Low-latency Interaction Research Articles

Cybersecurity Implications of Edge Computing in Data Engineering

Edge computing, as an extension of cloud computing, brings computation and data storage closer to the data source. This shift offers significant advantages in terms of latency reduction, bandwidth optimization, and real-time processing capabilities. By minimizing the distance that data needs to travel, edge computing enhances the performance of applications that require rapid data processing and immediate response times. This is particularly beneficial for Internet of Things (IoT) devices, autonomous vehicles, smart grids, and other applications that demand low-latency interactions. However, the decentralization inherent in edge computing introduces a unique set of cybersecurity challenges that are distinct from those faced in traditional centralized cloud environments. The distributed architecture of edge computing creates numerous points of vulnerability, each of which can be exploited by cyber attackers. Additionally, edge devices often operate with limited computational resources and power, which complicates the implementation of robust security measures. This paper explores the cybersecurity implications of edge computing in the context of data engineering. It begins with a comprehensive review of existing literature to establish the current understanding of edge computing security issues. The review identifies the primary vulnerabilities associated with edge computing, including those related to distributed architecture, data transmission, and resource constraints. Following the literature review, the paper delves into specific security threats that edge computing environments face. These include man-in-the-middle (MitM) attacks, distributed denial-of-service (DDoS) attacks, malware and ransomware, and insider threats. Each threat is analyzed to understand its potential impact on edge computing systems and the data they process.

A Novel Visually-Lossless Compression Model for Low-Latency Interaction

A Novel Visually-Lossless Compression Model for Low-Latency Interaction

Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing

The "Software as a Service" (SaaS) model of cloud computing popularized online multiuser collaborative software. Two famous examples of this class of software are Office 365 from Microsoft and Google Workspace. Cloud technology removes the need to install and update the software on end users' computers and provides the necessary underlying infrastructure for online collaboration. However, to provide a good end-user experience, cloud services require an infrastructure able to scale up to the task and allow low-latency interactions with a variety of users worldwide. This is a limiting factor for actors that do not possess such infrastructure. Unlike cloud computing which forgets the computational and interactional capabilities of end users' devices, the edge computing paradigm promises to exploit them as much as possible. To investigate the potential of edge computing over cloud computing, this paper presents a method for engineering interactive collaborative software supported by edge devices for the replacement of cloud computing resources. Our method is able to handle user interface aspects such as connection, execution, migration, and disconnection differently depending on the available technology. We exemplify our approach by developing a distributed Pictionary game deployed in two scenarios: a nonshared scenario where each participant interacts only with their own device and a shared scenario where participants also share a common device, including a TV. After a theoretical comparative study of edge vs. cloud computing, an experiment compares the two implementations to determine their effect on the end user's perceived experience and latency vs. real latency.

Toward Hyper-Realistic and Interactive Social VR Experiences in Live TV Scenarios

Social Virtual Reality (VR) allows multiple distributed users getting together in shared virtual environments to socially interact and collaborate. This article explores the applicability and potential of Social VR in the broadcast sector, focusing on a live TV show use case, by providing three main contributions: 1) a novel and lightweight social VR platform; 2) a professional piece of VR content to recreate an interactive live TV show; and 3) an analysis of the performance and user experience. The Social VR platform includes different innovative and outstanding features compared to state-of-the-art solutions. It allows a real-time integration of remote users in shared virtual environments, using realistic volumetric representations and affordable capturing systems, thus not relying on the use of synthetic avatars. It supports a seamless and rich integration of heterogeneous media formats, including 3D scenarios, dynamic volumetric representation of users and (live/stored) stereoscopic 2D and 180°/360° videos. In addition, it enables low-latency interaction between volumetric users and a video-based presenter (Chroma keying) and a dynamic control of the media playout to adapt to the session’s evolution. The article also describes the production process of an immersive an interactive TV show to demonstrate the platform’s capabilities and its potential benefits. On the one hand, the results from objective tests show the satisfactory performance of the platform. On the other hand, the promising results from user tests support the potential impact of the presented platform, opening up new opportunities in the broadcast sector.

KD-Box: Line-segment-based KD-tree for Interactive Exploration of Large-scale Time-Series Data.

Time-series data-usually presented in the form of lines-plays an important role in many domains such as finance, meteorology, health, and urban informatics. Yet, little has been done to support interactive exploration of large-scale time-series data, which requires a clutter-free visual representation with low-latency interactions. In this paper, we contribute a novel line-segment-based KD-tree method to enable interactive analysis of many time series. Our method enables not only fast queries over time series in selected regions of interest but also a line splatting method for efficient computation of the density field and selection of representative lines. Further, we develop KD-Box, an interactive system that provides rich interactions, e.g., timebox, attribute filtering, and coordinated multiple views. We demonstrate the effectiveness of KD-Box in supporting efficient line query and density field computation through a quantitative comparison and show its usefulness for interactive visual analysis on several real-world datasets.

Edge-Centric Distributed Discovery and Access in the Internet of Things

Massive diffusion of constrained devices communicating through low-power wireless technologies in the future Internet of Things (IoT) will require in many scenarios the deployment of IoT gateways to allow applications to discover and access IoT resources. In this context, Fog/Edge computing will represent an opportunity to deploy IoT gateways in proximity of IoT domains, meeting the requirements of applications needing low-latency interactions with devices. In this paper, we present an edge-centric distributed architecture to provide resource discovery and access services to IoT applications. The proposed approach leverages the CoRE Resource Directory interface and the Constrained Application Protocol (CoAP) to expose a standard interface for global discovery and access. Multiple IoT gateways are federated through a peer-to-peer overlay implemented by a distributed hash table, which is exploited to share the information on IoT resources available across multiple domains. The proposed solution is validated by means of a small-scale prototype, and extensively evaluated through emulation in large scale deployment in comparison to a centralized Cloud-based approach. Experimental results demonstrated that the proposed approach guarantees lower latencies than a centralized solution and can ensure scalability for small to medium sized deployments.

Future multimedia user interfaces

No matter how powerful or elegant the technologies underlying multimedia computing, it is the user interface that ultimately determines how these systems will be used. We provide an overview of two emerging areas of user-interface research that will play major roles in future multimedia systems: virtual environments and ubiquitous computing. We discuss what they are and why they are important, and describe their relationship to current multimedia systems. While mouse and window-based user interfaces provide access to 2D graphics, video, and sound, virtual environments not only involve interactive 3D graphics, but further address all our senses through the use of spatial audio, haptics, and other modalities. While it is still a research goal to provide high-throughput video on demand, ubiquitous computing will require that multimedia network infrastructure also support extremely low-latency interaction among large numbers of mobile wireless users. To arrive at an understanding of the needs, capabilities, and potential of these new paradigms, we introduce their terminology and technology, and explain the basic system architectures being explored, leading up to a discussion of key current research issues and future directions.