Dockemu 2.0: Evolution of a Network Emulation Tool

Petersen, Erick; Cotto, Guillermo; To, Marco Antonio

doi:10.1109/concapanxxxix47272.2019.8977002

Cited by 11 publications

(8 citation statements)

References 16 publications

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“…All experiments were performed by using the network simulator version 3 (ns-3) [18], the MP-QUIC library [11], and the docker [19]. The docker has been implemented by using the DOCKEMU [20,21].…”

Section: Performance Analysis By Experimentations 41 Testbed Configurationmentioning

confidence: 99%

Proxy-Based Adaptive Transmission of MP-QUIC in Internet-of-Things Environment

2021

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With the growth of Internet of Things (IoT) services and applications, the efficient transmission of IoT data has been crucially required. The IETF has recently developed the QUIC protocol for UDP-based multiplexed and secure transport. The Multipath QUIC (MP-QUIC) is also being discussed as an extension of QUIC in the multipath network environment. In this paper, we propose a proxy-based adaptive MP-QUIC transmission for throughput enhancement in the IoT environment. In the proposed scheme, a proxy device is employed between IoT clients and IoT server to aggregate the traffics of many clients in the access network. The proxy will transport a large among of traffics to the server, adaptively to the network conditions, by using multiple paths in the backbone network. For this purpose, the proxy device employs a path manager to monitor the current network conditions and a connection manager to manage the MP-QUIC connections with the IoT server over the backbone network with multiple paths. For effective MP-QUIC transmission, the proxy will transmit the prioritized packets to the server using the best path with the lowest round-trip time (RTT), whereas the non-prioritized packets are delivered over the other paths for traffic load balancing in the network. From the testbed experimentations with the MP-QUIC implementation and ns-3 simulation modules, we see that the proposed scheme can outperform the normal QUIC (using a single path) and the existing MP-QUIC scheme (using the round-robin policy) in terms of response delay and total transmission delay. Such performance gaps tend to increase as the link delays and packet loss rates get larger in the network.

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Section: Performance Analysis By Experimentations 41 Testbed Configurationmentioning

confidence: 99%

Proxy-Based Adaptive Transmission of MP-QUIC in Internet-of-Things Environment

2021

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“…We define this functionality to be present when the test environment supports to alter the domain environment during runtime in a way that is expected to introduce faults in the application running on the nodes. [23] 2017 C ----IOTier [24] 2021 -C TS --Fogify [30] 2020 C TS --MockFog [12] 2019 V TS --Blockade [33] 2014 C TS --Distem [28] 2013 C TS --Fogbed [6] 2018 C SDN --EmuFog [20] 2017 C SDN --Dockemu [26] 2015 C NS --EmuEdge [35] 2019 VC TS --Héctor [2] 2019 V TS --Sendorek et al [29] 2018 -V SDN --Chameleon [14] 2015 V SDN --StarBED [21] 2002 V SDN --UiTiOt [16] 2017 -C NS --WHYNET [38] 2006 -V NS --MobiNet [17] 2005 -V NS --…”

Section: Domain Environmentmentioning

confidence: 99%

“…Using Network Simulation. Dockemu [26] is the only tool without hardware integration that uses network simulation. It utilizes the network simulator ns-3 to model the communication between nodes, which in turn are represented by Docker containers.…”

Section: Test Environments Without Hardware Integrationmentioning

confidence: 99%

Continuously Testing Distributed IoT Systems: An Overview of the State of the Art

Beilharz¹,

Wiesner²,

Boockmeyer³

et al. 2021

Preprint

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The continuous testing of small changes to systems has proven to be useful and is widely adopted in the development of software systems. For this, software is tested in environments that are as close as possible to the production environments. When testing IoT systems, this approach is met with unique challenges that stem from the typically large scale of the deployments, heterogeneity of nodes, challenging network characteristics, and tight integration with the environment among others. IoT test environments present a possible solution to these challenges by emulating the nodes, networks, and possibly domain environments in which IoT applications can be executed. This paper gives an overview of the state of the art in IoT testing. We derive desirable characteristics of IoT test environments, compare 18 tools that can be used in this respect, and give a research outlook of future trends in this area.

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“…In this case, simulating support is proposed by using ns-3 to simulate the physical layer. 31 Thus, each docker container is connected to a simulated ns-3 network through tap devices providing hybrid capabilities, as shown in Figure 5. Ns-3 support gives DockSDN the ability to simulate several types of networks such as IP or none IP networks as well as wireless networks (Wi-Fi, WiMAX, LTE, and 5G) in addition to mobile networks with flexible grid settings.…”

Section: Docksdn Frameworkmentioning

confidence: 99%

“…Different from current emulators, one of the main features of DockSDN is the ability of creating scenarios and then emulating or simulating them depending on the need of the experiment. In this case, simulating support is proposed by using ns‐3 to simulate the physical layer 31 . Thus, each docker container is connected to a simulated ns‐3 network through tap devices providing hybrid capabilities, as shown in Figure 5.…”

Section: Docksdn Frameworkmentioning

confidence: 99%

DockSDN: A hybrid container‐based software‐defined networking emulation tool

Petersen

2021

Int J Network Mgmt

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Summary The Internet has proven to be able to connect billions of devices across the globe. In order to keep pace with today's high demands or even larger services and applications, traditional ways of networking will have to change or update. The future of computer networks needs to be agile without degrading efficiency, capacity, and availability. These new trends push forward the need for network programmability. Software‐defined networkings (SDNs) are the future of networking, but in order to deploy newer standards, they have to be tested. Furthermore, this calls for better testbeds that are close to a real environment as possible. Many tools have been proposed to provide a framework for testing newer approaches of networking, but they have come short in various characteristics, limiting the scenarios and their results. Our experience in containers (Docker) and the development of testbeds using this technology has now brought our attention to SDNs. DockSDN provides a tool that meets current and future needs and is our biggest contribution to the scientific community so far. DockSDN is presented in this work, which proposes various benefits and advantages over other tools. One of those benefits is that it uses dockers as building blocks for scenario deployment. Moreover, these scenarios can be done fairly quickly and is fully scalable through local PC hardware or elastic through cloud services. Now, the scientific community will be able to test a wide array of protocols in near real‐world conditions, saving financial resources and time.

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Dockemu 2.0: Evolution of a Network Emulation Tool

Cited by 11 publications

References 16 publications

Proxy-Based Adaptive Transmission of MP-QUIC in Internet-of-Things Environment

Proxy-Based Adaptive Transmission of MP-QUIC in Internet-of-Things Environment

Continuously Testing Distributed IoT Systems: An Overview of the State of the Art

DockSDN: A hybrid container‐based software‐defined networking emulation tool

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