Patrick Ocheja, Brendan Flanagan, Hiroaki Ogata, Solomon Sunday Oyelere
The use of blockchain in education has become one of the trending topics in education technology research. However, only a handful of education blockchain solutions have provided a measure of the impact on students' learning outcomes, teaching, or administrative processes. This work reviews how academic data stored on the blockchain is being visualized across various education blockchain solutions. We argue that education's uniqueness requires a different visualization approach that supports students' learning activities, advances teaching methods, and facilitates administrative procedures. We identify a consistent trend where most of the proposed education blockchain solutions focus on credentials collection and do not provide a way to make sense of the blockchain's data. Thus, we conducted a needs analysis by interviewing four teachers to understand essential features when accessing distributed academic data, report these results and use them to inform the features of our proposed visualizations. Our unique contributions include: presenting typical use cases of distributed learning records from multiple education institutes and demonstrating how past learning records of students stored on the blockchain can be visualized to support current learning. We also propose a method of visualization to increase the data awareness of information owners through the blockchain.
Taras Maksymyuk, Juraj Gazda, Gabriel Bugár, Vladimír Gazda · 6 authors
The future of networking will be driven by the current emerging trends of combining the physical and virtual realities in cyberspace. Considering the ambient pandemic challenges, the role of virtual and augmented reality will definitely grow over time by transforming into the paradigm of the Metaverse of Things, where each person, thing or other entity will simultaneously exist within multiple synchronized realities. In this paper, we propose a novel framework for future metaverse applications composed of multiple synchronized data flows from multiple operators through multiple wearable devices and with different quality requirements. A new service quality model is proposed based on a customizable utility function for each individual data flow. The proposed approach is based on dynamic fine-grained data flow allocation and service selection using non-fungible tokens, which can be traded over the blockchain among users and operators in a decentralized mobile network environment.
Lik‐Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang · 9 authors
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokemon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have bought us various degrees of digital transformation. The term `metaverse' has been coined to further facilitate the digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalysed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital `big bang' of our cyberspace is not far away. This survey paper presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems, and illustrates the possibility of the digital `big bang'. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously - Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors -- Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for the development of the metaverse.
Lik‐Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang · 9 authors
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments, including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokémon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have brought us various degrees of digital transformation. The term “metaverse” has been coined to facilitate further digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalyzed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital “big bang” of our cyberspace is not far away. This survey presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems and illustrates the possibility of the digital “big bang”. It is essential to highlight that the metaverse encompasses diverse technologies and ecosystems, calling it an interdisciplinary and emerging field. Its primary objective is to provide users with satisfactory and interactive experiences. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously – Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, IoT and Robotics, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors – Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for developing the metaverse.
Anderson Melo de Morais, Jorge da Silva Correia Neto, Robson Wagner Albuquerque de Medeiros, Obionor de Oliveira Nóbrega · 5 authors
Education generates a considerable amount of data and information, it is necessary to manage this data securely, avoiding problems of falsification and tampering with diplomas, certificates, and other important student documents. In addition, distance learning is becoming more popular due to the Covid-19 pandemic period, where courses are offered in virtual learning environments such as Moodle. Blockchain technology can be used as a tool to ensure the security of data managed by Moodle. However, there is a gap in current state-of-the-art solutions for integrating these data with Blockchain platforms. This work proposes BlockMoodle, a solution developed to integrate Moodle with Blockchain Ethereum. This work also performs an analysis of the financial cost of using the tool. In addition, a performance evaluation of the proposed solution is also carried out considering different usage scenarios. Finally, the conclusions and future work to be developed are presented.
Christoph Kinkeldey, Jean‐Daniel Fekete, Tanja Blascheck, Petra Isenberg
We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e., by individuals, companies, or other groups actively using Bitcoin. BitConduite makes Bitcoin data accessible to nontechnical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts.
In this work, we consider community detection in blockchain networks. We specifically take the Bitcoin network and Ethereum network as two examples, where community detection serves in different ways. For the Bitcoin network, we modify the traditional community detection method and apply it to the transaction social network to cluster users with similar characteristics. For the Ethereum network, on the other hand, we define a bipartite social graph based on the smart contract transactions. A novel community detection algorithm which is designed for low-rank signals on graph can help find users' communities based on user-token subscription. Based on these results, two strategies are devised to deliver on-chain advertisements to those users in the same community. We implement the proposed algorithms on real data. By adopting the modified clustering algorithm, the community results in the Bitcoin network is basically consistent with the ground-truth of betting site community which has been announced to the public. At the meanwhile, we run the proposed strategy on real Ethereum data, visualize the results and implement an advertisement delivery on the Ropsten test net.
Multiobject tracking is a basic task in video analysis. Due to the strict requirements on efficiency and resource consumption, most of the applications on edge devices are online or near-online methods. Besides motion modeling, appearance information is also widely used for tracking. However, the influence of occlusion is usually ignored. In this article, spatial-temporal co-occurrence constraints (STCCs) features are introduced to resist occlusions by exploring the rich spatial and temporal information of tracklets. In addition, a novel blockchain-based near-online framework called co-occurrence constraints tracklet tracker (CoCTs) is proposed for cross-camera tracking. It inherits the advantages of the blockchain technology in sharing information. Based on blockchain, an efficient association mechanism and a reliable information sharing method are introduced. Experimental results show that CoCT performs high computational efficiency and low resource consumption. In the edge computing environment, it achieves real-time performance on cross-camera tracking. On the MOT17 benchmark, our method shows the state-of-the-art results compared with other online trackers.
The fifth-generation (5G) cellular technology aims at providing network services at high speed with reliable Quality of Service (QoS). To enable this, 5G deploys Massive Multi-Input Multi-Out-put (MIMO) to increase the capacity of a Base Station (BS) and the efficiency of the network. Provisioning guaranteed and reliable services to support MIMO requires effective resource management. Blockchain is a highly promising solution to enable multi-dimensional management of various resources such as spectrum allocation and user association. It can potentially mitigate spectrum under-utilization and can help in scaling up the deployment of different 5G services. In this article, we present a model for Blockchain-based multi-operator service provisioning for 5G users with Intra and Inter spectrum management among multiple telecom operators. In particular, we present a Blockchain-based implementation model for spectrum sharing between the operators to minimize spectrum under-utilization.
While industry has adopted blockchain-based video-streaming platforms, other stakeholders could contribute more to grow the technology and support its implementation. This article reviews current blockchain-based video streaming applications and industrial advancements and identifies today's research activities and future opportunities for investigation.
Jie Feng, F. Richard Yu, Qingqi Pei, Jianbo Du · 5 authors
The application of blockchain to mobile edge computing (MEC) systems has attracted great interests. However, the design and optimization of blockchain and MEC in most existing works are done separately, which will result in sub-optimal performance. In this paper, we propose a joint optimization framework for blockchain-enabled MEC systems to achieve the optimal trade-off between the performance of the MEC system and the performance of the blockchain system. Specifically, both MEC and blockchain are considered as services in the framework, where energy consumption and delay/time to finality (DTF) are the performance metrics for the MEC system and the blockchain system, respectively. We formulate an optimization problem to achieve the optimal trade-off through jointly optimizing user association, data rate allocation, block producer scheduling, and computational resource allocation. To solve the problem, we decouple the optimization variables for efficient algorithm design. In addition, we develop an iterative algorithm for user association and data rate allocation and a bisection algorithm for computing resource allocation. Simulation results show the convergence of the proposed algorithms, and the proposed scheme can achieve the optimal trade-off between energy consumption and DTF.
Mengting Liu, Yinglei Teng, F. Richard Yu, Victor C. M. Leung · 5 authors
Blockchain technology is reshaping the video streaming industry by changing how humans create, distribute and consume videos. Leveraging blockchain technology, some emerging video streaming platforms aim to eliminate the centralized video streaming servers by building peer-to-peer content distribution architectures and cryptocurrency-based payment systems. On these blockchain-based platforms, the source video streams are required to be transcoded into multiple versions to meet heterogeneous user demands, which is a computationally intensive and energy consuming process. Meanwhile, the block size of the blockchain has significant impacts on the performance of blockchain-based video streaming systems. In this article, we propose a novel MEC-enabled transcoding framework for blockchain-based video streaming while an adaptive block size scheme is designed for the underlying blockchains. The system architecture of the proposed framework is presented to enable coordination of different aspects. Then we address the video transcoding and block size issues by using the ADMM method, and smart contract is used to facilitate distributed optimization among non-trusting entities. Simulation results are presented to show the effectiveness of the proposed framework.
Image and Video Quality Assessment
Advanced Steganography and Watermarking Techniques
Mengting Liu, Yinglei Teng, F. Richard Yu, Victor C. M. Leung · 5 authors
The boom of video streaming industry has resulted in the increasing demands for transcoding services from heterogeneous users. Recent advances of blockchain technology allow some startups to realize decentralized collaborative transcoding through device-to-device (D2D) networks, where a group of transcoders are selected to perform transcoding cooperatively. For the blockchain-enabled D2D transcoding systems, it's imperative to jointly design transcoder selection, task scheduling and resource allocation schemes in order to provide efficient and trustworthy transcoding services. In this paper, viewing the involved multi-dimensional complex factors and channel fluctuation, we propose a novel deep reinforcement learning (DRL) based transcoder selection framework for blockchain enabled D2D transcoding systems where both the platform dynamics and channel statistics are captured. To reduce the action space size, we adopt a two-stage decision approach to first select the transcoders through a normal DRL based framework and then obtain the optimal task scheduling, power control, and resource allocation scheme by solving a stochastic optimization problem with the constrained stochastic successive convex approximation (CSSCA) approach. Simulation results show that our proposed framework can achieve high transcoding revenue while meeting the quality of service (QoS) requirements, and it can well handle dynamic cases.
Natkamon Tovanich, Nicolas Heulot, Jean‐Daniel Fekete, Petra Isenberg
We present a systematic review of visual analytics tools used for the analysis of blockchains-related data. The blockchain concept has recently received considerable attention and spurred applications in a variety of domains. We systematically and quantitatively assessed 76 analytics tools that have been proposed in research as well as online by professionals and blockchain enthusiasts. Our classification of these tools distinguishes (1) target blockchains, (2) blockchain data, (3) target audiences, (4) task domains, and (5) visualization types. Furthermore, we look at which aspects of blockchain data have already been explored and point out areas that deserve more investigation in the future.
Yiming Liu, F. Richard Yu, Xi Li, Hong Ji · 5 authors
The blockchain-based video systems are designed to build a decentralized and flexible video ecosystem by enabling a direct interaction among users, video providers (VPs), and service providers. In blockchain-based video systems, the heterogeneous qualities and formats of the video streams usually require massive computational resources to transcode them into different versions and formats to meet distinct requirements of users. However, current blockchains cannot handle massive and heterogeneous video streaming due to limited computing capacity and long transaction times. To deal with this issue, in this paper, leveraging mobile edge computing (MEC) technology, we propose a blockchain-based MEC architecture, where small base stations (SBSs) allocate their computation as well as communication resources for providing video streaming in a distributed and secure manner. Moreover, to improve the operation efficiency, we use a series of smart contracts to enable a self-organized video transcoding and delivery service without a centralized controller. Then, users, SBSs, and VP could adjust their strategies according to the transactional information on blockchain. Moreover, we formulate the video transcoding and delivery problem as a three-stage Stackelberg game. We analyze the sub-game equilibrium in each stage and the interplays of the three-stage game. Last, we propose an iterative algorithm to solve the problem. Simulation results show that the proposed approach could obtain the good performance in terms of average time to finality (TTF), average access delay, and network cost.
Natkamon Tovanich, Nicolas Heulot, Jean‐Daniel Fekete, Petra Isenberg
We contribute a systematic review of online visualizations of the Bitcoin blockchain. Bitcoin is currently the most active cryptocurrency with the largest market share among other cryptocurrencies. It has attracted a large user base and more and more businesses are beginning to accept Bitcoin as payment. While there are still relatively few visualization research papers on Bitcoin, a growing number of online tools visualize data about the Bitcoin blockchain. We provide a first systematic assessment of these online tools to inform future research efforts on making the Bitcoin blockchain more accessible.
The goal of this research is to estimate the data propagation time on the Bitcoin network. Using network coordinates, we estimate the communication latency between computers. Such latency estimation contributes future optimization of data propagation. In this research, we report an experiment on computing the network coordinates. In the current Bitcoin network, it is very difficult to acquire internode delay because the network topology is not available. In this study, we calculate the delay based on our topology estimation and describe the effectiveness of the network coordinates using various topology estimation parameters.
Mengting Liu, F. Richard Yu, Yinglei Teng, Victor C. M. Leung · 5 authors
Blockchain-based video streaming systems aim to build decentralized peer-to-peer networks with flexible monetization mechanisms for video streaming services. On these blockchain-based platforms, video transcoding, which is computationally intensive and time-consuming, is still a major challenge. Meanwhile, the block size of the underlying blockchain has significant impacts on the system performance. Therefore, this paper proposes a novel blockchain-based framework with an adaptive block size for video streaming with mobile edge computing (MEC). First, we design an incentive mechanism to facilitate collaboration among content creators, video transcoders, and consumers. In addition, we present a block size adaptation scheme for blockchain-based video streaming. Moreover, we consider two offloading modes, i.e., offloading to the nearby MEC nodes or a group of device-to-device (D2D) users, to avoid the overload of MEC nodes. Then, we formulate the issues of resource allocation, scheduling of offloading, and adaptive block size as an optimization problem. We employ a low-complexity alternating direction method of the multipliers-based algorithm to solve the problem in a distributed fashion. Simulation results are presented to show the effectiveness of the proposed scheme.
Yiming Liu, F. Richard Yu, Xi Li, Hong Ji · 5 authors
By bringing computing capabilities to the network edge, mobile edge computing (MEC) has emerged as a promising technique to enable low-latency video streaming services. However, due to the rapid growth of the number of devices and the heterogeneous formats of the video streams, the traditionally centralized content delivery schemes are insufficient to provide secure, adaptive video services with low complexity. To achieve a decentralized content market among untruthful parties (e.g., users and operators), in this paper, we propose an effective video transcoding and delivery approach based on MEC and blockchain. In the proposed approach, we envision a set of blockchain-based smart contracts to build an autonomous content delivery market, where all the participants are financially enforced by smart contract terms. Then, users, small base stations (SBSs), and content provider (CP) are able to autonomously adjust their strategies according to the content market statistics. Moreover, we formulate the optimization problem, including resource allocation, determining content price and quality levels of contents, as a three-stage Stackelberg game. We analyze the subgame equilibrium for each stage and the interplays of the three-stage game. Lastly, an iterative algorithm is proposed to obtain the solution. Simulation results are presented to show the effectiveness of the proposed approach.
James Clay, Alexander Hargrave, Ramalingam Sridhar
We investigate the impact of how a cryptocurrency mining system can affect the power consumption of mobile devices. Specifically we look at CoinHive, a cryptocurrency miner and associated mining pool targeting the Monero (XMR) cryptocurrency. CoinHive distributes a JavaScript-based miner to webpages where visitors run the script and provide computing power to the web host's CoinHive account. Ideally, hosting JavaScript-based cryptocurrency miners provides alternatives to using ad-networks as a source of website revenue. While some users may not oppose an energy for advertisement trade-off, it may be less palatable to mobile users concerned with battery life. Our initial studies have revealed that, at a minimum, running the normally distributed JavaScript-based miner increases the power draw of a Samsung Galaxy S4 by about 5 fold. Under certain circumstances, the power draw can increase to eleven-fold. We illustrate these findings by comparing them with various normal use benchmarks and with a variety of different ad-enabled webpages.