An Analysis and Empirical Study of Container Networks

Suo, Kun; Zhao, Yong; Chen, Wei; Rao, Jia

doi:10.1109/infocom.2018.8485865

Cited by 63 publications

(33 citation statements)

References 11 publications

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“…For instance, Weave Net creates a virtual network that connects containers across multiple hosts and enables their automatic discovery [ 24 ]. Calico provides a highly scalable network with high throughput rates that would be valuable for data-intensive parallel algorithms [ 25 ]. Note that the performance comparison of the virtual networks is outside the scope of this study.…”

Section: Methodsmentioning

confidence: 99%

On-the-Fly Fusion of Remotely-Sensed Big Data Using an Elastic Computing Paradigm with a Containerized Spark Engine on Kubernetes

Huang

Zhou

Zhang

2021

Sensors

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Remotely-sensed satellite image fusion is indispensable for the generation of long-term gap-free Earth observation data. While cloud computing (CC) provides the big picture for RS big data (RSBD), the fundamental question of the efficient fusion of RSBD on CC platforms has not yet been settled. To this end, we propose a lightweight cloud-native framework for the elastic processing of RSBD in this study. With the scaling mechanisms provided by both the Infrastructure as a Service (IaaS) and Platform as a Services (PaaS) of CC, the Spark-on-Kubernetes operator model running in the framework can enhance the efficiency of Spark-based algorithms without considering bottlenecks such as task latency caused by an unbalanced workload, and can ease the burden to tune the performance parameters for their parallel algorithms. Internally, we propose a task scheduling mechanism (TSM) to dynamically change the Spark executor pods’ affinities to the computing hosts. The TSM learns the workload of a computing host. Learning from the ratio between the number of completed and failed tasks on a computing host, the TSM dispatches Spark executor pods to newer and less-overwhelmed computing hosts. In order to illustrate the advantage, we implement a parallel enhanced spatial and temporal adaptive reflectance fusion model (PESTARFM) to enable the efficient fusion of big RS images with a Spark aggregation function. We construct an OpenStack cloud computing environment to test the usability of the framework. According to the experiments, TSM can improve the performance of the PESTARFM using only PaaS scaling to about 11.7%. When using both the IaaS and PaaS scaling, the maximum performance gain with the TSM can be even greater than 13.6%. The fusion of such big Sentinel and PlanetScope images requires less than 4 min in the experimental environment.

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Section: Methodsmentioning

confidence: 99%

On-the-Fly Fusion of Remotely-Sensed Big Data Using an Elastic Computing Paradigm with a Containerized Spark Engine on Kubernetes

Huang

Zhou

Zhang

2021

Sensors

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“…Open vSwitch) [11], Calico [12], Weave [13] and Flannel [14] -by using Kubernetes in a clustered environment designed for Cloud, Edge and Fog [10]. They deployed distributed microservices based on FTP and CoAP (Constrained Application Protocol) and executed the benchmarks by considering the transfer times of each microservice [10].…”

Section: Buzachis Et Al Investigated the Performance Of Four Networkmentioning

confidence: 99%

A new smart networking architecture for container network functions

2020

Turk J Elec Eng & Comp Sci

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5G slices have challenging application demands from a wide variety of fields including high bandwidth, low latency and reliability. The requirements of the Container Network Functions which are used in telecommunications are different from any other cloud native IT applications as they are used for data plane packet processing functions, together with control, signalling and media processing which have critical processing requirements. This study aims to discover high performing container networking solution by considering traffic loads and application types. The behaviour of several container cluster networking solutions-Flannel, Weave, Libnetwork, Open Virtual Networking for Open vSwitch and Calico-are explored with regard to the most commonly-used Container Network Functions in the form of MongoDB and Web access. Evaluations show that none of the solutions provide a high throughput for all types of workload under optimum or heavy load situations. Hence, this research presents the view that traditional container networking implementation methods may not fulfill the Container Network Functions' networking performance requirements. This is because container networking performance changes dynamically, depending on traffic load and application types. To overcome this problem, a new smart container networking architecture is proposed which allows containers to use several container networking solutions dynamically in conjunction with container monitoring tools. Eventually, the primary implementation of proposed architecture has been performed and evaluated. This research shows that proposed smart architecture delivers promising results compared to traditional implementation methods, in case appropriate decision is made during dynamic interface selection process.

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“…An emerging trend in emulation is that virtual nodes gain ever-growing attention and widespread adoption for their better scalability and deployability. In this paper, we propose a decentralized and lightweight emulation platform based on virtual machines (VM), as VM with a standalone kernel and network protocol stack offers the capability to thoroughly examine the implementation and a higher degree of fidelity [110] compared to the kernel-based containers.…”

Section: Emulation Platformmentioning

confidence: 99%

Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval

Xiang

et al. 2019

IJGI

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Geospatial information is gaining immense interest and importance as we enter the era of highly developed transportation and communication. Despite the proliferation of cellular network and WiFi, on some occasions, users still face barriers to accessing geospatial data. In this paper, we design and implement a distributed prototype system with a delay/disruption tolerant network (DTN), named Geo-DMP, for cooperatively and opportunistically sharing and exchanging named geospatial contents in a device-to-device fashion. First of all, we construct a lightweight “content agent” module to bridge the gap between the application layer and the underlying DTN protocol stack. Afterwards, to profile the mobility history of users in practical geospatial environments, we present a map segmentation scheme based on road network and administrative subdivision information. Subsequently, we associate the regional movement history information with the content retrieval process to devise a hierarchical and region-oriented DTN routing scheme for both requests and responses. Finally, we conduct extensive experiments with real-world trajectories and complete implementations on the emulation platform composed of virtual machines. The experiments corroborate that Geo-DMP has the capability of successfully retrieving geospatial contents for users for most of the time under mobile circumstances with episodic connectivity. Moreover, en-route caches can be efficiently exploited to provision contents from multiple sources with less network resource consumption and shorter user-perceived latencies.

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An Analysis and Empirical Study of Container Networks

Cited by 63 publications

References 11 publications

On-the-Fly Fusion of Remotely-Sensed Big Data Using an Elastic Computing Paradigm with a Containerized Spark Engine on Kubernetes

On-the-Fly Fusion of Remotely-Sensed Big Data Using an Elastic Computing Paradigm with a Containerized Spark Engine on Kubernetes

A new smart networking architecture for container network functions

Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval

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