Mixed Reality (MR) has launched from science fiction but its entrance in reality can reshape our society. By combining the physical and virtual worlds, it provides novel ways of immersive interactions and experiences and by these means enables a new generation of applications. The most exciting and challenging ones support collaborative, multi-user operation in large geographical scale, require real-time environment comprehension and high visual fidelity. The success or failure is definitely impacted by the capabilities and performance limits of edge cloud platforms and 5G/6G networks providing the offloading features for CPU/GPU intensive MR functions. In addition, the desired quality of user experience calls for further mechanisms at the application level hiding the consequences of varying network characteristics. In this paper, we propose a novel edge cloud based architecture for future remote-rendered MR applications supporting low-latency immersive interactions. Our contribution is threefold. First, the system architecture is presented focusing on the remote rendering, 3D simulation and environment detection control loops. Second, we highlight the main features of our proof-of-concept prototype and our dedicated application, namely the Mixed Reality version of a Rocket League inspired game. Third, the concepts are validated via experiments in a Beyond 5G infrastructure where we analyze the operation and latency characteristics of the overall system. In addition, the quality of the user experience is also evaluated via real-life experiments conducted as part of a student competition. The results show that the latency and jitter characteristics of the most sensitive render loop can be managed efficiently together by a network-level control (slice priorities) and an application-level (dynamic jitter buffer) mechanism.

Augmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However, multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate position and orientation information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure. Our solution is built on open-source SLAM libraries and the Robot Operating System (ROS). Our contribution is threefold. First, we propose an extensible, edge cloud based AR architecture. Second, we develop a proof-of-concept prototype supporting multiple devices. Third, a dedicated measurement methodology is described and the overall performance of the system is evaluated via real experiments.

Cloud native programming and serverless architectures provide a novel way of software development and operation. A new generation of applications can be realized with features never seen before while the burden on developers and operators will be reduced significantly. However, latency sensitive applications, such as various distributed IoT services, generally do not fit in well with the new concepts and today's platforms. In this article, we adapt the cloud native approach and related operating techniques for latency sensitive IoT applications operated on public serverless platforms. We argue that solely adding cloud resources to the edge is not enough and other mechanisms and operation layers are required to achieve the desired level of quality. Our contribution is threefold. First, we propose a novel system on top of a public serverless edge cloud platform, which can dynamically optimize and deploy the microservice-based software layout based on live performance measurements. We add two control loops and the corresponding mechanisms which are responsible for the online reoptimization at different timescales. The first one addresses the steady-state operation, while the second one provides fast latency control by directly reconfiguring the serverless runtime environments. Second, we apply our general concepts to one of today's most widely used and versatile public cloud platforms, namely, Amazon's AWS, and its edge extension for IoT applications, called Greengrass. Third, we characterize the main operation phases and evaluate the overall performance of the system. We analyze the performance characteristics of the two control loops and investigate different implementation options.

Envisioned 5G applications and services, such as Tactile Internet, Industry 4.0 use-cases, remote control of drone swarms, pose serious challenges to the underlying networks and cloud platforms. On the one hand, evolved cloud infrastructures provide the IT basis for future applications. On the other hand, networking is in the middle of a momentous revolution and important changes are mainly driven by Network Function Virtualization (NFV) and Software Defined Networking (SDN). A diverse set of cloud and network resources, controlled by different technologies and owned by cooperating or competing providers, should be coordinated and orchestrated in a novel way in order to enable future applications and fulfill application level requirements. In this paper, we propose a novel cross domain orchestration system which provides wholesale XaaS (Anything as a Service) services over multiple administrative and technology domains. Our goal is threefold. First, we design a novel orchestration system exploiting a powerful information model and propose a versatile embedding algorithm with advanced capabilities as a key enabler. The main features of the architecture include i) efficient and multi-purpose service embedding algorithms which can be implemented based on graph models, ii) inherent multidomain support, iii) programmable aggregation of different resources, iv) information hiding together with flexible delegation of certain requirements enabling multi-operator use-cases, and v) support for legacy technologies. Second, we present our proof-of-concept prototype implementing the proposed system. Third, we establish a dedicated test environment spanning across multiple European sites encompassing sandbox environments from both operators and the academia in order to evaluate the operation of the system. Dedicated experiments confirm the feasibility and good scalability of the whole framework.

Microservices, serverless architectures, cloud native programming are novel paradigms and techniques which could significantly reduce the burden on both developers and operators of future services. Several types of applications fit in well with the new concepts easing the life of different stakeholders while enabling cloud-grade service deployments. However, latency sensitive applications with strict delay constraints between different components pose additional challenges on the platforms. In order to gain benefit from recent cloud technologies for latency sensitive applications as well, a comprehensive performance analysis of available platforms and relevant components is a crucial first step. In this paper, we address one of the most widely used and versatile cloud platforms, namely Amazon Web Services (AWS), and reveal the delay characteristics of key components and services which impact the overall performance of latency sensitive applications. Our contribution is threefold. First, we define a detailed measurement methodology for CaaS/FaaS (Container/Function as a Service) platforms, specifically for AWS. Second, we provide a comprehensive analysis of AWS components focusing on delay characteristics. Third, we attempt to adjust a drone control application to the platform and investigate the performance on today's system.

Safe and efficient 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. Can these applications be realized and operated on today's systems? In this demonstration, we give answers to this question via real experiments.