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Dominating OP Returns: The Impact of Omni and Veriblock on Bitcoin J. Grid Comput. (IF 2.095) Pub Date : 2020-12-11 Elias Strehle, Fred Steinmetz
Bitcoin has always been used to store arbitrary data, particularly since Bitcoin Core developers added a dedicated method for data storage in 2014: the OP Return operator. This paper provides an in-depth analysis of all OP Return transactions published on Bitcoin between September 14, 2018, and December 31, 2019. The 32.4 million OP Return transactions (22% of all Bitcoin transactions) published during
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AirCargoChain: A Distributed and Scalable Data Sharing Approach of Blockchain for Air Cargo J. Grid Comput. (IF 2.095) Pub Date : 2020-12-05 Gejun Le, Qifeng Gu, Qiang Qu, Qingshan Jiang, Jianping Fan
Air cargo involves large-scale data and multiple stakeholders, i.e., airports, airlines, agents, and clients. How to enable stakeholders to share data in a secure way is essential, since it improves efficiency for various processes among stakeholders. This paper proposes AirCargoChain, a blockchain-based data sharing approach for air cargo, which has the following advantages: (a) secure: we propose
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Smart Contracts for Service-Level Agreements in Edge-to-Cloud Computing J. Grid Comput. (IF 2.095) Pub Date : 2020-10-13 Petar Kochovski, Vlado Stankovski, Sandi Gec, Francescomaria Faticanti, Marco Savi, Domenico Siracusa, Seungwoo Kum
The management of Service-Level Agreements (SLAs) in Edge-to-Cloud computing is a complex task due to the great heterogeneity of computing infrastructures and networks and their varying runtime conditions, which influences the resulting Quality of Service (QoS). SLA-management should be supported by formal assurances, ranking and verification of various microservice deployment options. This work introduces
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A Review of Supervised Classification based on Contrast Patterns: Applications, Trends, and Challenges J. Grid Comput. (IF 2.095) Pub Date : 2020-10-04 Octavio Loyola-González, Miguel Angel Medina-Pérez, Kim-Kwang Raymond Choo
Supervised classification based on Contrast Patterns (CP) is a trending topic in the pattern recognition literature, partly because it contains an important family of both understandable and accurate classifiers. In this paper, we survey 105 articles and provide an in-depth review of CP-based supervised classification and its applications. Based on our review, we present a taxonomy of the existing
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Autonomic Management Framework for Cloud-Native Applications J. Grid Comput. (IF 2.095) Pub Date : 2020-09-26 Joanna Kosińska, Krzysztof Zieliński
In order to meet the rapidly changing requirements of the Cloud-native dynamic execution environment, without human support and without the need to continually improve one’s skills, autonomic features need to be added. Embracing automation at every layer of performance management enables us to reduce costs while improving outcomes. The main contribution of this paper is the definition of autonomic
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Multi-Objective Task and Workflow Scheduling Approaches in Cloud Computing: a Comprehensive Review J. Grid Comput. (IF 2.095) Pub Date : 2020-09-17 Mehdi Hosseinzadeh, Marwan Yassin Ghafour, Hawkar Kamaran Hama, Bay Vo, Afsane Khoshnevis
Efficient task and workflow scheduling are very important for improving resource management and reducing power consumption in cloud computing data centers (DCs). However, regarding numerous tasks, virtual machines, and several objectives which should be taken into account, scheduling is considered to be an NP-Hard problem. Multi-objective optimization is an interesting technique to deal with multiple
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Blockchain-Based Cache Poisoning Security Protection and Privacy-Aware Access Control in NDN Vehicular Edge Computing Networks J. Grid Comput. (IF 2.095) Pub Date : 2020-08-25 Kai Lei, Junjie Fang, Qichao Zhang, Junjun Lou, Maoyu Du, Jiyue Huang, Jianping Wang, Kuai Xu
Recent advances in artificial intelligence, big data, mobile edge computing and embedded systems have successfully driven the emergence and adoption of smart vehicles and vehicle edge computing which will improve road safety, traffic congestions, and vehicle exhaust emissions. The high-mobility, ad-hoc network topology, and diverse vehicle-to-everything (V2X) have brought substantial challenges in
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A Fault-Tolerant Workflow Scheduling Algorithm for Grid with Near-Optimal Redundancy J. Grid Comput. (IF 2.095) Pub Date : 2020-08-25 Alemeh Matani, Hamid Reza Naji, Hassan Motallebi
In scheduling workflows in grid environment, concerns such as minimizing the makespan and cost, meeting the time and budget constraints and the possibility of resource failures and so on have motivated researchers to propose numerous scheduling algorithms. Several heuristics and meta-heuristic algorithms have been proposed to address these issues, each of which often only considers one or a few of
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A Survey on the Computation Offloading Approaches in Mobile Edge/Cloud Computing Environment: A Stochastic-based Perspective J. Grid Comput. (IF 2.095) Pub Date : 2020-08-09 Ali Shakarami, Mostafa Ghobaei-Arani, Mohammad Masdari, Mehdi Hosseinzadeh
Fast growth of produced data from deferent smart devices such as smart mobiles, IoT/IIoT networks, and vehicular networks running different specific applications such as Augmented Reality (AR), Virtual Reality (VR), and positioning systems, demand more and more processing and storage resources. Offloading is a promising technique to cope with the inherent limitations of such devices by which the resource-intensive
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Towards Blockchain-Enabled Security Technique for Industrial Internet of Things Based Decentralized Applications J. Grid Comput. (IF 2.095) Pub Date : 2020-08-07 Ali Hassan Sodhro, Sandeep Pirbhulal, Muhammad Muzammal, Luo Zongwei
As the Industrial Internet of Things (IIoT) is one of the emerging trends and paradigm shifts to revolutionize the traditional industries with the fourth wave of evolution or transform it into Industry 4.0. This all is merely possible with the sensor-enabled technologies, e.g., wireless sensor networks (WSNs) in various landscapes, where security provisioning is one of the significant challenges for
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Remote Method Delegation: a Platform for Grid Computing J. Grid Comput. (IF 2.095) Pub Date : 2020-07-14 Bradley Wood, Brock Watling, Zachary Winn, Daniel Messiha, Qusay H. Mahmoud, Akramul Azim
While many cluster and grid computing frameworks are available, the task of building secure distributed systems or implementing distributed algorithms continue to be a challenging task due to the inherent distributed nature of such systems with multiple failure modes and security issues. In this paper, we present the design and development of remote method delegation (RMD), which is a secure lightweight
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Benchmarking Serverless Computing Platforms J. Grid Comput. (IF 2.095) Pub Date : 2020-07-07 Horácio Martins, Filipe Araujo, Paulo Rupino da Cunha
We propose a benchmarking test suite to evaluate performance of cloud serverless platforms and an open source software tool to automate the test process. Additionally, we used this setup to compare the commercial offers of Amazon, Google, Microsoft, and IBM. The work builds on ideas and experiments reported in the literature that, nevertheless, did not offer a “standard” set of coherent and comprehensive
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Building Science Gateways for Analysing Molecular Docking Results Using a Generic Framework and Methodology J. Grid Comput. (IF 2.095) Pub Date : 2020-07-05 Damjan Temelkovski, Tamas Kiss, Gabor Terstyanszky, Pamela Greenwell
Molecular docking and virtual screening experiments require large computational and data resources and high-level user interfaces in the form of science gateways. While science gateways supporting such experiments are relatively common, there is a clearly identified need to design and implement more complex environments for further analysis of docking results. This paper describes a generic framework
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Vulnerability Modelling for Hybrid Industrial Control System Networks J. Grid Comput. (IF 2.095) Pub Date : 2020-07-04 Attiq Ur-Rehman, Iqbal Gondal, Joarder Kamruzzaman, Alireza Jolfaei
With the emergence of internet-based devices, the traditional industrial control system (ICS) networks have evolved to co-exist with the conventional IT and internet enabled IoT networks, hence facing various security challenges. The IT industry around the world has widely adopted the common vulnerability scoring system (CVSS) as an industry standard to numerically evaluate the vulnerabilities in software
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Scalable Decentralized Indexing and Querying of Multi-Streams in the Fog J. Grid Comput. (IF 2.095) Pub Date : 2020-07-01 Patrizio Dazzi, Matteo Mordacchini
NOA-AID (Network Overlays for Adaptive information Aggregation, Indexing and Discovery on the fog) is an approach for decentralized indexing, aggregation and discovery of data belonging to streams. It is organized on two network layers. The upper layer is in charge of delivering an information discovery approach by providing a distributed index structure. The lower layer is devoted to resource aggregation
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Describing and Processing Topology and Quality of Service Parameters of Applications in the Cloud J. Grid Comput. (IF 2.095) Pub Date : 2020-06-15 Gabriele Pierantoni, Tamas Kiss, Gabor Terstyanszky, James DesLauriers, Gregoire Gesmier, Hai-Van Dang
Typical cloud applications require high-level policy driven orchestration to achieve efficient resource utilisation and robust security to support different types of users and user scenarios. However, the efficient and secure utilisation of cloud resources to run applications is not trivial. Although there have been several efforts to support the coordinated deployment, and to a smaller extent the
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A Negotiation Protocol for Fine-Grained Accountable Resource Provisioning and Sharing in e-Science J. Grid Comput. (IF 2.095) Pub Date : 2020-05-20 Zeqian Meng, John Brooke, Junyi Han, Rizos Sakellariou
With the increasing demand for dynamic and customised resource provisioning for computational experiments in e-Science, solutions are required to mediate different participants’ varied demands for such resource provision. This paper presents a novel negotiation protocol based on a new collaboration model. The protocol allows e-Scientists, the manager of an e-Scientist’s collaboration, and resource
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Approach for Selecting and Integrating Cloud Services to Construct Hybrid Cloud J. Grid Comput. (IF 2.095) Pub Date : 2020-05-13 Joonseok Park, Ungsoo Kim, Donggyu Yun, Keunhyuk Yeom
With the popularization of cloud computing, various cloud services have emerged, and hybrid clouds that can take advantage of combining public and private clouds are attracting attention. However, because of their variety, determining a combination of cloud services suited to the user’s current environment and requirements is expensive when deploying a hybrid cloud. Even if the required services are
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Design of a Flexible, User Friendly Feature Matrix Generation System and its Application on Biomedical Datasets J. Grid Comput. (IF 2.095) Pub Date : 2020-04-27 M. Ghorbani, S. Swift, S. J. E. Taylor, A. M. Payne
The generation of a feature matrix is the first step in conducting machine learning analyses on complex data sets such as those containing DNA, RNA or protein sequences. These matrices contain information for each object which have to be identified using complex algorithms to interrogate the data. They are normally generated by combining the results of running such algorithms across various datasets
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Enhancing the Cloud Inter-operation Toolkit ( CIT ) to Support Multiple Cloud Service Models J. Grid Comput. (IF 2.095) Pub Date : 2020-04-18 S. Kirthica, I. Saravanan, Rajeswari Sridhar
In the field of computer science, cloud computing plays an inevitable role in offering on-demand services to end users. The capability, and hence the advantage, of a cloud environment is widened when multiple clouds interact. However, this interaction is usually done in a static environment and/or with the help of insecure brokers. To the best of our knowledge, the Cloud Inter-operation Toolkit (CIT)
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A Systematic Training Procedure for Viola-Jones Face Detector in Heterogeneous Computing Architecture J. Grid Comput. (IF 2.095) Pub Date : 2020-04-15 Pooya Tavallali, Mehran Yazdi, Mohammad R. Khosravi
The face detection has become one of the most important topics in machine learning and computer vision in the last few decades. Many papers have been published utilizing various methods for face detection. One of the most popular face detectors used in many practical applications with heterogeneous computing architecture is Viola-Jones method. Despite of being a real-time and robust face detector,
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Recognizing MapReduce Straggler Tasks in Big Data Infrastructures Using Artificial Neural Networks J. Grid Comput. (IF 2.095) Pub Date : 2020-03-30 Mandana Farhang, Faramarz Safi-Esfahani
MapReduce framework is used for the distribution and parallelization of large-scale data processing. This framework breaks a job into several MapReduce tasks and assigns them to different nodes. A weak performance of a node in executing a task may result in a long execution of the job which is called Straggler Task. Also, detecting the nodes with the weak capability and assigning their tasks to other
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Provisioning Input and Output Data Rates in Data Processing Frameworks J. Grid Comput. (IF 2.095) Pub Date : 2020-03-03 Nam H. Do, Tien Van Do, Lóránt Farkas, Csaba Rotter
This paper is motivated by the need of deadline-bounded applications in live mobile network environments to obtain the guarantee and the appropriate share of an input and output (I/O) data rate. However, data processing frameworks only support the request of memory and the computing capacity at present. In this paper, we propose a solution that allows the control of disk I/O and network I/O for data
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Modeling-Learning-Based Actor-Critic Algorithm with Gaussian Process Approximator J. Grid Comput. (IF 2.095) Pub Date : 2020-04-18 Shan Zhong; Jack Tan; Husheng Dong; Xuemei Chen; Shengrong Gong; Zhenjiang Qian
The tasks with continuous state and action spaces are difficult to be solved with high sample efficiency. Model learning and planning, as a well-known method to improve the sample efficiency, is achieved by learning a system dynamics model first and then using it for planning. However, the convergence of the algorithm will be slowed if the system dynamics model is not captured accurately, with the
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Estimating CT from MR Abdominal Images Using Novel Generative Adversarial Networks J. Grid Comput. (IF 2.095) Pub Date : 2020-03-10 Pengjiang Qian; Ke Xu; Tingyu Wang; Qiankun Zheng; Huan Yang; Atallah Baydoun; Junqing Zhu; Bryan Traughber; Raymond F. Muzic
Computed tomography (CT) plays key roles in radiotherapy treatment planning and PET attenuation correction (AC). Magnetic resonance (MR) imaging has better soft tissue contrast than CT and has no ionizing radiation but cannot directly provide information about photon interactions with tissue that is needed for radiation treatment planning and AC. Therefore, estimating synthetic CT (sCT) images from
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Software Quality Assurance in INDIGO-DataCloud Project: a Converging Evolution of Software Engineering Practices to Support European Research e-Infrastructures J. Grid Comput. (IF 2.095) Pub Date : 2020-03-07 Pablo Orviz Fernández; Mário David; Doina Cristina Duma; Elisabetta Ronchieri; Jorge Gomes; Davide Salomoni
From the advent of Grid technology – as the new paradigm of distributed computing – to the current days of Cloud computing models, the continuous need of new tools and services to match the scientific community requirements has been addressed in Europe through dedicated software development projects for e–Infrastructure creation, operation and management. This work presents the most significant software
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Load Balancing Algorithms for Big Data Flow Classification Based on Heterogeneous Computing in Software Definition Networks J. Grid Comput. (IF 2.095) Pub Date : 2020-02-15 Yang Ping
Distributed network architecture of heterogeneous computing faces with such problems as strict performance constraints of network control, unpredictable mapping relationship between computing data algorithms of different mobile terminals and inconsistency between computing algorithms and link control of data networks. In order to solve the above problems, we begin with software definition network architecture
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Design and Implementation of Abnormal Behavior Detection Based on Deep Intelligent Analysis Algorithms in Massive Video Surveillance J. Grid Comput. (IF 2.095) Pub Date : 2020-02-01 Yan Hu
Aiming at the high complexity of existing crowd abnormal detection models, the inability of traditional CNN to extract time-related features, and the lack of training samples, an improved spatial-temporal convolution neural network is proposed in this paper. The algorithm firstly uses the aggregation channel feature model to process the surveillance image, and selects the suspected object region with
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Detecting Cryptomining Malware: a Deep Learning Approach for Static and Dynamic Analysis J. Grid Comput. (IF 2.095) Pub Date : 2020-01-21 Hamid Darabian; Sajad Homayounoot; Ali Dehghantanha; Sattar Hashemi; Hadis Karimipour; Reza M. Parizi; Kim-Kwang Raymond Choo
Cryptomining malware (also referred to as cryptojacking) has changed the cyber threat landscape. Such malware exploits the victim’s CPU or GPU resources with the aim of generating cryptocurrency. In this paper, we study the potential of using deep learning techniques to detect cryptomining malware by utilizing both static and dynamic analysis approaches. To facilitate dynamic analysis, we establish
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An Anomaly Data Mining Method for Mass Sensor Networks Using Improved PSO Algorithm Based on Spark Parallel Framework J. Grid Comput. (IF 2.095) Pub Date : 2020-01-17 Jingzhen Yuan
Accurate detection and capture of anomaly data in complex network data stream is an important part of ensuring network security. Traditional methods cannot adapt to the high dynamic changes of abnormal data characteristics in complex network. Thus, the detection accuracy is reduced. In this paper, a k-means parallel clustering algorithm is proposed. It is optimized by particle swarm optimization with
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IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications J. Grid Comput. (IF 2.095) Pub Date : 2020-01-10 Asad Javed; Jérémy Robert; Keijo Heljanko; Kary Främling
The evolution of Internet of Things (IoT) technology has led to an increased emphasis on edge computing for Cyber-Physical Systems (CPS), in which applications rely on processing data closer to the data sources, and sharing the results across heterogeneous clusters. This has simplified the data exchanges between IoT/CPS systems, the cloud, and the edge for managing low latency, minimal bandwidth, and
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Workload Allocation in IoT-Fog-Cloud Architecture Using a Multi-Objective Genetic Algorithm J. Grid Comput. (IF 2.095) Pub Date : 2020-01-10 Mahdi Abbasi; Ehsan Mohammadi Pasand; Mohammad R. Khosravi
With the rapid growth of Internet-of-Things (IoT) applications, data volumes have been considerably increased. The processing resources of IoT nodes cannot cope with such huge workloads. Processing parts of the workload in clouds could solve this problem, but the quality of services for end-users will be decreased. Given the latency reduction for end-users, the concept of processing in the fog devices
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Research on Parallel Adaptive Canopy-K-Means Clustering Algorithm for Big Data Mining Based on Cloud Platform J. Grid Comput. (IF 2.095) Pub Date : 2020-01-02 Dongliang Xia; Feifei Ning; Weina He
Firstly, this paper introduces the types of clustering algorithm, and introduces the classical K-means algorithm and canopy algorithm in detail. Then, combining the map reduce computing model and spark cloud computing framework, this paper introduces the parallel Canopy-K-means algorithm after using Canopy algorithm to optimize the initial value of K-means algorithm. However, because Canopy algorithm
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A Robust and Accurate Particle Filter-Based Pupil Detection Method for Big Datasets of Eye Video J. Grid Comput. (IF 2.095) Pub Date : 2019-12-27 Mahdi Abbasi; Mohammad R. Khosravi
Accurate detection of pupil position in successive frames of eye videos is finding applications in many areas including assistive systems and E-learning. Processing the big datasets of eye videos in such systems requires robust and fast eye-tracking algorithms that can predict the position of eye pupil in consecutive video frames. As a major technique, particle filters provide adequate speed but have
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Improved K-Means Clustering Algorithm for Big Data Mining under Hadoop Parallel Framework J. Grid Comput. (IF 2.095) Pub Date : 2019-12-20 Weijia Lu
In order to improve the accuracy and efficiency of the clustering mining algorithm, this paper focuses on the clustering mining algorithm for large data. Firstly, the traditional clustering mining algorithm is improved to improve the accuracy, and then the improved clustering algorithm is parallelized to improve the efficiency. In order to improve the accuracy of clustering, an incremental K-means
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Multi-Task Deep Metric Learning with Boundary Discriminative Information for Cross-Age Face Verification J. Grid Comput. (IF 2.095) Pub Date : 2019-12-12 Tongguang Ni; Xiaoqing Gu; Cong Zhang; Weibo Wang; Yiqing Fan
Image based face verification has attracted extension attention in the fields of pattern recognition and intelligent vision. With difference in age, cross-age face verification from facial images remains a challenging work because of a large number of facial variations caused by shape, skin color and wrinkles and so on. This study proposes a multi-task deep metric learning with boundary discriminative
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Adaptive Workload Forecasting in Cloud Data Centers J. Grid Comput. (IF 2.095) Pub Date : 2019-11-29 Eduard Zharikov; Sergii Telenyk; Petro Bidyuk
Forecasting on different levels of the management system of a cloud data center has received increased attention due to its significant impact on the cloud services quality. Making accurate forecasts, however, is challenging due to the non-stationary workload and intrinsic complexity of the management system of a cloud data center. It is possible to prevent excessive resource allocation and service
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Scheduling Algorithms for Heterogeneous Cloud Environment: Main Resource Load Balancing Algorithm and Time Balancing Algorithm J. Grid Comput. (IF 2.095) Pub Date : 2019-11-19 Weiwei Lin; Gaofeng Peng; Xinran Bian; Siyao Xu; Victor Chang; Yin Li
Cloud computing and Internet of Things (IoT) are two of the most important technologies that have significantly changed human’s life. However, with the growing prevalence of Cloud-IoT paradigm, the load imbalance and higher SLA lead to more resource wastage and energy consumption. Although there are many researches that study Cloud-IoT from the perspective of offloading side, few of them have focused
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A Typology of Online Privacy Personalities J. Grid Comput. (IF 2.095) Pub Date : 2019-11-16 Eva-Maria Schomakers; Chantal Lidynia; Martina Ziefle
With our lives being increasingly digital, most users are concerned about their online privacy. Still, many users provide manifold data online and show no protection behaviors. Research has found different explanations for this privacy paradox: users perform a privacy calculus (weighing benefits and concerns about data sharing), make affective and inconsiderate decisions, or are overtaxed by the complexity
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BOINC: A Platform for Volunteer Computing J. Grid Comput. (IF 2.095) Pub Date : 2019-11-16 David P. Anderson
“Volunteer computing” is the use of consumer digital devices for high-throughput scientific computing. It can provide large computing capacity at low cost, but presents challenges due to device heterogeneity, unreliability, and churn. BOINC, a widely-used open-source middleware system for volunteer computing, addresses these challenges. We describe BOINC’s features, architecture, implementation, and
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LincoSim: a Web Based HPC-Cloud Platform for Automatic Virtual Towing Tank Analysis J. Grid Comput. (IF 2.095) Pub Date : 2019-11-08 F. Salvadore; R. Ponzini
Thanks to evolving web technologies, computational platforms, automation tools and open-source software business model, today, it is possible to develop powerful automatic and virtualized web services for complex physical problems in engineering and design. In particular, in this work, we are presenting a new web based HPC-cloud platform for automatic virtual towing tank analysis. It is well known
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Addressing Application Latency Requirements through Edge Scheduling J. Grid Comput. (IF 2.095) Pub Date : 2019-11-05 Atakan Aral; Ivona Brandic; Rafael Brundo Uriarte; Rocco De Nicola; Vincenzo Scoca
Latency-sensitive and data-intensive applications, such as IoT or mobile services, are leveraged by Edge computing, which extends the cloud ecosystem with distributed computational resources in proximity to data providers and consumers. This brings significant benefits in terms of lower latency and higher bandwidth. However, by definition, edge computing has limited resources with respect to cloud
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Optimizing Applications for Mobile Cloud Computing Through MOCCAA J. Grid Comput. (IF 2.095) Pub Date : 2019-11-01 Harun Baraki; Alexander Jahl; Stefan Jakob; Corvin Schwarzbach; Malte Fax; Kurt Geihs
Mobile Cloud Computing (MCC) aims at leveraging remote resources to boost application performance on mobile devices while conserving resources such as battery, memory, and storage. Offloading computations and outsourcing tasks are, however, associated with numerous challenges known from distributed systems. Typical mobile applications have a monolithic design and are not laid out for a distributed
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Resource Management Approaches in Fog Computing: a Comprehensive Review J. Grid Comput. (IF 2.095) Pub Date : 2019-09-06 Mostafa Ghobaei-Arani; Alireza Souri; Ali A. Rahmanian
In recent years, the Internet of Things (IoT) has been one of the most popular technologies that facilitate new interactions among things and humans to enhance the quality of life. With the rapid development of IoT, the fog computing paradigm is emerging as an attractive solution for processing the data of IoT applications. In the fog environment, IoT applications are executed by the intermediate computing
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An Energy Efficient Algorithm for Workflow Scheduling in IaaS Cloud J. Grid Comput. (IF 2.095) Pub Date : 2019-09-03 Vishakha Singh, Indrajeet Gupta, Prasanta K. Jana
Energy efficient workflow scheduling is the demand of the present time’s computing platforms such as an infrastructure-as-a-service (IaaS) cloud. An appreciable amount of energy can be saved if a dynamic voltage scaling (DVS) enabled environment is considered. But it is important to decrease makespan of a schedule as well, so that it may not extend beyond the deadline specified by the cloud user. In
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Supporting Programmable Autoscaling Rules for Containers and Virtual Machines on Clouds J. Grid Comput. (IF 2.095) Pub Date : 2019-08-30 József Kovács
With the increasing utilization of cloud computing and container technologies, orchestration is becoming an important area on both cloud and container levels. Beyond resource allocation, deployment and configuration, scaling is a key functionality in orchestration in terms of policy, description and flexibility. This paper presents an approach where the aim is to provide a high degree of flexibility
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Green Cloud Computing Using Proactive Virtual Machine Placement: Challenges and Issues J. Grid Comput. (IF 2.095) Pub Date : 2019-08-27 Mohammad Masdari, Mehran Zangakani
Efficient VM management is very crucial for energy saving, increasing profit, and preventing SLA violations. VM placement schemes can be classified into reactive and proactive/predictive schemes which try to improve the VM placement results, by forecasting future workloads or resource demands using various prediction techniques. This paper puts forward an extensive survey of the proactive VM placement
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VM Reservation Plan Adaptation Using Machine Learning in Cloud Computing J. Grid Comput. (IF 2.095) Pub Date : 2019-07-13 Bartlomiej Sniezynski; Piotr Nawrocki; Michal Wilk; Marcin Jarzab; Krzysztof Zielinski
In this paper we propose a novel reservation plan adaptation system based on machine learning. In the context of cloud auto-scaling, an important issue is the ability to define and use a resource reservation plan, which enables efficient resource scheduling. If necessary, the plan may allocate new resources upon reservation where a sufficient amount of resources is available. Our solution allows the
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Cloud-Based Multi-Agent Cooperation for IoT Devices Using Workflow-Nets J. Grid Comput. (IF 2.095) Pub Date : 2019-06-26 Yehia Kotb; Ismaeel Al Ridhawi; Moayad Aloqaily; Thar Baker; Yaser Jararweh; Hissam Tawfik
Most Internet of Things (IoT)-based service requests require excessive computation which exceeds an IoT device’s capabilities. Cloud-based solutions were introduced to outsource most of the computation to the data center. The integration of multi-agent IoT systems with cloud computing technology makes it possible to provide faster, more efficient and real-time solutions. Multi-agent cooperation for
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Heuristic Load Balancing Based Zero Imbalance Mechanism in Cloud Computing J. Grid Comput. (IF 2.095) Pub Date : 2019-06-26 Lingfu Kong; Jean Pepe Buanga Mapetu; Zhen Chen
Cloud computing using virtualization technology has emerged as a new paradigm of large-scale distributed computing. One of its fundamental challenges is to schedule a vast amount of heterogeneous tasks while maintaining load balancing amongst different heterogeneous virtual machines (VMs) to meet both cloud users and providers’ requirements, such as minimum makespan low monetary costs, and high resource
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A Scalable Platform for Monitoring Data Intensive Applications J. Grid Comput. (IF 2.095) Pub Date : 2019-05-29 Ioan Drăgan; Gabriel Iuhasz; Dana Petcu
Latest advances in information technology and the widespread growth in different areas are producing large amounts of data. Consequently, in the past decade a large number of distributed platforms for storing and processing large datasets have been proposed. Whether in development or in production, monitoring the applications running on these platforms is not an easy task, dedicated tools and platforms
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What’s Happening Around the World? A Survey and Framework on Event Detection Techniques on Twitter J. Grid Comput. (IF 2.095) Pub Date : 2019-05-28 Zafar Saeed; Rabeeh Ayaz Abbasi; Onaiza Maqbool; Abida Sadaf; Imran Razzak; Ali Daud; Naif Radi Aljohani; Guandong Xu
In the last few years, Twitter has become a popular platform for sharing opinions, experiences, news, and views in real-time. Twitter presents an interesting opportunity for detecting events happening around the world. The content (tweets) published on Twitter are short and pose diverse challenges for detecting and interpreting event-related information. This article provides insights into ongoing
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The Incremental Load Balance Cloud Algorithm by Using Dynamic Data Deployment J. Grid Comput. (IF 2.095) Pub Date : 2019-03-29 Hui-Ching Hsieh; Mao-Lun Chiang
The rapid advancement of network technology has changed the way the world operates and has produced a large number of network application services for users. In order to provide more convenient services, the network service providers need to provide a more stable and high-capacity system. Therefore, cloud computing technology has been developed in the recent decade. The network service providers can
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Hybrid Cloud Adaptive Scheduling Strategy for Heterogeneous Workloads J. Grid Comput. (IF 2.095) Pub Date : 2019-03-29 Li Chunlin; Tang Jianhang; Luo Youlong
With the advent of the era of big data, many companies have taken the most important steps in the hybrid cloud to handle large amounts of data. In a hybrid cloud environment, cloud burst technology enables applications to be processed at a lower cost in a private cloud and burst into the public cloud when the resources of the private cloud are exhausted. However, there are many challenges in hybrid
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End-to-End Voting with Non-Permissioned and Permissioned Ledgers J. Grid Comput. (IF 2.095) Pub Date : 2019-03-20 Stefano Bistarelli; Ivan Mercanti; Paolo Santancini; Francesco Santini
We propose a decentralised end-to-end voting platform (from voter to candidate) based on the block-chain technology. In particular, we study and exploit both the non-permissioned ledger of Bitcoin, and the MultiChain permissioned ledger. We describe the main architectural choices behind the two implementations, including the pre-voting and post-voting phases. Similar approaches are not as decentralised
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QVIA-SDN: Towards QoS-Aware Virtual Infrastructure Allocation on SDN-based Clouds J. Grid Comput. (IF 2.095) Pub Date : 2019-03-16 Felipe Rodrigo de Souza; Charles Christian Miers; Adriano Fiorese; Marcos Dias de Assunção; Guilherme Piegas Koslovski
Virtual Infrastructures (VIs) emerged as a potential solution for network evolution and cloud services provisioning on the Internet. Deploying VIs, however, is still challenging mainly due to a rigid management of networking resources. By splitting control and data planes, Software-Defined Networks (SDN) enable custom and more flexible management, allowing for reducing data center usage, as well as
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An Improved Method to Deploy Cache Servers in Software Defined Network-based Information Centric Networking for Big Data J. Grid Comput. (IF 2.095) Pub Date : 2019-02-09 Jan Badshah; Muhammad Kamran; Nadir Shah; Shahbaz Akhtar Abid
Big data involves a large amount of data generation, storage, transfer from one place to another, and analysis to extract meaningful information. Information centric networking (ICN) is an infrastructure that transfers big data from one node to another node, and provides in-network caches. For software defined network-based ICN approach, a recently proposed centralized cache server architecture deploys
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A Journey into Bitcoin Metadata J. Grid Comput. (IF 2.095) Pub Date : 2019-01-28 Massimo Bartoletti; Bryn Bellomy; Livio Pompianu
Besides recording transfers of currency, the Bitcoin blockchain is being used to save metadata — i.e. arbitrary pieces of data which do not affect transfers of bitcoins. This can be done by using different techniques, and for different purposes. For instance, a growing number of protocols embed metadata in the blockchain to certify and transfer the ownership of a variety of assets beyond cryptocurrency
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Performability Evaluation and Optimization of Workflow Applications in Cloud Environments J. Grid Comput. (IF 2.095) Pub Date : 2019-01-17 Danilo Oliveira; André Brinkmann; Nelson Rosa; Paulo Maciel
Given the characteristics of dynamic provisioning and illusion of unlimited resources, clouds are becoming a popular alternative for running scientific workflows. In a cloud system for processing workflow applications, the system’s performance is heavily influenced by two factors: the scheduling strategy and failure of components. Failures in a cloud system can simultaneously affect several users and
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SimSim: A Service Discovery Method Preserving Content Similarity and Spatial Similarity in P2P Mobile Cloud J. Grid Comput. (IF 2.095) Pub Date : 2019-01-17 Zhiming Cai; Ivan Lee; Shu-Chuan Chu; Xuehong Huang
Mobile cloud has become a new computing paradigm such that services are accessible in any place and at any time. Despite its promising prospect, challenges arise due to unreliable channel condition and limited bandwidth in wireless communication, dynamic route establishment due to node mobility, difficulties in associating request to relevant service providers, and complication in service deployment
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