in terms of efficiency unless reservations can be updated very dynamically; in particular, efficiency falls below 50% when reservations are performed over long timescales. We provide further comparisons in terms of customizability, complexity, privacy and cost predictability, and discuss which approach might be more suitable depending on the network slices’ characteristics. We also describe the additional mechanisms required to implement the desired resource allocations while meeting the latency and reliability requirements of the different slice types, and outline some issues for future work.pu
Large Scale Collaborative Detection and Location of Threats in the Electromagnetic Space
Get PDFIn the 21st century, the security of the electromagnetic spectrum has tremendous strategic importance to society.
In particular, the wireless infrastructure that carries vital services such as 5G cellular networks, communication to aircraft and Global Navigation Satellite System is especially critical. This rapid change is even more impressive considering that in the 80s the only concern for spectrum management was mostly about radio/television broadcasting and military communications. The allocation of spectrum has become over the years more and more complex with different players and stakeholders that depend on largely of their correct operation. However, today, the cost of commodity radio technology prices is so low that access to it is no longer restricted to governments and network operators. It is now affordable to individuals, giving them the potential to become malicious intruders. More frequent and more sophisticated threats from such infiltrators could wreak havoc and are among the most serious challenges faced by society. Unauthorized
transmissions could threaten the operation of networks used by air traffic control systems, police, security and emergency services in populated areas. The SOCRATES (Large Scale Collaborative Detection and Location of Threats in the Electromagnetic Space, Grant G5461) project started in June 2018 and aims to deliver a security system to protect our electromagnetic environment and the services and users that depend upon it. SOCRATES will provide an accurate, autonomous, fast and secure system based on a novel and disruptive IoT (Internet of Things) architecture. By detecting and locating unusual RF signal and source activity it will identify intruders in the electromagnetic space, before a threat can become serious, learning about its physical layer features and its geographic location. By providing the capability to detect, identify and locate potential threats to electromagnetic infrastructure security, SOCRATES represents an important step in ensuring society's readiness to respond effectively to them. SOCRATES will shield economic and social structures from those who would harm them. In this contribution we present a summary of published results achieved in the first year of the project, how funds from SOCRATES have foster the collaboration between NATO countries Spain and Belgium and partner country Switzerland, including the activities led by Electrosense as partner country.TRUEpu
Experimenting with SRv6: a Tunneling Protocol supporting Network Slicing in 5G and beyond
Get PDFDOI: https://doi.org/10.1109/CAMAD50429.2020.9209260With network slicing, operators can acquire and manage virtual instances of a mobile network, tailored to a given service, in this way maximizing flexibility whileincreasing the overall resource utilization. However, the currently used tunnelling protocol, i.e., GTP, might not be the most appropriate choice for the envisioned scenarios, given its unawareness of the underlay network. In this paper, we analyse the use of an alternative tunnelling protocol to transport user data, namely, Segment Routing IPv6 (SRv6). More specifically, we discuss its qualitative advantages, present a prototype implementation, and carry out an experimental comparison vs. GTP, confirming that it constitutes a valid alternative as tunnelling protocol.TRUEpu
DeepCog: Optimizing Resource Provisioning in Network Slicing with AI-based Capacity Forecasting
Get PDFThe dynamic management of network resources is both a critical and challenging task in upcoming multi-tenant mobile networks, which requires allocating capacity to individual network slices so as to accommodate future time-varying service demands. Such an anticipatory resource configuration process must be driven by suitable predictors that take into account the monetary cost associated to overprovisioning or underprovisioning of networking capacity, computational power, memory, or storage. Legacy models that aim at forecasting traffic demands fail to capture these key economic aspects of network operation. To close this gap, we present DeepCog, a deep neural network architecture inspired by advances in image processing and trained via a dedicated loss function. Unlike traditional traffic volume predictors, DeepCog returns a cost-aware capacity forecast, which can be directly used by operators to take short- and long-term reallocation decisions that maximize their revenues. Extensive performance evaluations with real-world measurement data collected in a metropolitan-scale operational mobile network demonstrate the effectiveness of our proposed solution, which can reduce resource management costs by over 50% in practical case studies.pu
CoronaSurveys: Using Indirect Reporting to Estimate the Incidence of Epidemics
No full textThe world is suffering from a pandemic called COVID-19, caused by the SARS-CoV-2 virus. National governments have problems evaluating the reach of the epidemic, due to having limited resources and tests at their disposal. This problem is especially acute in low and middle-income countries (LMICs). Hence, any simple, cheap and flexible means of evaluating the incidence and evolution of the epidemic in a given country with a reasonable level of accuracy is useful. In this talk, I will present the CoronaSurveys project. CoronaSurveys uses a technique based on (anonymous) surveys in which participants report on the health status of their contacts. This indirect reporting technique, known in the literature as network scale-up method, preserves the privacy of the participants and their contacts, and collects information from a larger fraction of the population (as compared to individual surveys). The CoronaSurveys project has been collecting reports for the COVID-19 pandemic since March 2020. Results obtained by CoronaSurveys show the power and flexibility of the approach, suggesting that it could be an inexpensive and powerful tool to track the COVID-19 pandemic. This makes it especially interesting and useful for LMICs.FALSEpu
AI-Based Autonomous Control, Management, and Orchestration in 5G: From Standards to Algorithms
Get PDFWhile the application of artificial intelligence (Ai) to 5G networks has raised strong interest, standard solutions to bring Ai into 5G systems are still in their infancy and have a long way to go before they can be used to build an operational system. in this article, we contribute to bridging the gap between standards and a working solution by defining a framework that brings together the relevant standard specifications and complements them with additional building blocks. We populate this framework with concrete Ai-based algorithms that serve different purposes toward developing a fully operational system. We evaluate the performance resulting from applying our framework to control, management, and orchestration functions, showing the benefits that Ai can bring to 5G systems.pu
Performance evaluation of hybrid crowdsensing systems with stateful CrowdSenSim 2.0 simulator
Get PDFMobile crowdsensing (MCS) has become a popular paradigm for data collection in urban environments. In MCS systems, a crowd supplies sensing information for monitoring phenomena through mobile devices. Depending on the degree of involvement of users, MCS systems can be participatory, opportunistic or hybrid, which combines strengths of above approaches. Typically, a large number of participants is required to make a sensing campaign successful which makes impractical to build and deploy large testbeds to assess the performance of MCS phases like data collection, user recruitment, and evaluating the quality of information. Simulations offer a valid alternative. In this paper, we focus on hybrid MCS and extend CrowdSenSim 2.0 in order to support such systems. Specifically, we propose an algorithm for efficient re-route users that would offer opportunistic contribution towards the location of sensitive MCS tasks that require participatory-type of sensing contribution. We implement such design in CrowdSenSim 2.0, which by itself extends the original CrowdSenSim by featuring a stateful approach to support algorithms where the chronological order of events matters, extensions of the architectural modules, including an additional system to model urban environments, code refactoring, and parallel execution of algorithms.pu
SkySense: Terrestrial and Aerial Spectrum UseAnalysed Using Lightweight Sensing Technology with Weather Balloons
Get PDFGiven the availability of lightweight radio and processing technology, it becomes feasible to imagine spectrum sensing systems using weather balloons. Such balloons navigate the airspace up to 40 km, and can provide a bird's eye and clear view of terrestrial, as well as aerial spectrum use. In this paper, we present SkySense, which is an extension of the Electrosense sensing framework with mobile GPS-located sensors and local data logging. In addition, we present 6 different sensing campaigns, targeting multiple terrestrial or aerial technologies such as ADS-B, AIS or LTE. For instance, for ADS-B, we can clearly conclude that the number of airplanes that are detected is the same for each balloon altitude, but the message reception rate decreases strongly with altitude because of collisions. For each sensing campaign, the dataset is described, and some example spectrum analysis results are presented. In addition, we analyse and quantify important trends visible when sensing from the sky, such as temperature and hardware variations, increased ambient interference levels, as well as hardware limitations of the lightweight system. A key challenge is the automatic gain control and dynamic range of the system, as a radio navigating over 30km, sees a very wide range of possible signal levels. All data is publicly available through the Electrosense framework, to encourage the spectrum sensing community to further analyse the data or motivate further measurement campaigns using weather balloons.TRUEpu
Open Source RFNoC-Based Testbed for Millimeter-Wave Experimentation Using USRP Software Defined Radios
No full textMillimeter-wave (mm-wave) communications, as any other emerging technology, require suitable experimentation platforms that allow validation and field tests in both academic and industry research environments. Existing platforms formm-wave systems are based on Commercial-Off-The-Shelf(COTS) devices or expensive proprietary hardware platforms. In this paper we propose a mixed software-hardware testbedfor mm-wave experimentation using Software Defined Radio(SDR) devices. Specifically, we design and implement the hardware processing blocks required to decode the preamble of frames that follow the structure of IEEE 802.11ad compliant frames, working at a scaled-down bandwidth, along with their integration in X310 USRP devices using the RFNoC framework and 60GHz transceivers. The testbed is validated for different indoor channels with real-time Channel Impulse Response (CIR)measurements. The design exploits the maximum bandwidth for X310 devices while leaving enough FPGA logic space (≈60%),for further upgrades and extension of the system.FALSEpu
Coverage Optimization with a Dynamic Network of Drone Relays
Get PDFThe integration of aerial base stations carried by drones in cellular networks offers promising opportunities to enhance the connectivity enjoyed by ground users. In this paper, we propose an optimization framework for the 3–D placement and repositioning of a fleet of drones with a realistic inter-drone interference model and drone connectivity constraints. We show how to maximize network coverage by means of an extremal-optimization algorithm. The design of our algorithm is based on a mixed-integer non-convex program formulation for a coverage problem that is NP-Complete, as we prove in the paper. We not only optimize drone positions in a 3–D space in polynomial time, but also assign flight routes solving an assignment problem and using a strong geometrical tool, namely Bézier curves, which are extremely useful for non-uniform and realistic topologies. Specifically, we propose to fly drones following Bézier curves to seek the chance of approaching to clusters of ground users. This enhances coverage over time while users and drones move. We assess the performance of our proposal for synthetic scenarios as well as realistic maps extracted from the topology of a capital city. We demonstrate that our framework is near-optimal and using Bézier curves increases coverage up to 47% while drones move.pu