查看更多>>摘要：With the development of the era of big data, the demand for data sharing and usage is increasing, especially in the era of the internet of things, thus putting forward a keen demand for data exchanging and data trading. However, the existing data exchanging and trading platforms are usually centralised and users have to trust platforms. This paper proposes a secure and fair exchanging and trading protocol based on blockchain and smart contracts, especially, self-governance without relying on centralised trust. By using the protocol, it can guarantee fairness to defend against trade cheating, and security for data confidentiality. It can also guarantee efficiency by transferring data links instead of data between data owners and data buyers. The extensive analysis justified that the proposed scheme can facilitate self-exchanging and self-trading for big data in a secure, fair and efficient manner.
查看更多>>摘要：The arrival of the big data era introduces new necessities for accommodating data access and analysis by organisations. The evolution of data is three-fold, increase in volume, variety, and complexity. The majority of data nowadays is generated in the cloud. Cloud data warehouses profit from the benefits of the cloud by facilitating the integration of data in the cloud. A data warehouse is developed in this paper, which supports both spatial and temporal dimensions. The research focuses on proposing a general design for spatiobitemporal objects implemented by nested dimension tables using the starnest schema approach. Experimental results reflect that the parallel processing of such data on the cloud can process OLAP queries efficiently. Furthermore, by increasing the number of computational nodes results in a significant reduction of queries' time execution. The feasibility, scalability, and utility of the proposed technique for querying spatiotemporal data are demonstrated.
Carlos MeloJean AraujoJamilson DantasPaulo Pereira...
211-223页
查看更多>>摘要：Cloud computing has become the leading paradigm for internet service provisioning, attracting more adopters daily. Service providers face high costs related to acquisition and implementation, making outsourced maintenance a cost-effective alternative, especially for small infrastructures. This paper evaluates infrastructure reliability and the impact of outsourced maintenance on private cloud availability, with a focus on blockchain as a service. By modelling service and maintenance routines, the findings are applicable to various cloud services. The study assesses maintenance strategies - reactive, preventive, and self-healing - within Service Level Agreements. Results indicate that preventive and self-healing maintenance offer a better cost-benefit balance compared to traditional reactive methods. However, the optimal approach depends on the provider's available resources. This research helps small-scale service providers choose cost-efficient maintenance strategies while ensuring high availability.
查看更多>>摘要：Requirement analysis is critical step before the starting of software development. There are two kinds of software requirement in software development: (1) functional requirement and (2) non-functional requirement. Visibility of Functional Requirement (FR) is very much clear in software development, but Non-Functional Requirement (NFR) is hidden in nature so much less research has been done in the area of NFR. Even though it is hidden requirement it still plays a very important role in software development because it specifies quality and constraints of the system. To automate the process of requirement classification in software development, Machine Learning (ML) techniques are used. This paper presents the exhaustive experimental analysis of traditional ML techniques used for classification of NFR. In this experimental analysis Multinomial Naive Bayes (MNB), Logistic Regression (LR), Support Vector Machine with Stochastic Gradient Descent (SVM-SGD) and K-Nearest Neighbours (KNN) algorithms are analysed in terms of accuracy, recall, precision, and F1-Score to classify the NFR. As the data set to perform this experimental analysis, the PROMISE repository is used. In this work results show that SVM-SGD outperforms all the ML techniques by giving the F1-Score 00.92, Recall 00.92, Precision 00.93 and Accuracy 00.92.
查看更多>>摘要：In this study, we implemented a virtual traditional craft sharing system using MR technology in order to realise a highly realistic experience of traditional crafts and space sharing by multiple users in real space. This system consists of six functions: arrangement, delete, exchange, colour change, arrangement auxiliary and sharing of MR traditional craft object. The arrangement auxiliary function automatically arranges the MR traditional craft object in the real space by calculating its position, orientation and size. In addition, the sharing function realises sharing of MR traditional craft object among multiple users. Moreover, we conducted a questionnaire survey on 30 subjects to evaluate the MR traditional crafts sharing system. We obtained high evaluations of the system's operability, functionality, effectiveness and applicability. However, there were still issues related to the sense of immersion of our proposed system probably because the original texture of traditional crafts cannot be reproduced.
查看更多>>摘要：We are surrounded by many smart applications that make human life efficient. The general concept of IoT applications involves communication between devices. To make our smart environment secure, authentication is the most important requirement to be achieved to avoid unwanted attacks. Cryptographic schemes used currently in such IoT devices are public-key cryptographic primitives that are vulnerable to future quantum attacks. Quantum approaches derived by Shor and Grover will break the public-key primitives with square root and cube root speedups. Hence, there is a need to develop a successful and efficient signature scheme to authenticate such devices. Post-quantum cryptographic approaches are based on hard mathematical problems which are difficult to break by future attacks. Amongst all these post-quantum signature approaches, hash-based post-quantum signatures incorporate existing hash algorithms to achieve the required security level. This paper summarises stateful hash-based post-quantum signature schemes that can be implemented on constrained devices for IoT applications.
查看更多>>摘要：Applications can take advantage of virtual computation services independently of heterogeneity and locations of servers by using virtual machines in clusters. Here, a virtual machine on an energy-efficient host server has to be selected to perform an application process. In this paper, we newly propose a Simple Monotonically Increasing (SIM) estimation algorithm to estimate the energy consumption of a server to perform application processes and the total execution time of the processes on a server. We also propose an SMI Migration (SMIM) algorithm to make a virtual machine migrate from a host server to a guest server to reduce the total energy consumption of the servers by estimating the energy consumption in the SMI algorithm. In the evaluation, we show the energy consumption of servers in a cluster is reduced in the SMIM algorithm by at least 5% compared with other algorithms.
查看更多>>摘要：Cloud computing technology provides various computing resources on demand to users on pay per use basis. The technology fails in terms of its usage due to confidentiality and privacy issues. Access control mechanisms are the tools to prevent unauthorized access to remotely stored data. Cipher Text Policy Attribute-based Encryption (CPABE) is a widely used tool for facilitating authorised users to access the remotely stored encrypted data with fine-grained access control. In the proposed model FIAC, access control mechanism is embedded in cloud-based application. The major contribution of this work is the design of three algorithms all of which are attribute based: Key Generation algorithm, and Encryption and Decryption algorithms. Only authorised users can view them to take appropriate action plans. To enhance security of the cloud-based monitoring system, we have embedded a security scheme, all of which are attribute based. Further, the computation time of the model is found to be encouraging so that it can be used in low power devices. The experimental outcomes establish the usability of our model.
查看更多>>摘要：Data clustering is a fundamental task in the field of machine learning which involves the partitioning of the datasets into meaningful groups. The traditional clustering algorithms often struggle with issues such as initial centroid sensitivity, slow convergence, and local optima trap. On the other side, meta-heuristic algorithms consist of innovative paradigms to handle these issues. Hence, this work introduces a new meta-heuristic algorithm, called transient search optimisation (TSO) to alleviate the issues of traditional clustering algorithms. Further, some enhancements are included in TSO algorithm to generate more optimal results. These improvements aim to make TSO more reliable for data clustering problems. The efficiency of the TSO is evaluated over benchmark datasets and results are compared using intra cluster distance, accuracy rate and detection rate parameters. The average accuracy rate and average detection rate of the proposed TSO algorithm are 6.94% and 6.48% higher respectively as compared to other algorithms.
NETL
NSTL