Search

Traffic replay can effectively improve the fidelity of network emulation and support emerging network verification and network security evaluation. A distributed traffic replay system based on cloud platform is designed for large-scale, high-speed and highly concurrent network traffic emulation, named DTRS. Aiming at the diverse network traffic, a scalable multi-stream replay method is proposed to realize the flexible reproduction of multiple protocol traffic. A traffic replay strategy based on DPDK is proposed to achieve accurate control of the replay process and improve the timing fidelity of replay. To solve the problem of insufficient traffic replay speed, a vector packet processing strategy based on VPP is proposed to improve the throughput. The experimental results show that DTRS can realize the scalable loading of diverse network traffic, and support the flexible, realistic and controllable reproduction of massive heterogeneous network scenarios. In high- speed traffic emulation, DTRS can ensure the timing fidelity of replay. Compared with traditional methods, the traffic replay throughput of DTRS has increased by 3.71 times. [ABSTRACT FROM AUTHOR]

Distributed network emulators allow users to perform network evaluation by running large-scale virtual networks over a cluster of fewer machines. While they offer accessible testing environments for researchers to evaluate their contributions and for the community to reproduce its results, their use of limited physical network and compute resources can silently and negatively impact the emulation results. In this paper, we present a methodology that uses linear optimization to extract information about the physical infrastructure from emulation-level packet delay measurements, in order to pinpoint the root causes of emulation inaccuracy with minimal hypotheses. We evaluate the precision of our methodology using numerical simulations and then show how its implementation performs in a real network scenario. [ABSTRACT FROM AUTHOR]

Network emulation offers a flexible solution for network deployment and operations, leveraging software to consolidate all nodes in a topology and utilizing the resources of a single host system server. This research paper investigated the state of cybersecurity in virtualized systems, covering vulnerabilities, exploitation techniques, remediation methods, and deployment strategies, based on an extensive review of the related literature. We conducted a comprehensive performance evaluation and comparison of two network-emulation platforms: Graphical Network Simulator-3 (GNS3), an established open-source platform, and the SEED Internet Emulator, an emerging platform, alongside physical Cisco routers. Additionally, we present a Distributed System that seamlessly integrates network architecture and emulation capabilities. Empirical experiments assessed various performance criteria, including the bandwidth, throughput, latency, and jitter. Insights into the advantages, challenges, and limitations of each platform are provided based on the performance evaluation. Furthermore, we analyzed the deployment costs and energy consumption, focusing on the economic aspects of the proposed application.

Network emulation offers a flexible solution for network deployment and operations, leveraging software to consolidate all nodes in a topology and utilizing the resources of a single host system server. This research paper investigated the state of cybersecurity in virtualized systems, covering vulnerabilities, exploitation techniques, remediation methods, and deployment strategies, based on an extensive review of the related literature. We conducted a comprehensive performance evaluation and comparison of two network-emulation platforms: Graphical Network Simulator-3 (GNS3), an established open-source platform, and the SEED Internet Emulator, an emerging platform, alongside physical Cisco routers. Additionally, we present a Distributed System that seamlessly integrates network architecture and emulation capabilities. Empirical experiments assessed various performance criteria, including the bandwidth, throughput, latency, and jitter. Insights into the advantages, challenges, and limitations of each platform are provided based on the performance evaluation. Furthermore, we analyzed the deployment costs and energy consumption, focusing on the economic aspects of the proposed application. [ABSTRACT FROM AUTHOR]

Traffic replay can effectively improve the fidelity of network emulation and can support emerging network verification and network security evaluation. A distributed traffic replay framework for network emulation, named DTRF, is designed for large-scale and high-fidelity network traffic emulation on the cloud platform. A fast traffic replay strategy bypassing the kernel is proposed to improve the traffic replay performance in the single node by alleviating the problem of high overhead from the kernel protocol stack. To conveniently expand the emulation scale, an extendable method of workflow orchestration that can realize the flexible control and configuration of the execution process of emulation tasks is proposed. The experimental results show that, compared with that of the traditional method, the throughput of traffic replay is increased by 3.71 times on average, the number of concurrent streams is increased by 4.18 times on average, and the timestamp error of the replayed packets is reduced by 97.8% on average. The DTRF can expand the emulation scenario to a massive heterogeneous network. [ABSTRACT FROM AUTHOR]

In this paper, utilising real-internet traffic data, we modified a popular network emulator to better imitate real network traffic and studied its subjective and objective implications on QoE for cloud-gaming apps. Subjective QoE evaluation was then used to compare cross-correlated QoS metric with the default non-correlated emulator setup. Human test subjects showed different correlated versus non-correlated QoS parameters affects regarding cloud gaming QoE. Game-QoE is influenced more by network degradation than video QoE. To validate our subjective QoE study, we analysed the experiment's video objectively. We tested how well Full-Reference VQA measures subjective QoE. The correlation between FR QoE and subjective MOS was greater in non-correlated QoS than in correlated QoS conditions. We also found that correlated scenarios had more stuttering events compared to non-correlated scenarios, resulting in lower game QoE. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The innovations of key technologies enable and promote the future development of networks and the network industry.Therefore, there is an urgent need for a network experimental platform that can easily and quickly verify innovative network technologies, so asto effectively lower the innovation barriers and promote innovations.By analyzing the advantages of network emulation technology in network experiments and combining the demand of network technology innovation for network experiment platform, a network emulation experiment platform Klonet for network technology innovation was proposed.The platform can flexibly expand the scale of the network, emulate the network in all perspectives, manage the emulated network in a fine-grained manner, and thus ease the workflow of network experimentation.The experimental method on Klonet was described and the ability of Klonet to support network technology innovation was verified based on two specific use cases.

Faithfully emulating networks is critical for verifying the correctness and effectiveness of new networking-related designs. Existing network experiment platforms either cannot faithfully emulate the functionality and performance of production networks or cannot scale well due to cost constraints. In this paper, we propose TurboNet, a new network emulator that utilizes one or more programmable switches to achieve faithful emulation of the network data plane and control plane. For data plane emulation, we propose a series of key designs, such as port mapper, queue mapper, and delayed queue, to emulate network topologies and performance metrics with high flexibility and accuracy. For control plane emulation, we support static routing configurations, distributed routing agents, and the centralized routing controllers. Meanwhile, we provide APIs for operators to simplify network emulation tasks. We implement TurboNet on Tofino switches. Evaluation results show that: (1) On the data plane, TurboNet can flexibly emulate various topologies, such as an 8-ary fat-tree with only one programmable switch and a 10-ary fat-tree with four programmable switches; (2) On the control plane, TurboNet supports about 200 BGP agents on a single programmable switch with a CPU usage of 25%; (3) TurboNet can accurately emulate different network performance metrics such as 10−8 link loss, and microsecond to millisecond link delay. [ABSTRACT FROM AUTHOR]

Mobile Area NETworks (MANETs) can be modelled as time-varying graphs as their topology and traffic demands change. Optimizing routing in MANETs by proactively adapting the routes is a challenge, even with a fixed topology and user demand. Omniscient Dijkstra Routing (ODRb) is one of the best known approaches, which computes alternative paths but has limitations to mitigate congestions. In this paper, we investigate Graph Neural Networks (GNNs) for routing optimization in MANETs. Our contribution is inspired by the centralized GNN-based Data Driven Routing (GDDR) framework developed by Hope [15]. GDDR was developed for optical fibre networks to support time varying user demands. After failing to obtain good results using the GDDR approach on the tactical Anglova MANET scenario, we adapted GDDR to minimize the maximum number of traversals. Our GNN-t proposal is able to find alternative longer paths mitigating congestion on central nodes. Considering a challenging static topology, the first second of the 24-node Anglova scenario: GNN-t achieves a Completion Ratio of CR=99% for a trffic of acked-messages averaging 1msg/s/node and CR=77% when the traffic is doubled (2msg/s/node). For the challenging first 300s of Anglova CP1, similar performance is reported for ODRb and GNN-t: CR=81% without fading and CR=54% with fading.. [ABSTRACT FROM AUTHOR]

Network emulators enable rapid prototyping and testing of applications. In a typical emulation, the execution order and process execution burst lengths are managed by the host platform's operating system, largely independent of the emulator. Timerbased mechanisms are typically used, but the imprecision of timer firings introduces imprecision in the advancement of time. This leads to statistical variation in behavior that is not due to the model. This article describes an open-source tool called Kronos, which provides a set of mechanisms for precise instruction-level tracking of process execution and control over execution order of containers, thus improving the mapping of executed behavior to advancement in time. This, and control of execution and placement of emulated processes in virtual time make the behavior of the emulation independent of the CPU resources of the platform that hosts the emulation. Under Kronos each process has its own virtual clock that is advanced based on a count of the number of \(\times \) 86 assembly instructions executed by its children. Two types of instruction counting techniques are discussed: (1) hardware-assisted mechanisms that are transparent to the executing application and (2) binary instrumentation-assisted mechanisms that modify the executing binary. We analyze the overheads associated with each approach and experimentally demonstrate the impact of Kronos' time advancement precision by comparing it against emulations that, like Kronos, are embedded in virtual time, but unlike Kronos rely on Linux timers to control virtual machines and measure their progress in virtual time. We present two useful applications where Kronos aids in generating high-fidelity emulation results at low hardware costs: (1) analyzing protocol performance and (2) enabling analysis of cyber physical control systems. We also discuss limitations associated with simple linear conversions between instruction counts and ascribed virtual time and develop and evaluate more accurate virtual time conversion models. [ABSTRACT FROM AUTHOR]

Cyber Ranges represent complex, multi-component informatic systems, mainly used in the cyber security field. This domain is not the only operational scope of the Cyber Range concept. The applicability of this kind of system presents great benefits in domains like education, research, military etc. The entire scope of Cyber Range systems may be classified into three main categories: training and simulation, research and e-learning. The complexity of a Cyber Range system involves a time and financial consuming implementation. Depending on the area of operation, implementation may vary because each domain involves specific components. As a result, there must be steps prior to implementation in which the whole set of required pieces must be determined precisely. The existence of an implementation methodology may increase the performance and decrease the implementation costs - in the manner of time and financial resources. This paper aims to lay the foundations of a methodology for implementing cyber range systems in the main fields (training and simulation, research and e-learning). Starting from this methodology, detailed configuration and implementation procedures can be developed in each branch of each field. [ABSTRACT FROM AUTHOR]

In this paper, utilising real-internet traffic data, we modified a popular network emulator to better imitate real network traffic and studied its subjective and objective implications on QoE for cloud-gaming apps. Subjective QoE evaluation was then used to compare cross-correlated QoS metric with the default non-correlated emulator setup. Human test subjects showed different correlated versus non-correlated QoS parameters affects regarding cloud gaming QoE. Game-QoE is influenced more by network degradation than video QoE. To validate our subjective QoE study, we analysed the experiment’s video objectively. We tested how well Full-Reference VQA measures subjective QoE. The correlation between FR QoE and subjective MOS was greater in non-correlated QoS than in correlated QoS conditions. We also found that correlated scenarios had more stuttering events compared to non-correlated scenarios, resulting in lower game QoE.

Traffic replay can effectively improve the fidelity of network emulation and can support emerging network verification and network security evaluation. A distributed traffic replay framework for network emulation, named DTRF, is designed for large-scale and high-fidelity network traffic emulation on the cloud platform. A fast traffic replay strategy bypassing the kernel is proposed to improve the traffic replay performance in the single node by alleviating the problem of high overhead from the kernel protocol stack. To conveniently expand the emulation scale, an extendable method of workflow orchestration that can realize the flexible control and configuration of the execution process of emulation tasks is proposed. The experimental results show that, compared with that of the traditional method, the throughput of traffic replay is increased by 3.71 times on average, the number of concurrent streams is increased by 4.18 times on average, and the timestamp error of the replayed packets is reduced by 97.8% on average. The DTRF can expand the emulation scenario to a massive heterogeneous network.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Network emulation is an essential method to test network architecture, protocol and application software during a network's entire life-cycle. Compared with simulation and test-bed methods, network emulation possesses the advantages of accuracy and cost-efficiency. However, legacy network emulators are typically restricted in scalability, agility, and extensibility, which builds barriers to prevent them from being widely used. In this paper, we introduce the currently prevalent cloud computing and the related technologies including resource virtualization, NFV (network functional virtualization), SDN (software-defined networking), traffic control and flow steering to the network emulation domain. We design and implement an innovative cloud-based network emulation platform, aiming at providing users Network Emulation as a Service (NEaaS), which can be conveniently deployed on both public and private clouds. In order to emulate networks of much larger scale, and to reduce the hardware cost of the proposed platform, a representative light-weighted virtualization technology, namely Docker container is adopted as a supplement to virtual machine (VM) to emulate networking nodes in a hybrid manner. We carried out a comprehensive performance evaluation with in-depth discussions for this emulation platform. It turns out, our platform can significantly outperform legacy network emulators regarding to scalability, agility, and extensibility in large scale emulation scenarios, with much lower costs. Finally, a case study of applying the proposed platform to emulate a typical space-ground integrated network (SGIN) is given, which illustrates the platform's effectivity and efficiency. [ABSTRACT FROM AUTHOR]

In the recent years, resource virtualization technologies of different types have been widely used in the ICT industry, particularly in cloud computing domain. These virtualization technologies can squeeze out hardware potential and consequently can significantly save CAPEX and OPEX. Virtualization technologies are adopted in network emulation to emulate heterogeneous nodes of target networks. At present, network emulators typically utilize legacy x86-based virtual machines (VMs) and light-weighted containers to emulate network nodes of heterogeneous architectures including ARM, SPARC, PPC, etc., which introduces software incompatibility to the original system software, protocols and applications, and may consequently jeopardize emulation fidelity. This paper focuses on mitigating the emulation incompatibility problem caused by node heterogeneity. Firstly, this problem is thoroughly investigated and analyzed on a cloud-based network emulation platform. Then, a hybrid virtualization approach concurrently utilizing multiple virtualization technologies, namely KVM, QEMU, and Docker to emulate heterogeneously architected nodes is derived and then implemented in the cloud-based network emulation platform. Functional verification and performance evaluation experiments have been carried out and have led to the conclusion that the elaborated hybrid virtualization approach can effectively dispose of the emulation incompatibility problem with affordable performance degradations. In addition, a case study of applying the hybrid virtualization approach to emulate a space-ground integrated network (SGIN) is conducted to show its effectivity and efficiency. [ABSTRACT FROM AUTHOR]

In software system testing using Bluetooth Low Energy (BLE), it is necessary to evaluate the system, including the wireless communication. However, it is difficult to build a test environment for testing with physical machines because of installation costs. This problem can be solved by emulation to reproduce BLE communication on computers; however, a BLE emulator is required. In this paper, we propose a BLE emulator called BluMoon for testing software systems using BLE. We impose the following requirements on the BLE emulator: (1) calculating the received signal strength for each frame and (2) imitating radio interference. To satisfy these requirements, we devised a software-implemented BLE controller with a host controller interface as a boundary and devised a data format called the BluMoon frame for sending and receiving data frame by frame. We designed and implemented BluMoon, and performed functional and performance evaluation as well as a comparative experiment with a physical environment. The results revealed that it is possible to implement a BLE emulator that meets the aforementioned requirements. [ABSTRACT FROM AUTHOR]

This paper presents MaxHadoop, a flexible and scalable emulation tool, which allows the efficient and accurate emulation of Hadoop environments over Software Defined Networks (SDNs). Hadoop has been designed to manage endless data-streams over networks, making it a tailored candidate to support the new class of network services belonging to Big Data. The development of Hadoop is contemporary with the evolution of networks towards the new architectures "Software Defined." To create our emulation environment, tailored to SDNs, we employ MaxiNet, given its capability of emulating large-scale SDNs. We make it possible to emulate realistic Hadoop scenarios on large-scale SDNs using low-cost commodity hardware, by resolving a few key limitations of MaxiNet through appropriate configuration settings. We validate the MaxHadoop emulator by executing two benchmarks, namely WordCount and TeraSort, to evaluate a set of Key Performance Indicators. The tests' outcomes evidence that MaxHadoop outperforms other existing emulation tools running over commodity hardware. Finally, we show the potentiality of MaxHadoop by utilizing it to perform a comparison of SDN-based network protocols. [ABSTRACT FROM AUTHOR]

We introduce an open-source, scalable, and distributed architecture, called Megalos, that supports the implementation of virtual network scenarios consisting of virtual devices (VDs) where each VD may have several Layer 2 interfaces assigned to virtual LANs. We rely on Docker containers to realize vendor-independent VDs and we leverage Kubernetes for the management of the nodes of a distributed cluster. Our architecture does not require platform-specific configurations and supports a seamless interconnection between the virtual environment and the physical one. Also, it guarantees the segregation of each virtual LAN traffic from the traffic of other LANs, from the cluster traffic, and from Internet traffic. Further, a packet is only sent to the cluster node containing the recipient VD. We produce several example applications where we emulate large network scenarios, with thousands of VDs and LANs. Finally, we experimentally show the scalability potential of Megalos by measuring the overhead of the distributed environment and of its signaling protocols.

Adaptive video streaming over HTTP is becoming omnipresent in our daily life. In the past, dozens of research papers have proposed novel approaches to address different aspects of adaptive streaming and a decent amount of player implementations (commercial and open source) are available. However, state of the art evaluations are sometimes superficial as many proposals only investigate a certain aspect of the problem or focus on a specific platform – player implementations used in actual services are rarely considered. HTML5 is now available on many platforms and foster the deployment of adaptive media streaming applications. We propose a common evaluation framework for adaptive HTML5 players and demonstrate its applicability by evaluating eight different players which are actually deployed in real-world services.

Security attacks are becoming a standard part of the Internet and their frequency is constantly increasing. Therefore, an efficient way to research and investigate attacks is needed. Studying attacks needs to be coupled with security evaluation of currently deployed systems that are affected by them. The security evaluation and research process needs to be completed quickly to counter the incoming attacks, but this is currently a complex and time-consuming procedure which includes a variety of systems and tools. Furthermore, as the attack frequency is increasing, new security specialists need to be trained in a comprehensible and standardized way. We propose a new approach to security evaluation and research that uses scalable network emulation based on lightweight virtualization implemented in IMUNES. This approach provides a unified testing environment that is efficient and straightforward to use. The emulated environment also couples as a portable and intuitive training tool. Through a series of implemented and evaluated scenarios we demonstrate several concepts that can be used for a novel approach in security evaluation and research.

The development of protocols for mobile networks, especially for vehicular ad-hoc networks (VANETs), presents great challenges in terms of testing in real conditions. Using a production network for testing communication protocols may not be feasible, and the use of small networks does not meet the requirements for mobility and scale found in real networks. The alternative is to use simulators and emulators, but vehicular network simulators do not meet all the requirements for effective testing. Aspects closely linked to the behaviour of the network nodes (mobility, radio communication capabilities, etc.) are particularly important in mobile networks, where a delay tolerance capability is desired. This paper proposes a distributed emulator, EmuCD, where each network node is built in a container that consumes a data trace that defines the node’s mobility and connectivity in a real network (but also allowing the use of data from simulated networks). The emulated nodes interact directly with the container’s operating system, updating the network conditions at each step of the emulation. In this way, our emulator allows the development and testing of protocols, without any relation to the emulator, whose code is directly portable to any hardware without requiring changes or customizations. Using the facilities of our emulator, we tested InterPlanetary File System (IPFS), Sprinkler and BitTorrent content dissemination protocols with real mobility and connectivity data from a real vehicular network. The tests with a real VANET and with the emulator have shown that, under similar conditions, EmuCD performs closely to the real VANET, only lacking in the finer details that are extremely hard to emulate, such as varying loads in the hardware.

Virtualization has the advantages of strong scalability and high fidelity in host node emulation. It can effectively meet the requirements of network emulation, including large scale, high fidelity, and flexible construction. However, for router emulation, virtual routers built with virtualization and routing software use Linux Traffic Control to emulate bandwidth, delay, and packet loss rates, which results in serious distortions in congestion scenarios. Motivated by this deficiency, we propose a novel router emulation method that consists of virtualization plane, routing plane, and a traffic control method. We designed and implemented our traffic control module in multi-scale virtualization, including the kernel space of a KVM-based virtual router and the user space of a Docker-based virtual router. Experiments show not only that the proposed method achieves high-fidelity router emulation, but also that its performance is consistent with that of a physical router in congestion scenarios. These findings provide good support for network research into congestion scenarios on virtualization-based emulation platforms.