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Using Simu5G as a Realtime Network Emulator to Test MEC Apps in an End-To-End 5G Testbed
Abstract
Multi-access Edge Computing (MEC) allows users to run appli-cations on demand near their mobile access points. MEC appli-cations will exploit 5G infrastructure, and they will have to be designed by taking into account the characteristics of 5G mobile networks. This work describes how to use a system-level simula-tor of 5G networks – namely Simu5G, which evolves the popu-lar 4G network simulator SimuLTE – as a real-time 5G network emulator. This allows designers of networked applications – and MEC ones in particular – to use it as a testbed during the de-ployment. We describe the system setup of Simu5G as an emula-tor, and its emulation capabilities and scale. Moreover, we pre-sent a case study of a MEC testbed using Intel’s Open Network Edge Services Software (OpenNESS) toolkit, based on a recent demonstration in 5GAA (5G Automotive Association).
... Finally, three previous works of ours [13], [2], [27] are related to this one. Work [13] describes the MEC model developed for SimuLTE. ...
... For instance, the use case described in Section 5 could not have been emulated in that environmentnot even substituting 4G access for 5G. Our paper [2] describes the real-time emulation capabilities of an early release of Simu5G. As a case study, we show therein that Simu5G can provide 5G transport to a MEC app running on Intel OpenNESS [28]. ...
... As a case study, we show therein that Simu5G can provide 5G transport to a MEC app running on Intel OpenNESS [28]. On one hand, the current version of Simu5G is quite different from the one described in [2], especially for what concerns real-time emulation (thanks to the new versions of OMNeT++ and INET). On the other hand, the MEC app described therein is a simple client/server video application running on a virtual machine instantiated on a MEC host. ...
Multi-access Edge Computing (MEC) will enable context-aware services for users of mobile 4G/5G networks. MEC application developers need tools to aid the design and the performance evaluation of their apps. During the early stages of deployment, they should be able to evaluate the performance impact of design choices - e.g., what round-trip delay can be expected due to the interplay of computation, communication and service consumption. When a prototype of the app exists, it needs to be tested it live, under controllable conditions, to measure key performance indicators. In this paper, we present an open-source framework that allows developers to do all the above. Our framework is based on Simu5G, the OMNeT++-based simulator of 5G (NewRadio) and 4G (LTE) mobile networks. It includes models of MEC entities (i.e., MEC orchestrator, MEC host, etc.) and provides a standard-compliant RESTful interface towards application endpoints. Moreover, it can interface with external applications, and can also run in real time. Therefore, one can use it as a cradle to run a MEC app live, having underneath both 4G/5G data packet transport and MEC services based on information generated by the underlying emulated radio access network. We describe our framework and present a use-case of an emulated MEC-enabled 5G scenario.
... A previous work of ours [1] introduced the theme of real-time emulation with Simu5G. However, that work relies on outdated versions of Simu5G, INET and OMNeT++. ...
... However, that work relies on outdated versions of Simu5G, INET and OMNeT++. Simu5G's version in [1] relied on version 3.6.4 of the INET library, which did not exhibit the same performance as version 4.3, on which this work is based. The differences are many, and in fact involve the mechanism for interfacing with external applications. ...
... The differences are many, and in fact involve the mechanism for interfacing with external applications. All the above translated to improved baseline performance: for instance, it is now possible -and it was not in [1] -to run emulation with FG UEs at high numerologies. Moreover, in this work we have added modeling of BG UEs/gNBs, which allows Simu5G emulation to scale up considerably. ...
Real-time emulation of 5G networks is highly beneficial for several purposes, such as prototyping or performance evaluation of distributed applications meant to run on 5G networks, research demonstration, evaluation of other technologies (e.g., Multi-access Edge Computing) meant to interoperate with 5G access. In this work, we describe how to use Simu5G, a new end-to-end simulator of 5G networks based on OMNeT++, as a real-time emulator. We describe in detail the modeling choices that allow emulation to scale up without compromising accuracy. We present a thorough evaluation of the Simu5G’s emulation capabilities, showing that networks with hundreds of simulated users and tens of cells can be emulated on a single desktop machine.
... A previous work of ours [1] introduced the theme of real-time emulation with Simu5G. However, that work relies on outdated versions of Simu5G, INET and OMNeT++. ...
... However, that work relies on outdated versions of Simu5G, INET and OMNeT++. Simu5G's version in [1] relied on version 3.6.4 of the INET library, which did not exhibit the same performance as version 4.3, on which this work is based. The differences are many, and in fact involve the mechanism for interfacing with external applications. ...
... The differences are many, and in fact involve the mechanism for interfacing with external applications. All the above translated to improved baseline performance: for instance, it is now possible -and it was not in [1] -to run emulation with FG UEs at high numerologies. Moreover, in this work we have added modeling of BG UEs/gNBs, which allows Simu5G emulation to scale up considerably. ...
We verified that Simu5G can run in emulation mode, by connecting real application endpoints to modules in a simulation and having the simulation run in real time.
We verified that Simu5G can emulate up to 10 cells and 1000 users on a desktop machine.
... More recently, Nardini et. al. published results on using the system-level network simulator Simu5G in an emulation test bed for multi-access edge computing [8]. ...
... For the communication domain, the discrete event simulator OMNeT++ (version 6.0 Preview 11) is used in conjunction with the widely-used models INET (version 4.3.2), Artery [10], SimuLTE [9]/Simu5G [8]. For the mobility domain, SUMO [7] as well as the crowd dynamics framework Vadere [5] (see Sec. 2) are supported. ...
Network emulation is a well-established method for demonstrating and testing real devices and mobile apps in a controlled scenario. This paper reports preliminary results for an open-source extension of the CrowNet pedestrian communication framework. It enables the interaction between simulated and real devices using the emulation feature of OMNeT++. The interaction is handled by several OMNeT++ modules that can be combined to match different use-cases. Initial timing measurements have been conducted for an example application which creates decentralized pedestrian density maps based on pedestrian communication. The results indicate that the approach is feasible for scenarios with a limited number of pedestrians. This limitation is mainly due to the real-time simulation requirements in coupled emulation.
... Simu5G [21][22][23][24] is a system-level simulator for the data plane of the 5G NR technology, based on OMNeT++ [25]. It evolves from the well-known SimuLTE, which is a library for the simulation of 4G networks [26,27]. ...
... For instance, Simu5G can be connected to the Intel OpenNESS framework for MEC hosting [31]. Work [22] evaluates Simu5G emulation capabilities. ...
Multi-access Edge Computing (MEC) promises to deliver localized computing power and storage. Coupled with low-latency 5G radio access, this enables the creation of high added-value services for mobile users, such as in-vehicle infotainment or remote driving. The performance of these services as well as their scalability will however depend on how MEC will be deployed in 5G systems. This paper evaluates different MEC deployment options, coherent with the respective 5G migration phases, using an accurate and comprehensive end-to-end (E2E) system simulation model (exploiting Simu5G for radio access, and Intel CoFluent for core network and MEC), taking into account user-related metrics such as response time or MEC latency. Our results show that 4G radio access is going to be a bottleneck, preventing MEC services from scaling up. On the other hand, the introduction of 5G will allow a considerable higher penetration of MEC services.
... Another set of testbed studies have focused on 5G aspects related to multi-access edge computing (MEC), i.e., the paradigm of integrating computing capabilities into the 5G communication network infrastructure and operation, e.g., for in-network computation processing [38]- [40] and in-network re-coding of communication data packets [41]- [43]. Specifically, the studies [44]- [47] have conducted evaluations of MEC related frameworks and tests in the context of 5G communication systems. ...
A 5G campus network is a 5G network for the users affiliated with the campus organization, e.g., an industrial campus, covering a prescribed geographical area. A 5G campus network can operate as a so-called 5G non-stand-alone (NSA) network (which requires 4G Long-Term Evolution (LTE) spectrum access) or as a 5G standalone (SA) network (without 4G LTE spectrum access). 5G campus networks are envisioned to enable new use cases, which require cyclic delay-sensitive industrial communication, such as robot control. We design a rigorous testbed for measuring the one-way packet delays between a 5G end device via a radio access network (RAN) to a packet core with sub-microsecond precision as well as for measuring the packet core delay with nanosecond precision. With our testbed design, we conduct detailed measurements of the one-way download (downstream, i.e., core to end device) as well as one-way upload (upstream, i.e., end device to core) packet delays and losses for both 5G standalone (SA) and 5G non-standalone (NSA) hardware and network operation.We also measure the corresponding 5G SA and 5G NSA packet core processing delays for download and upload. We find that typically 95% of the SA download packet delays are in the range from 4–10 ms, indicating a fairly wide spread of the packet delays. Also, existing packet core implementations regularly incur packet processing latencies up to 0.4 ms, with outliers above one millisecond. Our measurement results inform the further development and refinement of 5G SA and 5G NSA campus networks for industrial use cases. We make the measurement data traces publicly available as the IEEE DataPort 5G Campus Networks: Measurement Traces dataset (DOI 10.21227/xe3c-e968).
This paper describes an open LTE uplink link level simulator. The simulator is developed using MATLAB and is offered under an academic non-profit license, including the source code. This released model allows the easy and open reproduction of results which addresses a common problem found in signal processing research in which reproducing the work of others is either highly complex or just not possible. This paper presents the basic structure of the simulator, as well as first results for AWGN channels, showing BER and throughput performance.
This paper presents Simu5G, a new OMNeT++-based system-level simulator of 5G networks. Simu5G is built starting from the SimuLTE simulation library, which models 4G (i.e., LTE/LTE-A) networks, and is compatible with the latter, thus allowing the simulation of 4G-5G coexistence and transition scenarios. We discuss the modelling of the protocol layers, network entities and functions, and validate our abstraction of the physical layer using 3GPP-based scenarios. Moreover, we report profiling results related to Simu5G execu-tion, and we describe how it can be employed to evaluate Radio Access Network configurations, as well as end-to-end scenarios involving communication and computation, e.g., with Multi-access Edge Computing applications.
With the convergence of mobility and communication in modern Intelligent Transportation Systems (ITS), researchers and developers require simulation tools that are capable of bringing both worlds together. Unlike existing approaches that couple specialized simulators using Inter-Process Communication (IPC), the proposed Lightweight Information and Communications Technology-centric Mobility Simulation (LIMoSim) uses a shared codebase for mobility and communication algorithms, enabling interactions between both worlds in a native way and offering transparent integration of vehicular mobility for all INET-based extension frameworks. The proposed framework relies on selected, well-known analytical models and requires only a single process for the actual execution of the simulation runs, thus enabling lean setups without synchronization-related overhead. In this chapter, we introduce LIMoSim and its possible applications using different case-studies.
In Long Term Evolution-Advanced (LTE-A), network-controlled device-to-device (D2D) communications allow User Equipments (UEs) to communicate directly, without involving the Evolved Node-B in data relaying, while the latter still retains control of resource allocation. The above paradigm allows reduced latencies for the UEs and increased resource efficiency for the network operator, and is therefore foreseen to support several services, from Machine-to-machine to vehicular communications. D2D communications introduce research challenges that might affect the performance of applications and upper-layer protocols, hence simulations represent a valuable tool for evaluating these aspects. However, simulating D2D features might pose additional com-putational burden to the simulation environment. To this aim, a careful modeling is required in order to reduce computational overhead. In this paper we describe our modeling of net-work-controlled D2D communications in SimuLTE, a system-level LTE-A simulation library based on OMNeT++. We describe the core modeling choices of SimuLTE, and show how these allow an easy extension to D2D communications. Moreover, we describe in detail the modeling of specific problems arising with D2D communications, such as scheduling with frequency reuse, connection mode switching and broadcast transmission. We document the computational efficiency of our modeling choices, showing that simulation of D2D communications is not more complex than simulation of classical cellular communications of comparable scale. Results show that the heaviest computational burden of D2D communication lies in estimating the Sidelink channel quality. We show that SimuLTE allows one to evaluate the interplay between D2D communication and end-to-end performance of UDP- and TCP-based services. Moreover, we assess the accuracy of using a binary interference model for frequency reuse, and we evaluate the trade-off between speed of execution and accuracy in modeling the reception probability.
In this work we present SimuLTE, an OMNeT++-based simulator for LTE and LTE-Advanced networks. Following well-established OMNeT++ programming practices, SimuLTE exhibits a fully modular structure, which makes it easy to be extended, verified, and integrated. Moreover, it inherits all the benefits of such a widely used and versatile simulation framework as OMNeT++, i.e., experiment support and seamless integration with the OMNeT++ network modules, such as INET. This allows SimuLTE users to build up mixed scenarios where LTE is only a part of a wider network. This paper describes the architecture of SimuLTE, with particular emphasis on the modeling choices at the MAC layer, where resource scheduling is located. Furthermore, we describe some of the verification and validation efforts and present an example of the performance analysis that can be carried out with SimuLTE.
Recently, many efforts have been made to develop more efficient Inter-Vehicle Communication (IVC) protocols for on-demand route planning according to observed traffic congestion or incidents, as well as for safety applications. Because practical experiments are often not feasible, simulation of network protocol behavior in Vehicular Ad Hoc Network (VANET) scenarios is strongly demanded for evaluating the applicability of developed network protocols. In this work, we discuss the need for bidirectional coupling of network simulation and road traffic microsimulation for evaluating IVC protocols. As the selection of a mobility model influences the outcome of simulations to a great extent, the use of a representative model is necessary for producing meaningful evaluation results. Based on these observations, we developed the hybrid simulation framework Veins (Vehicles in Network Simulation), composed of the network simulator OMNeT++ and the road traffic simulator SUMO. In a proof-of-concept study, we demonstrate its advantages and the need for bidirectionally coupled simulation based on the evaluation of two protocols for incident warning over VANETs. With our developed methodology, we can advance the state-of-the-art in performance evaluation of IVC and provide means to evaluate developed protocols more accurately.