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  • Parallel acceleration of CPU and GPU range queries over large data sets
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-08-05
    Mitchell Nelson; Zachary Sorenson; Joseph M. Myre; Jason Sawin; David Chiu

    Data management systems commonly use bitmap indices to increase the efficiency of querying scientific data. Bitmaps are usually highly compressible and can be queried directly using fast hardware-supported bitwise logical operations. The processing of bitmap queries is inherently parallel in structure, which suggests they could benefit from concurrent computer systems. In particular, bitmap-range queries

    更新日期:2020-08-05
  • Network perception task migration in cloud-edge fusion computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-08-03
    Chen Ling; Weizhe Zhang; Hui He; Yu-chu Tian

    With the development of cloud computing, edge computing has been proposed to provide real-time and low-delay services to users. Current research usually integrates cloud computing and edge computing as cloud-edge fusion computing for more personalized services. However, both cloud computing and edge computing suffer from high network consumption, which remains a key problem yet to be solved in cloud-edge

    更新日期:2020-08-03
  • A fuzzy inference system (FIS) to evaluate the security readiness of cloud service providers
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-29
    Syed Rizvi; John Mitchell; Abdul Razaque; Mohammad R. Rizvi; Iyonna Williams

    Cloud computing is a model for on-demand delivery of IT resources (e.g., servers, storage, databases, etc.) over the Internet with pay-as-you-go pricing. Although it provides numerous benefits to cloud service users (CSUs) such as flexibility, elasticity, scalability, and economies of scale, there is a large trust deficit between CSUs and cloud service providers (CSPs) that prevents the widespread

    更新日期:2020-07-29
  • Highly secure edge-intelligent electric motorcycle management system for elevators
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-29
    Zongwei Zhu; Jing Cao; Tiancheng Hao; Wenjie Zhai; Bin Sun; Gangyong Jia; Ming Li

    Because of their portability, electric motorcycles are usually pushed into elevators by residents and charged in the home, which has serious safety risks. Traditional manual-based methods to manage this behavior have poor monitoring effects and high costs. As for automatic management systems using artificial intelligence (AI), the deployment method matters. Cloud-based deployment methods have the disadvantages

    更新日期:2020-07-29
  • 2PC*: a distributed transaction concurrency control protocol of multi-microservice based on cloud computing platform
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-23
    Pan Fan; Jing Liu; Wei Yin; Hui Wang; Xiaohong Chen; Haiying Sun

    The two-phase commit (2PC) protocol is a key technique for achieving distributed transactions in storage systems such as relational databases and distributed databases. 2PC is a strongly consistent and centralized atomic commit protocol that ensures the serialization of the transaction execution order. However, it does not scale well to large and high-throughput systems, especially for applications

    更新日期:2020-07-23
  • Intelligent cloud workflow management and scheduling method for big data applications
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-21
    Yannian Hu; Hui Wang; Wenge Ma

    With the application and comprehensive development of big data technology, the need for effective research on cloud workflow management and scheduling is becoming increasingly urgent. However, there are currently suitable methods for effective analysis. To determine how to effectively manage and schedule smart cloud workflows, this article studies big data from various aspects and draws the following

    更新日期:2020-07-22
  • Towards secure and network state aware bitrate adaptation at IoT edge
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-13
    Zeng Zeng; Hang Che; Weiwei Miao; Jin Huang; Hao Tang; Mingxuan Zhang; Shaqian Zhang

    Video streaming is critical in IoT systems, enabling a variety of applications such as traffic monitoring and health caring. Traditional adaptive bitrate streaming (ABR) algorithms mainly focus on improving Internet video streaming quality where network conditions are relatively stable. These approaches, however, suffer from performance degradation at IoT edge. In IoT systems, the wireless channels

    更新日期:2020-07-13
  • Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-13
    Yi-hua Chen

    In recent years, the rapid development of fresh food e-commerce in China has brought about more development opportunities for the cold chain logistics industry but has also presented new challenges. With the development of cloud computing and big data technology, it is increasingly important to study the application of big data and cloud computing technology in cold chain logistics. The purpose of

    更新日期:2020-07-13
  • A novel privacy-preserving speech recognition framework using bidirectional LSTM
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-07-08
    Qingren Wang; Chuankai Feng; Yan Xu; Hong Zhong; Victor S. Sheng

    Utilizing speech as the transmission medium in Internet of things (IoTs) is an effective way to reduce latency while improving the efficiency of human-machine interaction. In the field of speech recognition, Recurrent Neural Network (RNN) has significant advantages to achieve accuracy improvement on speech recognition. However, some of RNN-based intelligence speech recognition applications are insufficient

    更新日期:2020-07-08
  • Studying gas exceptions in blockchain-based cloud applications
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-30
    Chao Liu; Jianbo Gao; Yue Li; Huihui Wang; Zhong Chen

    Blockchain-based cloud application (BCP) is an emerging cloud application architecture. By moving trust-critical functions onto blockchain, BCP offers unprecedented function transparency and data integrity. Ethereum is by far the most popular blockchain platform chosen for BCP. In Ethereum, special programs named smart contracts are often used to implement key components for BCP. By design, users can

    更新日期:2020-06-30
  • Near real-time optimization of fog service placement for responsive edge computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-19
    Tom Goethals; Filip De Turck; Bruno Volckaert

    In recent years, computing workloads have shifted from the cloud to the fog, and IoT devices are becoming powerful enough to run containerized services. While the combination of IoT devices and fog computing has many advantages, such as increased efficiency, reduced network traffic and better end user experience, the scale and volatility of the fog and edge also present new problems for service deployment

    更新日期:2020-06-19
  • A joint optimization scheme of content caching and resource allocation for internet of vehicles in mobile edge computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-18
    Mu Zhang; Song Wang; Qing Gao

    In a high-speed free-flow scenario, a joint optimization scheme for content caching and resource allocation is proposed based on mobile edge computing in Internet of Vehicles. Vehicle trajectory prediction provides the basis for the realization of vehicle-cloud collaborative cache. By pre-caching the business data of requesting vehicles to edge cloud networks and oncoming vehicles, requesting vehicles

    更新日期:2020-06-18
  • Dynamic resource provisioning for cyber-physical systems in cloud-fog-edge computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-17
    Zhanyang Xu; Yanqi Zhang; Haoyuan Li; Weijing Yang; Quan Qi

    Cyber-Physical Systems(CPS) serves as an interdisciplinary effort that incorporates cyber vector as well as physical vector. The latter can generate exponentially growing amounts of data. How to process CPS big data systematically and efficiently is the key to the breakthrough of offering prospective and personalized services for each individual user and entity involved. In recent years, much research

    更新日期:2020-06-17
  • Image data model optimization method based on cloud computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-15
    Jingyu Liu; Jing Wu; Linan Sun; Hailong Zhu

    In the current age of data explosion, the amount of data has reached incredible proportions. Digital image data constitute most of these data. With the development of science and technology, the demand for networked work and life continues to grow. Cloud computing technology plays an increasingly important role in life and work. This paper studies the optimization methods for cloud computing image

    更新日期:2020-06-15
  • Two-level fuzzy-neural load distribution strategy in cloud-based web system
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-11
    Krzysztof Zatwarnicki

    Cloud computing Web systems are today the most important part of the Web. Many companies transfer their services to the cloud in order to avoid infrastructure aging and thus preventing less efficient computing. Distribution of the load is a crucial problem in cloud computing systems. Due to the specifics of network traffic, providing an acceptable time of access to the Web content is not trivial. The

    更新日期:2020-06-11
  • Approximation analysis of ontology learning algorithm in linear combination setting
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-04
    Wei Gao; Yaojun Chen

    In the past ten years, researchers have always attached great importance to the application of ontology to its relevant specific fields. At the same time, applying learning algorithms to many ontology algorithms is also a hot topic. For example, ontology learning technology and knowledge are used in the field of semantic retrieval and machine translation. The field of discovery and information systems

    更新日期:2020-06-04
  • An efficient task offloading scheme in vehicular edge computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-06-02
    Salman Raza; Wei Liu; Manzoor Ahmed; Muhammad Rizwan Anwar; Muhammad Ayzed Mirza; Qibo Sun; Shangguang Wang

    Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular applications and high mobility scenarios, cost-efficient task offloading in the vehicular environment is still a challenging problem. In this paper, we study the partial task offloading problem in vehicular edge computing in an urban

    更新日期:2020-06-02
  • CNN based lane detection with instance segmentation in edge-cloud computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-05-19
    Wei Wang; Hui Lin; Junshu Wang

    At present, the number of vehicle owners is increasing, and the cars with autonomous driving functions have attracted more and more attention. The lane detection combined with cloud computing can effectively solve the drawbacks of traditional lane detection relying on feature extraction and high definition, but it also faces the problem of excessive calculation. At the same time, cloud data processing

    更新日期:2020-05-19
  • A learning style classification approach based on deep belief network for large-scale online education
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-05-18
    Hao Zhang; Tao Huang; Sanya Liu; Hao Yin; Jia Li; Huali Yang; Yu Xia

    With the rapidly growing demand for large-scale online education and the advent of big data, numerous research works have been performed to enhance learning quality in e-learning environments. Among these studies, adaptive learning has become an increasingly important issue. The traditional classification approaches analyze only the surface characteristics of students but fail to classify students

    更新日期:2020-05-18
  • An ensemble-learning method for potential traffic hotspots detection on heterogeneous spatio-temporal data in highway domain
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-05-11
    Weilong Ding; Yanqing Xia; Zhe Wang; Zhenyu Chen; Xingyu Gao

    Inter-city highway plays an important role in modern urban life and generates sensory data with spatio-temporal characteristics. Its current situation and future trends are valuable for vehicles guidance and transportation security management. As a domain routine analysis, daily detection of traffic hotspots faces challenges in efficiency and precision, because huge data deteriorates processing latency

    更新日期:2020-05-11
  • Revisiting the power of reinsertion for optimal targets of network attack
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-05-07
    Changjun Fan; Li Zeng; Yanghe Feng; Baoxin Xiu; Jincai Huang; Zhong Liu

    Understanding and improving the robustness of networks has significant applications in various areas, such as bioinformatics, transportation, critical infrastructures, and social networks. Recently, there has been a large amount of work on network dismantling, which focuses on removing an optimal set of nodes to break the network into small components with sub-extensive sizes. However, in our experiments

    更新日期:2020-05-07
  • A security event description of intelligent applications in edge-cloud environment
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-05-01
    Qianmu Li; Xiaochun Yin; Shunmei Meng; Yaozong Liu; Zijian Ying

    In traditional network environment, the attack topology of the network is usually obtained based on a graph traversal algorithm. It uses connection relationships to describe the process of the attack, thus completing the description of network security event. However, in the edge-cloud environment, the control logic and data forwarding of network devices are separated from each other. The control layer

    更新日期:2020-05-01
  • Ground radar precipitation estimation with deep learning approaches in meteorological private cloud
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-04-15
    Wei Tian; Lei Yi; Wei Liu; Wei Huang; Guangyi Ma; Yonghong Zhang

    Accurate precipitation estimation is significant since it matters to everyone on social and economic activities and is of great importance to monitor and forecast disasters. The traditional method utilizes an exponential relation between radar reflectivity factors and precipitation called Z-R relationship which has a low accuracy in precipitation estimation. With the rapid development of computing

    更新日期:2020-04-16
  • Deep learning-driven wireless communication for edge-cloud computing: opportunities and challenges
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-04-10
    Huaming Wu; Xiangyi Li; Yingjun Deng

    Future wireless communications are becoming increasingly complex with different radio access technologies, transmission backhauls, and network slices, and they play an important role in the emerging edge computing paradigm, which aims to reduce the wireless transmission latency between end-users and edge clouds. Deep learning techniques, which have already demonstrated overwhelming advantages in a

    更新日期:2020-04-16
  • Flexible automatic detection for security management of dispatching data network
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-04-09
    Xianrui Yang; Yuming Liu; Jiehong Wang; Zhao Yao; Yanping Zhou; Shucun Fu

    Power grid dispatching is among the forefront issues in the power industry for it can highly influence the efficiency of electricity-related industries. At present, power grid dispatching is usually managed manually, which is quite time-consuming with the continuous growth of scale and complexity of electric power systems. To mitigate the time cost of power grid dispatching, an automatic power grid

    更新日期:2020-04-16
  • Energy-efficient sensory data gathering based on compressed sensing in IoT networks
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-04-05
    Xinxin Du; Zhangbing Zhou; Yuqing Zhang; Taj Rahman

    The Internet of Things (IoT) networks have become the infrastructure to enable the detection and reaction of anomalies in various domains, where an efficient sensory data gathering mechanism is fundamental since IoT nodes are typically constrained in their energy and computational capacities. Besides, anomalies may occur occasionally in most applications, while the majority of time durations may reflect

    更新日期:2020-04-16
  • Evaluating TCP performance of routing protocols for traffic exchange in street-parked vehicles based fog computing infrastructure
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-03-28
    Awangku Muhammad Iqbal Yura; S. H. Shah Newaz; Fatin Hamadah Rahman; Thien Wan Au; Gyu Myoung Lee; Tai-Won Um

    As most vehicles remain parked 95% of its time, this suggests that leveraging the use of On-board Units (OBUs) in parked vehicles would provide communication and computation services to other mobile and fixed nodes for delivery of services such as multimedia streaming, data storage and data processing. The nearby vehicles can form an infrastructure using IEEE 802.11p communication interface, facilitating

    更新日期:2020-04-16
  • Fault localization by analyzing failure propagation with samples in cloud computing environment
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-03-12
    Tiantian Wang; Kechao Wang; Xiaohong Su

    With the development of information technology such as cloud computing, IoT, etc, software becomes the infrastructure. On the one hand, it is critical to ensure the reliability of software, on the other, sample code can be mined from open source software to provide reference for automatic debugging. Most of existing automated debugging researches are based on the assumption that defect programs are

    更新日期:2020-04-16
  • ConvLSTMConv network: a deep learning approach for sentiment analysis in cloud computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-03-05
    Mohsen Ghorbani; Mahdi Bahaghighat; Qin Xin; Figen Özen

    The rapid development of social media, and special websites with critical reviews of products have created a huge collection of resources for customers all over the world. These data may contain a lot of information including product reviews, predicting market changes, and the polarity of opinions. Machine learning and deep learning algorithms provide the necessary tools for intelligence analysis in

    更新日期:2020-04-16
  • Pricing cloud IaaS computing services
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-03-03
    Nicola Dimitri

    The economics of cloud computing has recently attracted increasing attention. In particular, a topic which is still under debate is how prices charged to customers for cloud resources are formed, since alternative pricing rules could be considered. Based on three pricing schemes inspired by those used by Amazon EC2, the main global cloud service provider, in the paper we address two main issues. First

    更新日期:2020-04-16
  • Tuning high flow concurrency for MPTCP in data center networks
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-24
    Jiawei Huang; Weihe Li; Qi Li; Tao Zhang; Pingping Dong; Jianxin Wang

    In the data center networks, multipath transmission control protocol(MPTCP) uses multiple subflows to balance traffic over parallel paths and achieve high throughput. Despite much recent progress in improving MPTCP performance in data center, how to adjust the number of subflows according to network status has remained elusive. In this paper, we reveal theoretically and empirically that controlling

    更新日期:2020-04-16
  • Multimodal transport information sharing platform with mixed time window constraints based on big data
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-07
    Liqun Ding

    The primary consideration in the top-level design of multimodal transport systems is the matching degree and coordination degree of port facilities and transport information platforms. In the process of container transportation, there exists a mixed time window consisting of a hard time window and a soft time window. This study focuses on the coordination of transport organization considering the scale

    更新日期:2020-04-16
  • Providing privacy preserving in next POI recommendation for Mobile edge computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-07
    Li Kuang; Shenmei Tu; Yangqi Zhang; Xiaoxian Yang

    Point of interest (POI) recommendation can benefit users and merchants. It is a very important and popular service in modern life. In this paper, we aim to study the next new POI recommendation problem with the consideration of privacy preserving in edge computing. The challenge lies in capturing the transition patterns between POIs precisely and meanwhile protecting users’ location. In this paper

    更新日期:2020-04-16
  • Efficient resourceful mobile cloud architecture (mRARSA) for resource demanding applications
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-07
    Asharul Islam; Anoop Kumar; Khalid Mohiuddin; Sadaf Yasmin; Mohammed Abdul Khaleel; Mohammad Rashid Hussain

    For mobile clients, sufficient resources with the assurance of efficient performance and energy efficiency are the core concerns. This article mainly considers this need and proposes a resourceful architecture, called mRARSA that addresses the critical need in a mobile cloud environment. This architecture consists of cloud resources, mobile devices, and a set of functional components. The performance

    更新日期:2020-04-16
  • Improvement of job completion time in data-intensive cloud computing applications
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-07
    Ibrahim Adel Ibrahim; Mostafa Bassiouni

    Task stragglers in MapReduce jobs dramatically impede job execution of data-intensive computing in cloud data centers. This impedance is due to the uneven distribution of input data, heterogeneous data nodes, resource contention situations, and network configurations. Data skew of intermediate data in MapReduce job causes delay failures due to the violation of job completion time. Data-intensive computing

    更新日期:2020-04-16
  • CIES: Cloud-based Intelligent Evaluation Service for video homework using CNN-LSTM network
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-05
    Rui Song; Zhiyi Xiao; Jinjiao Lin; Ming Liu

    Video (used as a form of examination or homework) as an efficient approach for examining students’ abilities is drawing increasing attention in the education field. How to assess video assignments effectively and accurately has become a significant topic in academia. This work proposes a method based on a multi-channel CNN-LSTM hybrid architecture to extract and classify image features such as students’

    更新日期:2020-04-16
  • An efficient parallel genetic algorithm solution for vehicle routing problem in cloud implementation of the intelligent transportation systems
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-02-03
    Mahdi Abbasi; Milad Rafiee; Mohammad R. Khosravi; Alireza Jolfaei; Varun G. Menon; Javad Mokhtari Koushyar

    A novel parallelization method of genetic algorithm (GA) solution of the Traveling Salesman Problem (TSP) is presented. The proposed method can considerably accelerate the solution of the equivalent TSP of many complex vehicle routing problems (VRPs) in the cloud implementation of intelligent transportation systems. The solution provides routing information besides all the services required by the

    更新日期:2020-04-16
  • PHYAlert: identity spoofing attack detection and prevention for a wireless edge network
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-01-28
    Zhiping Jiang; Kun Zhao; Rui Li; Jizhong Zhao; Junzhao Du

    Delivering service intelligence to billions of connected devices is the next step in edge computing. Wi-Fi, as the de facto standard for high-throughput wireless connectivity, is highly vulnerable to packet-injection-based identity spoofing attacks (PI-ISAs). An attacker can spoof as the legitimate edge coordinator and perform denial of service (DoS) or even man-in-the-middle (MITM) attacks with merely

    更新日期:2020-04-16
  • Study on coupling degree of rail transit capacity and land use based on multivariate data from cloud platform
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-01-21
    Quanhua Hou; Yaotian Xing; Di Wang; Jiachen Liu; Xiaoyang Fan; Yaqiong Duan

    The study of exploring the internal connection between rail transit and land use is of great significance for the coordinated development of urban space and rail transit construction, and it is also important for the intensive use of land affected by rail transit stations. The land use structure and population density surrounding the stations of Line 1.2.3 of Xi’an Rail Transit were clustered by SPSS

    更新日期:2020-04-16
  • Secure VM management with strong user binding in semi-trusted clouds
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-01-17
    Keisuke Inokuchi; Kenichi Kourai

    In Infrastructure-as-a-Service (IaaS) clouds, remote users access provided virtual machines (VMs) via the management server. The management server is managed by cloud operators, but not all the cloud operators are trusted in semi-trusted clouds. They can execute arbitrary management commands to users’ VMs and redirect users’ commands to malicious VMs. We call the latter attack the VM redirection attack

    更新日期:2020-04-16
  • A dockerized framework for hierarchical frequency-based document clustering on cloud computing infrastructures
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-01-17
    Maria Th. Kotouza; Fotis E. Psomopoulos; Pericles A. Mitkas

    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

    更新日期:2020-04-16
  • Cloudy transaction costs: a dive into cloud computing economics
    J. Cloud Comp. (IF 2.788) Pub Date : 2020-01-13
    Rasha Makhlouf

    Looking merely from the neoclassical perspective, cloud computing is price effective. However, according to institutional and transaction cost economics, cloud customers should estimate other costs beyond the price. Such costs may not be known to cloud customers, leading to unmet expectations and implementation challenges. The aim of this paper is to study transaction costs of cloud computing from

    更新日期:2020-04-16
  • Publicly verifiable and efficiency/security-adjustable outsourcing scheme for solving large-scale modular system of linear equations
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-27
    Panpan Meng; Chengliang Tian; Xiangguo Cheng

    Solving large-scale modular system of linear equations ($\mathcal {LMSLE}$) is pervasive in modern computer and communication community, especially in the fields of coding theory and cryptography. However, it is computationally overloaded for lightweight devices arisen in quantity with the dawn of the things of internet (IoT) era. As an important form of cloud computing services, secure computation

    更新日期:2020-04-16
  • Security governance as a service on the cloud
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-26
    Ciarán Bryce

    Small companies need help to detect and to respond to increasing security related threats. This paper presents a cloud service that automates processes that make checks for such threats, implement mitigating procedures, and generally instructs client companies on the steps to take. For instance, a process that automates the search for leaked credentials on the Dark Web will, in the event of a leak

    更新日期:2020-04-16
  • Load balancing in cloud computing – A hierarchical taxonomical classification
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-23
    Shahbaz Afzal; G. Kavitha

    Load unbalancing problem is a multi-variant, multi-constraint problem that degrades performance and efficiency of computing resources. Load balancing techniques cater the solution for load unbalancing situation for two undesirable facets- overloading and under-loading. In contempt of the importance of load balancing techniques to the best of our knowledge, there is no comprehensive, extensive, systematic

    更新日期:2020-04-16
  • Reliability and capability based computation offloading strategy for vehicular ad hoc clouds
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-16
    Bo Li; Ziyi Peng; Peng Hou; Min He; Marco Anisetti; Gwanggil Jeon

    In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment to hand over tasks to these nodes for execution. In this way

    更新日期:2020-04-16
  • The cloud application modelling and execution language
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-16
    Achilleas P. Achilleos; Kyriakos Kritikos; Alessandro Rossini; Georgia M. Kapitsaki; Jörg Domaschka; Michal Orzechowski; Daniel Seybold; Frank Griesinger; Nikolay Nikolov; Daniel Romero; George A. Papadopoulos

    Cloud computing offers a flexible pay-as-you-go model for provisioning application resources, which enables applications to scale on-demand based on the current workload. In many cases, though, users face the single vendor lock-in effect, missing opportunities for optimal and adaptive application deployment across multiple clouds. Several cloud modelling languages have been developed to support multi-cloud

    更新日期:2020-04-16
  • Secure end-to-end processing of smart metering data
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-12-04
    Andrey Brito; Christof Fetzer; Stefan Köpsell; Peter Pietzuch; Marcelo Pasin; Pascal Felber; Keiko Fonseca; Marcelo Rosa; Luiz Gomes; Rodrigo Riella; Charles Prado; Luiz F. Rust; Daniel E. Lucani; Márton Sipos; László Nagy; Marcell Fehér

    Cloud computing considerably reduces the costs of deploying applications through on-demand, automated and fine-granular allocation of resources. Even in private settings, cloud computing platforms enable agile and self-service management, which means that physical resources are shared more efficiently. Cloud computing considerably reduces the costs of deploying applications through on-demand, automated

    更新日期:2020-04-16
  • Multi-cloud provisioning of business processes
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-11-27
    Kyriakos Kritikos; Chrysostomos Zeginis; Joaquin Iranzo; Roman Sosa Gonzalez; Daniel Seybold; Frank Griesinger; Jörg Domaschka

    The Cloud offers enhanced flexibility in the management of resources for any kind of application while it promises the reduction of its cost as well as its infinite scalability. In this way, due to these advantages, there is a recent move towards migrating business processes (BPs) in the Cloud. Such a move is currently performed in a manual manner and only in the context of one Cloud. However, a multi-

    更新日期:2020-04-16
  • A Neuro-fuzzy approach for user behaviour classification and prediction
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-11-21
    Atta-ur-Rahman; Sujata Dash; Ashish Kr. Luhach; Naveen Chilamkurti; Seungmin Baek; Yunyoung Nam

    Big data and cloud computing technology appeared on the scene as new trends due to the rapid growth of social media usage over the last decade. Big data represent the immense volume of complex data that show more details about behaviours, activities, and events that occur around the world. As a result, big data analytics needs to access diverse types of resources within a decreased response time to

    更新日期:2020-04-16
  • Strand: scalable trilateration with Node.js
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-11-12
    Konstantinos Tserpes; Maria Pateraki; Iraklis Varlamis

    This work reports on the development details and results of an experimental setup for the localization of the attendants of a music festival. The application had to be reporting in real-time the asymmetric crowd density based on the Received Signal Strength Indicator (RSSI) between the attendants’ smartphones and an experimental installation of 24 WiFi access points. The impermanent nature of the application

    更新日期:2020-04-16
  • An optimization approach to capacity evaluation and investment decision of hybrid cloud: a corporate customer’s perspective
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-11-01
    In Lee

    While the rapid growth of cloud computing is driven by the surge of big data, the Internet of Things, and social media applications, an evaluation and investment decision for cloud computing has been challenging for corporate managers due to a lack of proper decision models. This paper attempts to identify critical variables for making a cloud capacity decision from a corporate customer’s perspective

    更新日期:2020-04-16
  • Replaceability and negotiation in a cloud service ecosystem
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-09-14
    Adrija Bhattacharya; Sankhayan Choudhury; Agostino Cortesi

    Cloud federation is an aggregation of services from different providers in a single pool supporting interoperability and resource migration. In federation, Services are assigned to the consumer’s service access pool as per their specific functional and associated Quality level requirements. The said assignment is based on the advertised features of services. Sometimes, the selected provider fails to

    更新日期:2020-04-16
  • Temperature and energy-aware consolidation algorithms in cloud computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-08-27
    Maede Yavari; Akbar Ghaffarpour Rahbar; Mohammad Hadi Fathi

    Cloud computing provides access to shared resources through Internet. It provides facilities such as broad access, scalability and cost savings for users. However, cloud data centers consume a significant amount of energy because of inefficient resources allocation. In this paper, a novel virtual machine consolidation technique is presented based on energy and temperature in order to improve QoS (Quality

    更新日期:2020-04-16
  • Design, simulation and testing of a cloud platform for sharing digital fabrication resources for education
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-08-19
    Gianluca Cornetta; Javier Mateos; Abdellah Touhafi; Gabriel-Miro Muntean

    Cloud and IoT technologies have the potential to support applica- tions that are not strictly limited to technical fields. This paper shows how digital fabrication laboratories (Fab Labs) can leverage cloud technologies to enable resource sharing and provide remote access to distributed expensive fabrication resources over the internet. We call this new concept Fabrication as a Service (FaaS), since

    更新日期:2020-04-16
  • Experts reviews of a cloud forensic readiness framework for organizations
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-08-14
    Ahmed Alenezi; Hany F. Atlam; Gary B. Wills

    Cloud computing has drastically altered the ways in which it is possible to deliver information technologies (ITs) to consumers as a service. In addition, the concept has given rise to multiple benefits for consumers and organizations. However, such a fast surge in the adoption of cloud computing has led to the emergence of the cloud as a new cybercrime environment, thus giving rise to fresh legal

    更新日期:2020-04-16
  • Scalability analysis comparisons of cloud-based software services
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-07-23
    Amro Al-Said Ahmad; Peter Andras

    Performance and scalability testing and measurements of cloud-based software services are necessary for future optimizations and growth of cloud computing. Scalability, elasticity, and efficiency are interrelated aspects of cloud-based software services’ performance requirements. In this work, we use a technical measurement of the scalability of cloud-based software services. Our technical scalability

    更新日期:2020-04-16
  • Online architecture for predicting live video transcoding resources
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-07-09
    Pekka Pääkkönen; Antti Heikkinen; Tommi Aihkisalo

    End users stream video increasingly from live broadcasters (via YouTube Live, Twitch etc.). Adaptive live video streaming is realised by transcoding different representations of the original video content. Management of transcoding resources creates costs for the service provider, because transcoding is a CPU-intensive task. Additionally, the content must be transcoded within real time with the transcoding

    更新日期:2020-04-16
  • Multi-Dimensional Regression Host Utilization algorithm (MDRHU) for Host Overload Detection in Cloud Computing
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-06-13
    Ali A. El-Moursy; Amany Abdelsamea; Rukshanda Kamran; Mohamed Saad

    The use of cloud computing data centers is growing rapidly to meet the tremendous increase in demand for high-performance computing (HPC), storage and networking resources for business and scientific applications. Virtual machine (VM) consolidation involves the live migration of VMs to run on fewer physical servers, and thus allowing more servers to be switched off or run on low-power mode, as to improve

    更新日期:2020-04-16
  • A placement architecture for a container as a service (CaaS) in a cloud environment
    J. Cloud Comp. (IF 2.788) Pub Date : 2019-05-29
    Mohamed K. Hussein; Mohamed H. Mousa; Mohamed A. Alqarni

    Unlike a traditional virtual machine (VM), a container is an emerging lightweight virtualization technology that operates at the operating system level to encapsulate a task and its library dependencies for execution. The Container as a Service (CaaS) strategy is gaining in popularity and is likely to become a prominent type of cloud service model. Placing container instances on virtual machine instances

    更新日期:2020-04-16
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