| 1. |
- Albshri, Adel, et al.
(author)
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A conceptual architecture for simulating blockchain-based IoT ecosystems
- 2023
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In: Journal of Cloud Computing. - : Springer Nature. - 2192-113X. ; 12
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Journal article (peer-reviewed)abstract
- Recently, the convergence between Blockchain and IoT has been appealing in many domains including, but not limited to, healthcare, supply chain, agriculture, and telecommunication. Both Blockchain and IoT are sophisticated technologies whose feasibility and performance in large-scale environments are difficult to evaluate. Consequently, a trustworthy Blockchain-based IoT simulator presents an alternative to costly and complicated actual implementation. Our primary analysis finds that there has not been so far a satisfactory simulator for the creation and assessment of blockchain-based IoT applications, which is the principal impetus for our effort. Therefore, this study gathers the thoughts of experts about the development of a simulation environment for blockchain-based IoT applications. To do this, we conducted two different investigations. First, a questionnaire is created to determine whether the development of such a simulator would be of substantial use. Second, interviews are conducted to obtain participants’ opinions on the most pressing challenges they encounter with blockchain-based IoT applications. The outcome is a conceptual architecture for simulating blockchain-based IoT applications that we evaluate using two research methods; a questionnaire and a focus group with experts. All in all, we find that the proposed architecture is generally well-received due to its comprehensive range of key features and capabilities for blockchain-based IoT purposes.
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| 2. |
- Alzubaidi, Ali, et al.
(author)
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A blockchain-based SLA monitoring and compliance assessment for IoT ecosystems
- 2023
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In: Journal of Cloud Computing. - : Springer Nature. - 2192-113X. ; 12
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Journal article (peer-reviewed)abstract
- A Service Level Agreement (SLA) establishes the trustworthiness of service providers and consumers in several domains; including the Internet of Things (IoT). Given the proliferation of Blockchain technology, we find it compelling to reconsider the assumption of trust and centralised governance typically practised in SLA management including monitoring, compliance assessment, and penalty enforcement. Therefore, we argue that, such critical tasks should be operated by blockchain-based smart contracts in a non-repudiable manner beyond the influence of any SLA party. This paper envisions an IoT scenario wherein a firefighting station outsources end-to-end IoT operations to a specialised service provider. The contractual relationship between them is governed by an SLA which stipulates a set of quality requirements and violation consequences. The main contribution of this paper lies in designing, deploying and empirically experimenting a novel blockchain-based SLA monitoring and compliance assessment framework in the context of IoT. This is done by utilising Hyperledger Fabric (HLF), an enterprise-grade blockchain technology. Our work highlights a set of considerations and best practice at two sides, the IoT application monitoring-side and the blockchain-side. Moreover, it experimentally validates the reliability of the proposed monitoring approach, which collects relevant metrics from each IoT component and examines them against the quality requirements stated in the SLA. Finally, we propose a novel design for smart contracts at the blockchain-side, analyse and benchmark the performance, and demonstrate that the new design proves to successfully handle Multiversion Concurrency Control (MVCC) conflicts typically encountered in blockchain applications, while maintaining sound throughput and latency.
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| 3. |
- Armstrong, Django, et al.
(author)
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Contextualization : dynamic configuration of virtual machines
- 2015
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 4:17
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Journal article (peer-reviewed)abstract
- New VM instances are created from static templates that contain the basic configuration of the VM to achieve elasticity with regards to capacity. Instance specific settings can be injected into the VM during the deployment phase through means of contextualization. So far this is limited to a single data source and data remains static throughout the lifecycle of the VM.We present a layered approach to contextualization that supports different classes of contextualization data available from several sources. The settings are made available to the VM through virtual devices. Inside each VM data from different classes are layered on top of each other to create a unified file hierarchy.Context data can be modified during runtime by updating the contents of the virtual devices, making our approach the first contextualization approach to natively support recontextualization. Recontextualization enables runtime reconfiguration of an executing service and can act as a trigger and key enabler of self-* techniques. This trigger provides a service with a mechanism to adapt or optimize itself in response to a changing environment. The runtime reconfiguration using recontextualization and its potential gains are illustrated in an example with a distributed file system, demonstrating the feasibility of our approach.
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| 4. |
- Elrawy, Mohamed Faisal, et al.
(author)
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Intrusion detection systems for IoT-based smart environments : a survey
- 2018
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 7:21, s. 1-20
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Journal article (peer-reviewed)abstract
- One of the goals of smart environments is to improve the quality of human life in terms of comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a technology for building smart environments. Security and privacy are considered key issues in any real-world smart environment based on the IoT model. The security vulnerabilities in IoT-based systems create security threats that affect smart environment applications. Thus, there is a crucial need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. This article presents a comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms. This article also provides deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT architecture. This work demonstrates that despite previous studies regarding the design and implementation of IDSs for the IoT paradigm, developing efficient, reliable and robust IDSs for IoT-based smart environments is still a crucial task. Key considerations for the development of such IDSs are introduced as a future outlook at the end of this survey.
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| 5. |
- Hai, Tao, et al.
(author)
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Enhanced security using multiple paths routine scheme in cloud-MANETs
- 2023
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 12:1
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Journal article (peer-reviewed)abstract
- Cloud Mobile Ad-hoc Networks (Cloud-MANETs) is a framework that can access and deliver cloud services to MANET users through their smart devices. MANETs is a pool of self-organized mobile gadgets that can communicate with each other with no support from a central authority or infrastructure. The main advantage of MANETs is its ability to manage mobility while data communication between different users in the system occurs. In MANETs, clustering is an active technique used to manage mobile nodes. The security of MANETs is a key aspect for the fundamental functionality of the network. Addressing the security-related problems ensures that the confidentiality and integrity of the data transmission is secure. MANETs are highly prone to attacks because of their properties.In clustering schemes, the network is broken down to sub-networks called clusters. These clusters can have overlapping nodes or be disjointed. An enhanced node referred to asthe Cluster Head (CH) is chosen from each set to overseetasks related to routing. It decreases the member nodes’ overhead and improvesthe performance of the system. The relationship between the nodes and CH may vary randomly, leading to re-associations and re-clustering in a MANET that is clustered. An efficient and effective routing protocol is required to allow networking and to find the most suitable paths between the nodes. The networking must be spontaneous, infrastructure-less, and provide end-to-end interactions. The aim of routing is the provision of maximum network load distribution and robust networks. This study focused on the creation of a maximal route between a pair of nodes, and to ensure the appropriate and accurate delivery of the packet. The proposed solution ensured that routing can be carried out with the lowest bandwidth consumption. Compared to existing protocols, the proposed solution had a control overhead of 24, packet delivery ratio of 81, the lowest average end-to-end delay of 6, and an improved throughput of 80,000, thereby enhancing the output of the network. Our result shows that multipath routing enables the network to identify alternate paths connecting the destination and source. Routing is required to conserve energy and for optimum bandwidth utilization.
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| 6. |
- Hai, Tao, et al.
(author)
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Task scheduling in cloud environment: optimization, security prioritization and processor selection schemes
- 2023
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 12
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Journal article (peer-reviewed)abstract
- Cloud computing is an extremely important infrastructure used to perform tasks over processing units. Despite its numerous benefits, a cloud platform has several challenges preventing it from carrying out an efficient workflow submission. One of these is linked to task scheduling. An optimization problem related to this is the maximal determination of cloud computing scheduling criteria. Existing methods have been unable to find the quality of service (QoS) limits of users- like meeting the economic restrictions and reduction of the makespan. Of all these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm produces the maximum outcomes for scheduling tasks in a heterogeneous environment in a reduced time. Reviewed literature proves that HEFT is efficient in terms of execution time and quality of schedule. The HEFT algorithm makes use of average communication and computation costs as weights in the DAG. In some cases, however, the average cost of computation and selecting the first empty slot may not be enough for a good solution to be produced. In this paper, we propose different HEFT algorithm versions altered to produce improved results. In the first stage (rank generation), we execute several methodologies to calculate the ranks, and in the second stage, we alter how the empty slots are selected for the task scheduling. These alterations do not add any cost to the primary HEFT algorithm, and reduce the makespan of the virtual machines’ workflow submissions. Our findings suggest that the altered versions of the HEFT algorithm have a better performance than the basic HEFT algorithm regarding decreased schedule length of the workflow problems.
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| 7. |
- Hedayati, Soudabeh, et al.
(author)
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MapReduce scheduling algorithms in Hadoop : a systematic study
- 2023
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 12
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Journal article (peer-reviewed)abstract
- Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process that data. MapReduce is a parallel computing framework for processing large amounts of data on clusters. Scheduling is one of the most critical aspects of MapReduce. Scheduling in MapReduce is critical because it can have a significant impact on the performance and efficiency of the overall system. The goal of scheduling is to improve performance, minimize response times, and utilize resources efficiently. A systematic study of the existing scheduling algorithms is provided in this paper. Also, we provide a new classification of such schedulers and a review of each category. In addition, scheduling algorithms have been examined in terms of their main ideas, main objectives, advantages, and disadvantages.
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| 8. |
- Kotouza, MT, et al.
(author)
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A dockerized framework for hierarchical frequency-based document clustering on cloud computing infrastructures
- 2020
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In: JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS. - : Springer Science and Business Media LLC. ; 9:1
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Journal article (other academic/artistic)abstract
- Scalable big data analysis frameworks are of paramount importance in the modern web society, which is characterized by a huge number of resources, including electronic text documents. Document clustering is an important field in text mining and is commonly used for document organization, browsing, summarization and classification. Hierarchical clustering methods construct a hierarchy structure that, combined with the produced clusters, can be useful in managing documents, thus making the browsing and navigation process easier and quicker, and providing only relevant information to the users’ queries by leveraging the structure relationships. Nevertheless, the high computational cost and memory usage of baseline hierarchical clustering algorithms render them inappropriate for the vast number of documents that must be handled daily. In this paper, we propose a new scalable hierarchical clustering framework, which uses the frequency of the topics in the documents to overcome these limitations. Our work consists of a binary tree construction algorithm that creates a hierarchy of the documents using three metrics (Identity, Entropy, Bin Similarity), and a branch breaking algorithm which composes the final clusters by applying thresholds to each branch of the tree. The clustering algorithm is followed by a meta-clustering module which makes use of graph theory to obtain insights in the leaf clusters’ connections. The feature vectors representing each document derive from topic modeling. At the implementation level, the clustering method has been dockerized in order to facilitate its deployment on cloud computing infrastructures. Finally, the proposed framework is evaluated on several datasets of varying size and content, achieving significant reduction in both memory consumption and computational time over existing hierarchical clustering algorithms. The experiments also include performance testing on cloud resources using different setups and the results are promising.
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| 9. |
- Toczé, Klervie, 1992-, et al.
(author)
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Characterization and modeling of an edge computing mixed reality workload
- 2020
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 9:1
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Journal article (peer-reviewed)abstract
- The edge computing paradigm comes with a promise of lower application latency compared to the cloud. Moreover, offloading user device computations to the edge enables running demanding applications on resource-constrained mobile end devices. However, there is a lack of workload models specific to edge offloading using applications as their basis.In this work, we build upon the reconfigurable open-source mixed reality (MR) framework MR-Leo as a vehicle to study resource utilisation and quality of service for a time-critical mobile application that would have to rely on the edge to be widely deployed. We perform experiments to aid estimating the resource footprint and the generated load by MR-Leo, and propose an application model and a statistical workload model for it. The idea is that such empirically-driven models can be the basis of evaluations of edge algorithms within simulation or analytical studies.A comparison with a workload model used in a recent work shows that the computational demand of MR-Leo exhibits very different characteristics from those assumed for MR applications earlier.
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| 10. |
- Yin, Fang, et al.
(author)
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Fintech application on banking stability using Big Data of an emerging economy
- 2022
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In: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 11:1
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Journal article (peer-reviewed)abstract
- The rapid growth and development of financial technological advancement (Fintech) services and innovations have attracted the attention of scholars who are now on a quest to analyse their impact on the banking sector. This study conducts several kinds of analyses to measure the effect of the fintech era on the stability of the Chinese banking sector. It uses Big Data and performs Pearson correlation and regression analysis on the fintech era’s transition period to measure the impact of several explanatory variables— institutional regulation, government stability, bank credit to deposit ratio, and economic growth— on the outcome variables, which includes Nonperforming loans (NPLs) and its numerical measurement in relation to the mean score of the Big Data (Z-score). This study uses yearly Big Data from 1995–2018 and revealed that compared to the first wave of the fintech era, the second wave helped in the reduction of NPLs and the enhancement of financial stability in China. This study concludes that in the second wave of the fintech era, the explanatory variables mentioned above had a positive impact on NPLs and banking stability. This work helps comprehend fintech development in modern society and the importance of its disruptive forces in developing and developed countries.
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