skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Demo: EdgeVPN.io: Open-source Virtual Private Network for Seamless Edge Computing with Kubernetes
Edge and fog computing encompass a variety of technologies that are poised to enable new applications across the Internet that support data capture, storage, processing, and communication across the networking continuum. These environments pose new challenges to the design and implementation of networks-as membership can be dynamic and devices are heterogeneous, widely distributed geographically, and in proximity to end-users, as is the case with mobile and Internet-of-Things (IoT) devices. We present a demonstration of EdgeVPN.io (Evio for short), an open-source programmable, software-defined network that addresses challenges in the deployment of virtual networks spanning distributed edge and cloud resources, in particular highlighting its use in support of the Kubernetes container orchestration middleware. The demo highlights a deployment of unmodified Kubernetes middleware across a virtual cluster comprising virtual machines deployed both in cloud providers, and in distinct networks at the edge-where all nodes are assigned private IP addresses and subject to different NAT (Network Address Translation) middleboxes, connected through an Evio virtual network. The demo includes an overview of the configuration of Kubernetes and Evio nodes and the deployment of Docker-based container pods, highlighting the seamless connectivity for TCP/IP applications deployed on the pods.  more » « less
Award ID(s):
2004323 2004441
PAR ID:
10221380
Author(s) / Creator(s):
;
Date Published:
Journal Name:
2020 IEEE/ACM Symposium on Edge Computing (SEC)
Volume:
1
Page Range / eLocation ID:
190 to 192
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, The IEEE Smart World Congress 2017 (IEEE SWC 2017))
    The rapid growth in technology and wide use of internet has increased smart applications such as intelligent transportation control system, and Internet of Things, which heavily rely on an efficient and reliable connectivity network. To overcome high bandwidth work load on the network, as well as minimize latency for real-time applications, the computation can be moved from the central cloud to a distributed edge cloud. The edge computing benefits various smart applications that uses distributed network for data analytics and services. Different from the existing cloud management solutions, edge computing needs to move cloud management services towards distributed heterogeneous edge nodes for multi-tenant user applications. However, existing cloud management services do not offer remote deployment of multi-tenant user applications on the cloud of edge nodes. In this paper, we propose a practical edge cloud software framework for deploying multi-tenant distributed smart applications. Having multiple distributed end nodes, auto discovery of all active end nodes is required for deploying multi-tenant user applications. However, existing cloud solutions require either private network or fixed IP address, which is not achievable for the distributed edge nodes. Most of the edge nodes connected through the public internet without fixed IP, and some of them even connect through IEEE 802.15 based sensor networks. We propose to build a software platform to manage the distributed edge nodes as well as support services to deploy and launch isolated, multi-tenant user applications through a lightweight container. We propose an architectural solution to remotely access edge cloud management services through intermittent internet connections. We open sourced our whole set of software solutions, and analyzed the major performance metrics of the edge cloud platform. 
    more » « less
  2. ; ; (, 26th {IEEE} International Symposium on Local and Metropolitan Area Networks, {LANMAN} 2020, Orlando, FL, USA, July 13-15, 2020)
    Kubernetes, an open-source container orchestration platform, has been widely adopted by cloud service providers (CSPs) for its advantages in simplifying container deployment, scalability and scheduling. Networking is one of the central components of Kubernetes, providing connectivity between different pods (group of containers) both within the same host and across hosts. To bootstrap Kubernetes networking, the Container Network Interface (CNI) provides a unified interface for the interaction between container runtimes. There are several CNI implementations, available as open-source ‘CNI plugins’. While they differ in functionality and performance, it is a challenge for a cloud provider to differentiate and choose the appropriate plugin for their environment. In this paper, we compare the various open source CNI plugins available from the community, qualitatively and through detailed quantitative measurements. With our experimental evaluation, we analyze the overheads and bottlenecks for each CNI plugin, as a result of the network model it implements, interaction with the host network protocol stack and the network policies implemented in iptables rules. The choice of the CNI plugin may also be based on whether intra-host or inter-host communication dominates. 
    more » « less
  3. ; ; ; ; ; (, Wireless Communications and Mobile Computing)
    Edge application’s distributed nature presents significant challenges for developers in orchestrating and managing the multitenant applications. In this paper, we propose a practical edge cloud software framework for deploying multitenant distributed smart applications. Here we exploit commodity, a low cost embedded board to form distributed edge clusters. The cluster of geo-distributed and wireless edge nodes not only power multitenant IoT applications that are closer to the data source and the user, but also enable developers to remotely deploy and orchestrate application containers over the cloud. Specifically, we propose building a software platform to manage the distributed edge nodes along with support services to deploy and launch isolated and multitenant user applications through a lightweight container. In particular, we propose an architectural solution to improve the resilience of edge cloud services through peer collaborated service migration when the failures happen or when resources are overburdened. We focus on giving the developers a single point control of the infrastructure over the intermittent and lossy wide area networks (WANs) and enabling the remote deployment of multitenant applications. 
    more » « less
  4. ; ; ; (, IEICE transactions on communications)
    Systems for Internet of Things (IoT) have generated new requirements in all aspects of their development and deployment, including expanded Quality of Service (QoS) needs, enhanced resiliency of computing and connectivity, and the scalability to support massive numbers of end devices in a variety of applications. The research reported here concerns the development of a reliable and secure IoT/cyber physical system (CPS), providing network support for smart and connected communities, to be realized by means of distributed, secure, resilient Edge Cloud (EC) computing. This distributed EC system will be a network of geographically distributed EC nodes, brokering between end-devices and Backend Cloud (BC) servers. This paper focuses on three main aspects of the CPS: a) resource management in mobile cloud computing; b) information management in dynamic distributed databases; and c) biological-inspired intrusion detection system. 
    more » « less
  5. ; ; ; ; ; ; ; (, 2021 IEEE 17th International Conference on eScience (eScience))
    The management of drinking water quality is critical to public health and can benefit from techniques and technologies that support near real-time forecasting of lake and reservoir conditions. The cyberinfrastructure (CI) needed to support forecasting has to overcome multiple challenges, which include: 1) deploying sensors at the reservoir requires the CI to extend to the network’s edge and accommodate devices with constrained network and power; 2) different lakes need different sensor modalities, deployments, and calibrations; hence, the CI needs to be flexible and customizable to accommodate various deployments; and 3) the CI requires to be accessible and usable to various stakeholders (water managers, reservoir operators, and researchers) without barriers to entry. This paper describes the CI underlying FLARE (Forecasting Lake And Reservoir Ecosystems), a novel system co-designed in an interdisciplinary manner between CI and domain scientists to address the above challenges. FLARE integrates R packages that implement the core numerical forecasting (including lake process modeling and data assimilation) with containers, overlay virtual networks, object storage, versioned storage, and event-driven Function-as-a-Service (FaaS) serverless execution. It is a flexible forecasting system that can be deployed in different modalities, including the Manual Mode suitable for end-users’ personal computers and the Workflow Mode ideal for cloud deployment. The paper reports on experimental data and lessons learned from the operational deployment of FLARE in a drinking water supply (Falling Creek Reservoir in Vinton, Virginia, USA). Experiments with a FLARE deployment quantify its edge-to-cloud virtual network performance and serverless execution in OpenWhisk deployments on both XSEDE-Jetstream and the IBM Cloud Functions FaaS system. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email