A situation-aware cross-platform architecture for ubiquitous game

Multi-player online games (MOGs) are popular in these days. However, contemporary MOGs do not really support ubiquity in the sense that a seamless service across heterogeneous hardware platforms is not provided. This paper presents the architecture of the cross-platform online game, which provides a service to users from heterogeneous platforms and is equipped with a situation-aware capability for enabling the users to seamlessly move between heterogeneous platforms. The experimental results through the prototype implementations show the feasibility of the situation-aware cross-platform game

Requirements Negotiation Using Multi-Criteria Preference Analysis

Many software projects have failed because their requirements were poorly negotiated among stakeholders. Reaching agreements of negotiated requirements among stakeholders who have different concerns, responsibilities, and priorities is quite challenging. Formal (fully-automated) approaches of requirements negotiation require significant efforts of knowledge representation and validation, whereas informal (manual) approaches do not provide systematic methods of requirements negotiation. This paper proposes a novel light-weighted, yet systematic requirements negotiation model, called "Multi-Criteria Preference Analysis Requirements Negotiation (MPARN) " to guide stakeholders to evaluate, negotiate, and agree upon alternatives among stakeholders using multi-criteria preference analysis theory. This eight-step MPARN model was applied to requirements gathered for an industrial-academic repository system. The result showed that the MPARN model assisted stakeholders to have unbiased aspects within a requirements negotiation in a light-weighted way and increase stakeholders ’ levels of cooperation and trust by measuring each stakeholder’s preference and value function explicitly through a step-by-step process

Q-RTOP: Quantum-Secure Random Transaction Ordering Protocol for Mitigating Maximal Extractable Value Attacks in Blockchains With a Priority Gas-Fee Policy

Public blockchains, such as Ethereum, rely on decentralized networks of peer-to-peer nodes known as validators or miners to verify all transactions and create new valid blocks. These validators can prioritize transactions, primarily based on high gas fees, allowing miners to maximize their block rewards, a concept referred to as maximal extractable value (MEV). However, MEV is vulnerable to front-running, back-running, and sandwich attacks (FBSAs), and is exploited by malicious nodes and bots to manipulate users’ valuable transactions. These malicious activities adversely impact the Blockchain’s scalability, transparency, and security. Flashbots, as one of the solutions, introduces centralization since all nodes have to forward all blocks to the central node. To address these issues, we have designed a new Blockchain transaction ordering protocol called Quantum Random Transaction Ordering Protocol (Q-RTOP). The proposed protocol operates on top of the existing Blockchain transaction ordering mechanism. However, instead of allowing validators to select transactions based on high gas fees, decentralized nodes running Q-RTOP securely randomize all transactions and then forward them to the validators, which proceed with the block validation without any change. Our protocol primarily focuses on randomizing transactions before being processed by the validators by utilizing a quantum random generator as a secure source of randomness. The final results demonstrated that Q-RTOP effectively secured user transactions and randomized 8192 transactions within 25 milliseconds

Decentralized Global Copyright System Based on Consortium Blockchain With Proof of Authority

Conventional copyright systems are governed nationally, and there is no global ledger for storing copyright data. Due to the lack of a global copyright monitoring system, it is difficult to provide cross-border copyright protection. In this paper, we propose a novel decentralized copyright system based on a consortium blockchain, which ensures cross-border copyright protection of individuals’ digital content and solves existing challenges in international copyright management. The proposed system enables a synchronized platform to register and trade copyright globally without using a global cloud. Individual countries receive membership from a copyright federation and participate in block creation by executing the energy-efficient proof of authority consensus algorithm. These countries are regarded as the authorities of the platform. They validate transactions conducted by users and store them in the blockchain. Anyone, either registered or unregistered, can investigate a copyrighted work, but only registered users can make transactions. A token-based payment method is also proposed for paying copyright charges (i.e., transaction fees) to authorities through the federation. A prototype of the system was implemented, and its performance was evaluated. This paper provides direction and guidance towards international copyright management

Adaptive Kinetic Scrolling: Kinetic Scrolling for Large Datasets on Mobile Devices

Scrolling is a frequently used Graphical User Interface widget that enables users to interact with a large amount of data using a limited viewport. However, if excessive data is included in the scroll, users are required to spend a substantial amount of time and effort to find the required information. In this paper, we present adaptive kinetic scrolling (AKS), a technique based on kinetic scrolling by which users can access target information more rapidly on mobile devices. Based on the user’s behavior, AKS detects situations when the user intends to access certain information that may be distant from the current viewport. At this point, AKS amplifies the speed of kinetic scrolling. Furthermore, the scrolling speed adapts according to the size of the remaining data to be scrolled. The more data that the scrolling widget contains, the more rapidly it scrolls so that the user can quickly reach the target. Kinetic scrolling is frequently used in scrolling widgets, and with AKS, users can save time and energy wasted on repetitive meaningless scrolling. We conducted a user study and verified that the proposed scrolling technique enables users to access target information more rapidly, particularly when there is a large dataset to navigate

Abstract

Recently wireless web services have been rapidly growing as a new way of information service. As the wireless Internet access grows, so do e-commerce opportunities through the wireless web services. Wireless Internet access has inherent limitations since most handheld devices have much less display and means of operations. This imposes a particular problem to the design of mobile information services in terms of information and service navigation. In this paper, a novel approach called SmartClick is presented to achieve user-centered wireless web services. SmartClick enables users to explicitly express their intentions or preferences with minimal clicks (user interaction). SmartClick with a middleware support provides users a way to get the desired web contents more efficiently and easily

Multitier Web System Reliability: Identifying Causative Metrics and Analyzing Performance Anomaly Using a Regression Model

With the development of the Internet and communication technologies, the types of services provided by multitier Web systems are becoming more diverse and complex compared to those of the past. Ensuring a continuous availability of business services is crucial for multitier Web system providers, as service performance issues immediately affect customer experience and satisfaction. Large companies attempt to monitor the system performance indicator (SPI) that summarizes the status of multitier Web systems to detect performance anomalies at an early stage. However, the current anomaly detection methods are designed to monitor a single specific SPI. Moreover, the existing approaches consider performance anomaly detection and its root cause analysis separately, thereby aggravating the burden of resolving the performance anomaly. To support the system provider in diagnosing the performance anomaly, we propose an advanced causative metric analysis (ACMA) framework. First, we draw out 191 performance metrics (PMs) closely related to the target SPI. Among these PMs, the ACMA determines 62 vital PMs that have the most influence on the variance of the target SPI using several statistical methods. Then, we implement a performance anomaly detection model to identify the causative metrics (CMs) between the vital PMs using random forest regression. Even if the target SPI changes, our detection model does not require any change in its model structure and can derive closely related PMs of the target SPI. Based on our experiments, wherein we applied the ACMA to the business services in an enterprise system, we observed that the proposed ACMA could correctly detect various performance anomalies and their CMs