Computer Internet Research Articles

The Volatility Spillover in Metaverse Token Market: TVP-VAR Model Application

In this study, the volatility spillover between metaverse tokens is investigated to guide investors. In the research, price data of Decentraland, StarLink, Axie Infinity, Radio Caca, The Sandbox, Internet Computer, My Neighbor Alice and Enjin Token, for the period 12.14.2021-10.22.2023 analyzes with the time-varying parameter vector autoregressive (TVP-VAR) model developed by Antonakakis et al. (2019). As a result of the research, it determine that Radio Caca and Axie Infinity only receive volatility; My Neighbor Alice and Enjin Token only spread volatility; StarLink, Decentraland and Internet Computer are metaverse tokens that both receive and spread volatility.

Edge Computing and Analytics for IoT Devices: Enhancing Real-Time Decision Making in Smart Environments

This article presents a comprehensive analysis of edge computing and analytics for Internet of Things (IoT) devices, addressing the growing need for real-time processing and reduced latency in IoT applications. We explore the evolution of IoT architectures, from cloud-centric models to edge-enabled systems, and examine the key components and data flows in edge computing environments. Through a detailed comparison of cloud and edge processing, we demonstrate significant latency reductions across various IoT scenarios, with improvements from hundreds of milliseconds to mere milliseconds. The article delves into crucial aspects of data management in edge computing, including local versus cloud processing trade-offs, data synchronization strategies, and privacy considerations. A case study of an edge analytics pipeline in a smart factory setting showcases practical implementations, revealing substantial improvements in anomaly detection speed, bandwidth utilization, and overall system efficiency. The case study achieved a 92.5% reduction in anomaly detection latency and an 85% decrease in bandwidth usage. Finally, we discuss ongoing challenges and future directions in edge computing, including scalability issues, standardization efforts, and the integration of emerging technologies such as 5G and AI accelerators. This article contributes to the growing body of knowledge on edge computing in IoT, offering insights into its transformative potential for creating more responsive and intelligent systems across diverse applications.

RIS-Enabled Integrated Sensing, Computing, and Communication for Internet of Robotic Things

RIS-Enabled Integrated Sensing, Computing, and Communication for Internet of Robotic Things

STAR-RIS-Aided Integrated Sensing, Computing, and Communication for Internet of Robotic Things

STAR-RIS-Aided Integrated Sensing, Computing, and Communication for Internet of Robotic Things

Self-Adaptive Evolutionary Multitasking Algorithm for Mobile Edge Computing in Internet of Things

Self-Adaptive Evolutionary Multitasking Algorithm for Mobile Edge Computing in Internet of Things

SDN-based security low-latency data storage and distribution scheme for industrial Internet of Things

For the problem that massive data and cloud computing in the industrial Internet of Things cannot meet the requirements of low latency, a cloud hybrid network architecture is proposed. In the single user scenario, RS coding is used to realize data redundancy, and the security evaluation method is put forward on this basis. By using the ant colony algorithm, the data transmission delay and security objective function are established to obtain the best allocation scheme. In the multi-user scenario, the SD-CFIIoT architecture is constructed by combining SDN and fog computing technology. The optimal solution is found by applying the ant colony algorithm to solve the objective function of the data transmission delay. Simulation results show that when the security constraint is 0.9, the data transmission delay of RS is 5.04 s, which is 0.18 s less than LDPC; 0.19 s less than MBR. When the safety constraint is 0.9, the delay of the cloud mixed structure is 5.82 seconds; 1.53 seconds less than the cloud core structure and 1.20 seconds less than the fog core structure. When the data volume reached 80 MB, the delay of SD-CFIIoT was 2.20 s, 6.61 s lower than the fog structure and 15.80 s lower than the cloud structure. The simulation results prove the effectiveness of the proposed scheme, which can ensure data security while realizing low delay data transmission, improve the efficiency of the Internet of Things, and then improve the industrial production efficiency. This has a certain positive significance to the industrial modernization and intelligent development.

Integrating Communication, Sensing and Computing in Satellite Internet of Things: Challenges and Opportunities

Integrating Communication, Sensing and Computing in Satellite Internet of Things: Challenges and Opportunities

NFT – MARKETPLACE USING ICP BLOCKCHAIN AND CUSTOM TOKENS

The Cutting-Edge ICP Blockchain Marketplace is a groundbreaking platform revolutionizing NFT trading through the innovative utilization of the Internet Computer Protocol (ICP) blockchain. Our marketplace provides a secure, transparent, and tamper-proof environment for buying, selling, and trading NFTs. With a user-friendly React frontend, users can seamlessly navigate through a diverse collection of NFTs, including digital artwork, collectibles, virtual real estate, and domain names. Simplified trading processes empower users to list NFTs, set prices, and engage in secure transactions effortlessly. Curated collections feature exceptional NFT artworks and rare collectibles, fostering creativity and passion within our community. Through the immutability and transparency of blockchain technology, our marketplace ensures the authenticity and provenance of each NFT, establishing a trusted ecosystem for users to explore and exchange digital assets with confidence. Key Words: NFT Marketplace, digital assets, ICP Blockchain

Adaptive Resource Allocation for Mobile Edge Computing in Internet of Vehicles: A Deep Reinforcement Learning Approach

Adaptive Resource Allocation for Mobile Edge Computing in Internet of Vehicles: A Deep Reinforcement Learning Approach

Enhancing Medical Data Analysis with Federated Learning in the Internet of Medical Things

The Internet of Things refers to physical items, which are equipped with software, sensors, computing power, and other technologies, and that communicate with other electronic devices and systems over communication networks or the Internet. A collection of medical devices and software programmes known as the Internet of Medical Things (IoMT) link to healthcare networks via internet computing. Machine-to-machine communication, which is the foundation of IoMT, is made feasible by medical equipment that includes Wi-Fi. IoMT devices have the ability to analyse and store collected data by connecting to cloud services. IoMT is a different moniker for IoT in healthcare. Since data is transferred via the internet and the IoMT creates a lot of data, privacy concerns are important. The vast volume of data produced by IoMT devices calls for big data processing, and federated learning tackles privacy issues as a way to overcome these difficulties. The big data health care framework for IoMT is discussed in this article. It is built on federated learning.

Pengembangan Sistem Pemantauan Potensi Banjir Online di Desa Mangun Jaya Kabupaten Bekasi

Mangun Jaya Village is an area affected by flooding every year. There are at least two characteristics that cause flooding, namely local rain with high rainfall and the overflow of the Bekasi River. Kali Bekasi is a river located in the village of Mangun Jaya, South Tambun sub-district, Bekasi Regency, which has a large current, especially when it rains. In this community service activity, the team from Bhayangkara University, Jakarta Raya, has succeeded in developing a potential flood monitoring system based on IoT technology as a disaster mitigation measure. This system consists of a sensor device that can measure the height of the river surface and rainfall where these physical data are sent to the Internet. Access to this potential flood data can be done in real time and remotely using mobile devices and internet computers. This system has also been tested in the field by installing sensors on the edge of the Bekasi River where an average of 1429 data is collected daily. The percentage of data loss is 0.75%. This proves that the system can be used as a preventive effort in dealing with potential flooding in South Tambun Regency.

UAV-Enabled Integrated Sensing, Computing, and Communication for Internet of Things: Joint Resource Allocation and Trajectory Design

UAV-Enabled Integrated Sensing, Computing, and Communication for Internet of Things: Joint Resource Allocation and Trajectory Design

ADTO: A Trust Active Detecting-based Task Offloading Scheme in Edge Computing for Internet of Things

In edge computing, Internet of Things devices with weak computing power offload tasks to nearby edge servers for execution, so the task completion time can be reduced and delay-sensitive tasks can be facilitated. However, if the task is offloaded to malicious edge servers, then the system will suffer losses. Therefore, it is significant to identify the trusted edge servers and offload tasks to trusted edge servers, which can improve the performance of edge computing. However, it is still challenging. In this article, a trust Active Detecting-based Task Offloading (ADTO) scheme is proposed to maximize revenue in edge computing. The main innovation points of our work are as follows: (a) The ADTO scheme innovatively proposes a method to actively get trust by trust detection. This method offloads microtasks to edge servers whose trust needs to be identified, and then quickly identifies the trust of edge servers according to the completion of tasks by edge servers. Based on the identification of the trust, tasks can be offloaded to trusted edge servers, to improve the success rate of tasks. (b) Although the trust of edge servers can be identified by our detection, it needs to pay a price. Therefore, to maximize system revenue, searching the most suitable number of trusted edge servers for various conditions is transformed into an optimization problem. Finally, theoretical and experimental analysis shows the effectiveness of the proposed strategy, which can effectively identify the trusted and untrusted edge servers. The task offloading strategy based on trust detection proposed in this article greatly improves the success rate of tasks, compared with the strategy without trust detection, the task success rate is increased by 40.27%, and there is a significant increase in revenue, which fully demonstrates the effectiveness of the strategy.

Bacterial Communications and Computing in Internet of Everything (IoE)

Bacterial Communications and Computing in Internet of Everything (IoE)

Exploring the Influences of Metaverse on Education Based on the Neutrosophic Appraiser Model

The growth of information technology over the course of human history has resulted in an update to traditional schooling. The Metaverse is an innovative concept for social work that incorporates many different types of technology. These technologies include big data, interactivity, artificial intelligence (AI), game design, internet computing, the Internet of Things (IoTs), and blockchain. It is reasonable to anticipate that the utilization of Metaverse will contribute to the advancement of educational practices. However, the structures of the Metaverse in educational settings are not yet developed to the point where they are ready for use. When it comes to schooling and the Metaverse, there are a lot of questions that need answering. Considering this, the purpose of this research is to provide a comprehensive analysis of the use of Metaverse in educational settings. This article provides an in-depth study of the use of the Metaverse in education, with a particular emphasis on contemporary technology, obstacles, and possibilities, as well as potential future paths. First, we provide a concise introduction to the use of the Metaverse in education, as well as an explanation of the rationale for including it. After that, we look at a few crucial aspects of the Metaverse's use in the educational sector, such as the individual's capacity to create their own personalized learning and teaching environments. The next step is appraising determined alternatives and criteria which related to utilize metaverse in education environment. Hence, entropy is supported with SingleValue Neutrosophic Sets (SVNSs) to analyze and valuation of criteria’s weights. Then Combined Compromise Solution (CoCoSo) is utilized under authority of SVNSs to rank alternatives related to deploying metaverse in educations. The results demonstrated that alternative 1 is the optimal otherwise alternative 3 is worst.

A Trust-Aware and Authentication-Based Collaborative Method for Resource Management of Cloud-Edge Computing in Social Internet of Things

The Social Internet of Things (S-IoT) paradigm is focused on topic of the Internet of Things (IoT), which accelerates the object issues by working with the concept of social networks. Searching and finding a new object in the community are considered to manage the number of friends and complex relationships between them and affect the ability to navigate at the cloud-edge layer, and resources, such as battery lifetime of S-IoT devices and energy resources, are important challenges in this field. In the processing of social messages of remote devices, increasing the battery life of devices that require such requirements plays the most important role. In this research, a collaboration scenario is presented to consider object attributes, friend’s functions and intelligent friend selection among objects for group messaging. First, a general reference model is designed and presented to select a friend to access group message remote processing services and minimize cloud-edge resources. The simulation results show that, for the correct communication of friends at the edge of the network and in each service discovery, according to the length of the path in the network, it is possible to establish stable communication and make better service with the least possible. The results show that if we want to develop a method for friendship between objects in communication in cloud computing, the proposed method can greatly improve the effectiveness of providing reliable message processing types.

Call for Papers: IEEE Internet Computing Special Issue on Civilizing and Humanizing AI

Call for Papers: IEEE Internet Computing Special Issue on Civilizing and Humanizing AI

Voting on ICP Blockchain: A Decentralized Web3 Approach

In this comprehensive exploration, our paper delves into the intricate implementation of robust authentication and transaction management within the realm of secure voting systems leveraging blockchain technology. Our innovative project stands as a testament to the commitment to privacy and integrity, safeguarding voter interactions through the adept application of advanced cryptographic techniques—all achieved without reliance on a centralized authority. The multifaceted capabilities of blockchain technology are showcased through the seamless facilitation of secure voting processes and the optimization of transaction transfers, collectively contributing to an ecosystem characterized by enhanced security, transparency, and efficiency. Beyond the immediate applications, our study uncovers profound insights into the transformative potential of blockchain within the voting sector, redefining conventional paradigms by introducing unparalleled security measures and transparency to the intricate dynamics of voter interactions. This research not only underscores the feasibility of blockchain in addressing the unique challenges of voting systems but also offers a roadmap for leveraging its capabilities to create a more secure, accountable, and streamlined electoral ecosystem. The paper thus serves as a pioneering contribution, illuminating the path towards a future where blockchain technologies play a pivotal role in shaping the voting landscape. Index Terms: Internet Computer Blockchain (ICP), Blockchain Voting, Decentralized, Rust, Cryptography, SHA-256 algorithm

A Novel Hybrid Decision Making Framework for Comparing Market Performance of Metaverse Crypto Assets

With proliferation of smartphone usage and rapidly increasing internet access, the financial sectors has been witnessing a transformational change in the last few years, leading to the digital economy. The cryptocurrencies (digital assets) and the metaverse assets that use blockchain technology extensively have emerged as an attractive investment option to the investors. The review of the extant literature shows a scantiness of research in comparing the performance of metaverse crypto assets based on market indicators. In this regard, the current work aims to provide a framework to compare the metaverse crypto assets based on their market performance. To this end, the present paper proposes a novel hybrid framework such as Logarithmic Percentage Change driven Compromise Solution based Appraisal (LOPCCSA). To compare the alternatives the variables like return, momentum of the daily closing price, market capitalization, trading volume and risk (in terms of historical volatility realized over the study period 2022). From the result we observe that the momentum of the closing prices and volatility of the price movements hold the higher importance as derived by calculation of objective weights. Theta Network (A10) comes out as the top performer ahead of ApeCoin (A1) or MANA (A3) or Internet Computer (A6). The comparison of the results obtained by LOPCCSA with other MCDM models show considerable consistency. The sensitivity analysis indicates that LOPCCSA provides a stable solution. The present paper is a distinct attempt that shall attract the decision makers and investors to carry out a deeper and comprehensive analysis of the metaverse crypto assets in near future.

Integrating Edge Computing and Software Defined Networking in Internet of Things: A Systematic Review

The Internet of Things (IoT) has transformed our interaction with the world by connecting devices, sensors, and systems to the Internet, enabling real-time monitoring, control, and automation in various applications such as smart cities, healthcare, transportation, homes, and grids. However, challenges related to latency, privacy, and bandwidth have arisen due to the massive influx of data generated by IoT devices and the limitations of traditional cloud-based architectures. Moreover, network management, interoperability, security, and scalability issues have emerged due to the rapid growth and heterogeneous nature of IoT devices. To overcome such problems, researchers proposed a new architecture called Software Defined Networking for Edge Computing in the Internet of Things (SDN-EC-IoT), which combines Edge Computing for the Internet of Things (EC-IoT) and Software Defined Internet of Things (SDIoT). Although researchers have studied EC-IoT and SDIoT as individual architectures, they have not yet addressed the combination of both, creating a significant gap in our understanding of SDN-EC-IoT. This paper aims to fill this gap by presenting a comprehensive review of how the SDN-EC-IoT paradigm can solve IoT challenges. To achieve this goal, this study conducted a literature review covering 74 articles published between 2019 and 2023. Finally, this paper identifies future research directions for SDN-EC-IoT, including the development of interoperability platforms, scalable architectures, low latency and Quality of Service (QoS) guarantees, efficient handling of big data, enhanced security and privacy, optimized energy consumption, resource-aware task offloading, and incorporation of machine learning.