Augmented Reality over NDN networks

About us

Brief summary of the project objectives: Existing Augmented Reality (AR) applications, similar to the Web, are built upon the widespread TCP/IP protocol stack and rely on cloud computation. To enable pervasive AR applications, it is important to explore new computing paradigms, new approaches to network communications, and new business models. Information Centric Networking (ICN or also called as Named Data Networking, NDN, or Content Centric Networking, CCN), a proposed new internet architecture, can be an enabler for pervasive AR by supporting local resource discovery, offering built-in communication security, and enabling experimentation with new business models. Moreover, Edge computing paradigms, which utilize performance advantage of server class hardware within physical vicinity, could achieve the required low latency while protecting user privacy. Edge computing paradigms are important in accomplishing pervasive AR, for performance and privacy reasons. The goal of the proposal is to support Edge Cloud Computing (ECC) for NDN to address the requirements of resource discovery, trust management, multicast support for context-content exchange, and experimentation with new business and user experience.

Rövid összefoglaló a projekt célkitűzéseiről: A kiterjesztett valóság (angol szaknyelven Augmented Reality: AR) alkalmazások egyre közelebb kerülnek ahhoz, hogy meghódítsák a világot. A gyenge láncszem a TCP/IP protokoll-struktúrán keresztül üzemelő felhő alapú kiszolgálás, amely a jelenleg elterjedt megoldás és a világháló rengeteg szolgáltatásánál bevált. Egyre világosabb, hogy a kiterjesztett valóság széleskörű elterjedéséhez új kommunikációs szolgáltatásokat, új hálózati megoldásokat és új üzleti modelleket kell kidolgozni. Az AR igenyeihez az ú.n. tartalomközpontú hálózatok (angol szaknyelven Information Centric Networking: ICN, vagy a vele rokon Named Data Networking: NDN, másnéven a Content Centric Networking: CCN) internet architektúra koncepciója áll legközelebb, ami támogatja a fizikailag közel lévő szabad erőforrások feltérképezését, hálózati szinten támogatja a titkosítást, és nagyobb teret enged új üzleti modellek megvalósítására. További fontos építőkocka az alacsony késleltetésű szolgáltatások megvalósítására a felhő szolgáltatások új generációja, a perem számítás (angol szaknyelven edge cloud computing ECC), amellyel a kiszolgálás nem csak az adatközpontokban történik, hanem részben kitelepítik azt a hálózat peremére, például a mobil bázisállomásokra. Ez a megoldás már képes megfelelően alacsony késleltetést és teljesítményt garantálni az AR számára. Projektünk célja az NDN integrálása ECC környezetbe, ezzel megvalósítva a AR elterjedéséhez szükséges hiányzó szolgáltatásokat, mint a kis késleltetéssel elérhető közeli szabad erőforrások feltérképezése a hálózatban, a titkosításhoz szükséges kulcs menedzsment, a többesadás hatékony támogatása információs tartalmak hatékony cseréjére, és új üzleti modellek kidolgozására, illetve megvalósítására.

Project call (Pályázati felhívás): Magyar-koreai kutatás-fejlesztési együttműködési pályázat (2018-2.1.17-TÉT-KR) https://nkfih.gov.hu/palyazoknak/nkfi-alap/magyar-koreai-kfi-egyuttmukodes/2018-2117-tet-kr

Project ID (Projekt azonosító): 2018-2.1.17-TÉT-KR-2018-00012

Technologies and prototypes

Stable matching method for cloud scheduling

More and more data centers are being deployed in order to accommodate the physical resources needed by cloud systems. As an important side effect the global energy demand of data centers are also on the rise. In the meantime the advancement in virtualization technologies has made migrating virtual machines from one host to another without shutting them down possible. Therefore the optimization of data center operations through the dynamic placement of virtual machines became a reality. We formalize the well-studied cloud scheduling problem in a matching theoretical model in which the virtual machine to physical server mapping is translated into a stable matching problem.

Safe and efficient Human-Robot Collaboration

Human-Robot Collaboration (HRC) is an essential feature of future Industry 4.0 production systems which requires sophisticated collision avoidance mechanisms with intense computation need. Digital twins provide a novel way to test the impact of different control decisions in a simulated virtual environment even in parallel. In addition, Virtual/Augmented Reality (VR/AR) applications can revolutionize future industry environments. Each component requires extreme computational power which can be provided by cloud platforms but at the cost of higher delay and jitter. Moreover, clouds bring a versatile set of novel techniques easing the life of both developers and operators.

Resource provisioning for highly reliable and ultra-responsive edge applications

Edge and fog computing are emerging concepts extending traditional cloud computing by deploying compute resources closer to the users. This approach, closely integrated with carrier-networks, enables several future services, such as tactile internet, 5G and beyond telco services, and extended reality applications. The emphasis is on integration: the rigorous delay constraints, ensuring reliability on the distributed remote nodes, and the sheer scale altogether call for a powerful provisioning platform that offers the applications the best out of the underlying infrastructure.

Network-aware big data applications in edge-cloud systems

The amount of data collected in various IT systems has grown exponentially in the recent years. So the challenge rises how we can process those huge datasets with the fulfillment of strict time criteria and of effective resource consumption, usually posed by the service consumers. We present the steps we made towards network-aware big data task scheduling over such distributed systems. We propose different resource orchestration algorithms for two potential challenges we identify related to network resources of a geographically distributed topology: decreasing end-to-end latency and effectively allocating network bandwidth.

Scalable edge cloud platforms for IoT services

Emerging cloud platforms that tightly integrate compute and network resources enable novel services, such as versatile IoT (Internet of Things), augmented reality or Tactile Internet applications. Virtual infrastructure managers (VIMs), network controllers and upper-level orchestrators are in charge of managing these distributed resources. A key and challenging task of these orchestrators is to find the proper placement for software components of the services. We propose two architecture options together with proof-of-concept prototypes and corresponding embedding algorithms, which enable the provisioning of delay-sensitive IoT applications.

Parentheses Tree Based Multicast header processor 2

We implemented a separate software package for the source routing multicast method, which was made available under the GNU GPLv3 open source license.

Products and services

AR over NDN

AR over NDN is an integrated system and software package, with the help of which we can build an NDN "overlay" network over general-purpose hardware elements from open source components. It provides an opportunity to take advantage of the inherent multicast support of NDN, which can ensure efficient network operation for AR applications with well-designed identification schemes, while the increased FIB (Forwarding Information Base) tables of NDN routers can be efficiently compressed using well-chosen compression algorithms.



AR over NDN as a Product

To demonstrate the capabilities of the basic system and to present the development details, we designed and implemented an example AR application based on Unity. It provides a collaborative 3D design/drawing environment where multiple (up to thousands) users can join and edit or view the design space using AR tools. On the one hand, real Android-based clients can be connected to the specific application, but we also provide the possibility to connect emulated users, which can be used to test the scaling properties. This application required very precise, continuous synchronization between many users, which follows a so-called all-to-all communication pattern, where everyone exchanges information with every other participant. Our system can effectively solve this with a lower traffic load due to the profit from multiple drops, and it can also ensure the necessary low latency, because the processing modules running in NDN nodes operate with minimal processing latency. We used several open-source software packages and improved or adapted them in the system.

AR over NDN as a Service

The entire AR over NDN platform can be operated independently as a product, but it is also possible to operate it as a service. In such cases, an operator is responsible for ensuring the operation of the entire platform and "overlay" network, and users can use the offered capabilities as a service. This means that applications developed for the special NDN platform can be run in the environment provided by the operator. We also provide a sample application to demonstrate the development of special NDN-compatible applications. It is a Unity-based AR application that provides a collaborative 3D design/drawing environment where multiple (up to thousands) users can join and edit or view the design space using AR tools.



Kubernetes edge-cloud orchestrator extension

Kubernetes has become the most popular cluster manager during the past 5 years. It is used primarily for orchestrating data center deployments running web applications. Its powerful features, e.g., self-healing and scaling, have attracted a huge community, which in turn, is inducing a meteoric rise of this open source project. We venture to shape Kubernetes to be suited for edge infrastructure. As mostly delay-sensitive applications are to be deployed in the edge, a topology-aware Kubernetes is needed, extending its widely-used feature set with regard to network latency. Moreover, as the edge infrastructure is highly prone to failures and is considered to be expensive to build and maintain, self-healing features must receive more emphasis than in the baseline Kubernetes. We therefore designed a custom Kubernetes scheduler that makes its decisions with applications' delay constraints and edge reliability in mind. In this demonstration we show the novel features of our Kubernetes extension, and describe the solution that we release as open source.

Demo

Publications

A stable matching method for cloud scheduling
László Toka, Barnabás Gema, Balázs Sonkoly

2019 IEEE 8th International Conference on Cloud Networking (CloudNet)

Cloud-Powered Digital Twins: Is It Reality?
Balázs Sonkoly, Bálint György Nagy, János Dóka, István Pelle, Géza Szabó, Sándor Rácz, János Czentye, László Toka

2019 IEEE 8th International Conference on Cloud Networking (CloudNet)

Resource provisioning for highly reliable and ultra-responsive edge applications
László Toka, Dávid Haja, Attila Kőrősi, Balázs Sonkoly

2019 IEEE 8th International Conference on Cloud Networking (CloudNet)

Towards making big data applications network-aware in edge-cloud systems
Dávid Haja, Balázs Vass, László Toka

2019 IEEE 8th International Conference on Cloud Networking (CloudNet)

Towards Human-Robot Collaboration: An Industry 4.0 VR Platform with Clouds Under the Hood
Bálint György Nagy, János Dóka, Sándor Rácz, Géza Szabó, István Pelle, János Czentye, László Toka, Balázs Sonkoly

2019 IEEE 27th International Conference on Network Protocols (ICNP)

Scalable edge cloud platforms for IoT services
Balázs Sonkoly, Dávid Haja, Balázs Németh, Márk Szalay, János Czentye, Róbert Szabó, Rehmat Ullah, Byung-Seo Kim, László Toka

2020 Journal of Network and Computer Applications (JNCA)

AR over NDN: augmented reality applications and the rise of information centric networking
János Dóka, Bálint György Nagy, Muhammad Atif Ur Rehman, Dong-Hak Kim, Byung-Seo Kim, László Toka, Balázs Sonkoly

2020 ACM SIGCOMM

Demo

Cost and Latency Optimized Edge Computing Platform
István Pelle, Márk Szalay, János Czentye, Balázs Sonkoly, László Toka

2022 MDPI Electronics

Survey on Placement Methods in the Edge and Beyond
Balázs Sonkoly, János Czentye, Márk Szalay, Balázs Németh, László Toka

2021 IEEE Communications Surveys & Tutorials

Contacts