Thin Client Devices Research Articles

Progressive 3D Reconstruction for Collaborative Construction of Digital Twins

Digital twins are increasingly useful in metaverse-related applications, but their construction process usually involves deep technical expertise and costly resources. This position paper demonstrates an early prototype (see Figure 1) of a web-based digital twin authoring system to enable untrained users to collaboratively build digital twin environments. The system aims to explore the combination of photogrammetry and GAN-based machine learning models to enable near-real-time collaboration between capture client (scanning objects using common smartphone cameras) and editing client (constructing 3D scenes on thin client devices) users.

QuadStream

Streaming rendered 3D content over a network to a thin client device, such as a phone or a VR/AR headset, brings high-fidelity graphics to platforms where it would not normally possible due to thermal, power, or cost constraints. Streamed 3D content must be transmitted with a representation that is both robust to latency and potential network dropouts. Transmitting a video stream and reprojecting to correct for changing viewpoints fails in the presence of disocclusion events; streaming scene geometry and performing high-quality rendering on the client is not possible on limited-power mobile GPUs. To balance the competing goals of disocclusion robustness and minimal client workload, we introduce QuadStream , a new streaming content representation that reduces motion-to-photon latency by allowing clients to efficiently render novel views without artifacts caused by disocclusion events. Motivated by traditional macroblock approaches to video codec design, we decompose the scene seen from positions in a view cell into a series of quad proxies , or view-aligned quads from multiple views. By operating on a rasterized G-Buffer, our approach is independent of the representation used for the scene itself; the resulting QuadStream is an approximate geometric representation of the scene that can be reconstructed by a thin client to render both the current view and nearby adjacent views. Our technical contributions are an efficient parallel quad generation, merging, and packing strategy for proxy views covering potential client movement in a scene; a packing and encoding strategy that allows masked quads with depth information to be transmitted as a frame-coherent stream; and an efficient rendering approach for rendering our QuadStream representation into entirely novel views on thin clients. We show that our approach achieves superior quality compared both to video data streaming methods, and to geometry-based streaming.

A Compact Ciphertext-Policy Attribute-Based Encryption Scheme for the Information-Centric Internet of Things

The information-centric Internet of things (IC-IoT) is different from the traditional Internet of things (IoT) in that the device-to-device pattern is generalized to a device-to-network pattern. Furthermore, in an IC-IoT environment, there is a demand for protecting the security of all data generated from IC-IoT devices. A cryptography scheme named attribute-based encryption (ABE) represents a smart method of providing the fine-grained access control that can sufficiently protect data security. The most attractive advantage of ABE is its expressive access policy, which makes the access control of data flexible and manageable. However, there is a serious problem caused by such an access policy; it incurs a greater ciphertext redundancy and computational overhead. This implies that the current ABE scheme is hard to implement in the thin client devices of IC-IoT. In this paper, we propose a universalized policy-compacting method via sharing public parts of the policy. Compared with the original policy, the compacted policy applies a more compact ciphertext and requires less computation, communication, and storage cost. However, the policy-compacting problem is proved to be a non-deterministic polynomial complete (NPC) problem. Thus, a greedy algorithm is provided to obtain an approximate minimum compacted policy scale. Finally, we propose a compact ciphertext-policy attribute-based encryption (CCP-ABE) scheme with the policy-compacting method. A security proof and performance evaluation show that the proposed CCP-ABE scheme provides a comprehensive performance improvement.

A New Technique for Optimizing Resource Allocation and Data Distribution in Mobile Cloud Computing

The emergence of mobile cloud computing (MCC) brings benefits to mobile users and cloud providers. However, due to the inherent limitations of the device such as battery life time, CPU and memory capacity, a mobile thin client device ( e.g. smart phones, tablets, iWatch, Google Glass, etc ) cannot meet the requirements of some demanding applications. To alleviate this limitation, the mobile device should cooperate with external resources to increase its performance. Recently, current research approaches have been unable to offer an efficient, seamless computing experience. In this paper, we present a comprehensive thin-thick client collaboration that involves conventional desktop or laptop computers, known as thick clients, by allowing the thin client to borrow resources from thick clients, particularly for optimizing data distribution and utilizing MCC resources to meet Service-Level Agreements, Quality-of-Service requirements and cloud service customers’ budget. Our work uses both numerical analysis and simulation to prove that our proposed architecture can improve resource allocation efficiency and achieve better performance than other existing approaches in some cases. DOI: http://dx.doi.org/10.5755/j01.eee.22.1.14113

Thin is green: Leveraging the thin-client paradigm for sustainable mobile computing

Progress in the area of environmental sustainability for the mobile computing industry could be achieved by making advancement on two fronts: reducing the energy consumed by individual devices throughout their life cycle and reducing the rate at which these devices are discarded. In this work, to address both fronts, we propose the use of a thin-client approach, whereby a mobile device relies mainly on the resources at a remote server to carry out application tasks. To assess the benefits of the proposed approach, this work develops an analytical model as well as performs an empirical evaluation of performance and energy consumption on Android-based smartphones. In terms of energy, a reduction of approximately 11% in the average life cycle energy (LCE) is seen by increasing the device’s usage life by even three months through a thin-client approach. In terms of performance, a thin-client device is shown to improve execution by 57% compared to a self-reliant device.

An Architecture Approach for 3D Render Distribution using Mobile Devices in Real Time

Nowadays, video games such as Massively Multiplayer Online Game (MMOG) have become cultural mediators. Mobile games contribute to a large number of downloads and potential benefits in the applications market. Although processing power of mobile devices increases the bandwidth transmission, a poor network connectivity may bottleneck Gaming as a Service (GaaS). In order to enhance performance in digital ecosystem, processing tasks are distributed among thin client devices and robust servers. This research is based on the method �divide and rule�, that is, volumetric surfaces are subdivided using a tree-KD of sequence of scenes in a game, so reducing the surface into small sets of points. Reconstruction efficiency is improved, because the search of data is performed in local and small regions. Processes are modeled through a finite set of states that are built using Hidden Markov Models with domains configured by heuristics. Six test that control the states of each heuristic, including the number of intervals are carried out to validate the proposed model. This validation concludes that the proposed model optimizes response frames per second, in a sequence of interactions.

An Adaptive Procedure for Task Scheduling Optimization in Mobile Cloud Computing

Nowadays, mobile cloud computing (MCC) has emerged as a new paradigm which enables offloading computation-intensive, resource-consuming tasks up to a powerful computing platform in cloud, leaving only simple jobs to the capacity-limited thin client devices such as smartphones, tablets, Apple’s iWatch, and Google Glass. However, it still faces many challenges due to inherent problems of thin clients, especially the slow processing and low network connectivity. So far, a number of research studies have been carried out, trying to eliminate these problems, yet few have been found efficient. In this paper, we present an enhanced architecture, taking advantage of collaboration of thin clients and conventional desktop or laptop computers, known as thick clients, particularly aiming at improving cloud access. Additionally, we introduce an innovative genetic approach for task scheduling such that the processing time is minimized, while considering network contention and cloud cost. Our simulation shows that the proposed approach is more cost-effective and achieves better performance compared with others.

Comparing Embodied Greenhouse Gas Emissions of Modern Computing and Electronics Products

Information and communications technology (ICT) contributes substantially to global greenhouse gas (GHG) pollutant emissions, but it is time-consuming to estimate the environmental impacts caused by the production of ICT devices, and the literature lacks coverage for newer products. Using a process-sum life cycle assessment (LCA) approach, we estimate and compare the embodied GHG emissions of 11 ICT products, including large- and small-form-factor desktop and laptop personal computers, a thin client device, an LCD monitor, newer mobile devices (an Apple iPad, an iPod Touch, and an Amazon Kindle), a rack server, and a network switch. Full bills of materials are provided via hand disassembly and weighing and are mapped to processes in the ecoinvent v2.2 database to produce impact estimates. Results are analyzed to develop simplified impact estimation models using linear regressions based on product characteristics. A simple and robust linear relationship between mass and embodied emissions is identified; a more sophisticated linear model using display mass, battery mass, and circuit board mass as inputs is slightly more accurate. Embodied GHG emissions for newer products are 50-60% lower than corresponding older products with similar functionality, largely due to decreased material usage, especially reductions in integrated circuit content.

THUNDER: helping underfunded NPO’s distribute electronic resources

As federal funding in many public non-profit organizations (NPO’s) seems to be dwindling, it is of the utmost importance that efforts are focused on reducing operating costs of needy organizations, such as public schools. Our approach for reducing organizational costs is through the combined benefits of a high performance cloud architecture and low-power, thin-client devices. However, general-purpose private cloud architectures are not easily deployable by average users, or even those with some computing knowledge. For this reason, we propose a new vertical cloud architecture, which is focused on ease of deployment and management, as well as providing organizations with cost-efficient virtualization and storage, and other organization-specific utilities. We postulate that if organizations are provided with on-demand access to electronic resources in a way that is cost-efficient, then the operating costs may be reduced, such that the user experience and organizational efficiency may be increased. In this paper we discuss our private vertical cloud architecture called THUNDER. Additionally, we introduce a number of methodologies that could enable needy non-profit organizations to decrease costs and also provide many additional benefits for the users. Specifically, this paper introduces our current implementation of THUNDER, details about the architecture, and the software system that we have designed to specifically target the needs of underfunded organizations.

클라우드 환경의 Thin-Client 모바일을 위한 동적 자원 분배 기술

클라우드 컴퓨팅의 폭발적 성장으로 IT를 활용하는 다양한 분야에 걸쳐 클라우드 기반의 시스템을 이용한 연구가 활발하게 진행되어 왔다. 특히, 클라우드 시스템을 이용하여 가상 머신 기반의 데스크탑 환경(DaaS, Desktop as a Service) 및 가상 모바일 환경을 구축하여 씬 클라이언트 형태로 어플리케이션 서비스를 이용하는 연구가 활발하게 진행 중에 있다. 본 논문은 씬 클라이언트 모바일 단말에서 모바일 어플리케이션 수행에 필요한 클라우드 시스템과, 자원 분배 시스템인 DRAMMA(Dynamic Resource Allocation Manager for Mobile Application)를 제안하고 있다. 또한 성능평가를 통해 DRAMMA가 기존의 클라우드 환경의 자원 분배 알고리즘과 비교하여 클라우드 시스템의 활용성을 높였고, 더 적은 가상머신의 이동, 자원 할당에 나타나는 오류를 줄여 보다 효율적인 서비스가 가능함을 확인 할 수 있었다. The study of Cloud based system is emerging to become the core technology in IT field due to the tremendous growth of Cloud Computing. Researches to deliver applications to Thin-Client based mobile virtual machine and Desktop as a Service(DaaS) using Cloud Computing are conducted actively. In this paper, we propose a Cloud system to run the mobile application in the mobile Thin-Client device and resource allocation mechanism Dynamic Resource Allocation Manager for Mobile Application(DRAMMA). Thus, through performance check, we show DRAMMA has improved the utilization of Cloud system, less migration of virtual machines and decreased the error rate of resource allocation. Also our proposed system delivers service more efficiently than the previous resource allocation algorithm.

Thin clients: slim security?

Thin computing has been around since early 1993, starting life as graphical workstations and X terminals. The devices have evolved, along with advancements in modern computing technologies, to become more complex, hybrid embedded devices and appliances, with many capable of running standalone operating systems. They have become a popular choice for IT organisations as desktop replacements owing to their lower costs, eco-friendly benefits and marketing by vendors claiming additional security benefits. Indeed, they are often marketed as something of a security silver bullet compared with traditional desktops. To assess the accuracy of these claims, we performed an independent security evaluation of several popular thin-client devices by analysing device management and determining risk and feasibility of attacks against organisations that have adopted thin-client technologies.

Impromptu Service Discovery and Delivery in Mobile Environments

Wireless hotspots and broadband coverage are permeating the globe, giving rise to interesting spontaneous networking scenarios. The discovery and delivery of the most relevant and suitable services in a spontaneous network is a problem of great importance. In this paper we present an architecture that can support context-aware service discovery and delivery for resource-constrained mobile devices. At the heart of the architecture is the μJini proxy which mediates the discovery and delivery processes. Its discovery subsystem exploits relevant context information for the highest quality instance discovery. Its delivery subsystem provides thin-client based adaptation for fat service delivery not supported by thin client devices. To demonstrate its effectiveness, we developed a proofof-concept prototype for Java mobile service environments.