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  Subjects -> COMPUTER SCIENCE (Total: 1969 journals)
    - ANIMATION AND SIMULATION (29 journals)
    - ARTIFICIAL INTELLIGENCE (97 journals)
    - AUTOMATION AND ROBOTICS (96 journals)
    - CLOUD COMPUTING AND NETWORKS (62 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ENGINEERING (10 journals)
    - COMPUTER GAMES (15 journals)
    - COMPUTER PROGRAMMING (23 journals)
    - COMPUTER SCIENCE (1147 journals)
    - COMPUTER SECURITY (45 journals)
    - DATA BASE MANAGEMENT (12 journals)
    - DATA MINING (32 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (28 journals)
    - ELECTRONIC DATA PROCESSING (21 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (101 journals)
    - INTERNET (91 journals)
    - SOCIAL WEB (49 journals)
    - SOFTWARE (32 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1147 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 11)
Abakós     Open Access   (Followers: 3)
Academy of Information and Management Sciences Journal     Full-text available via subscription   (Followers: 67)
ACM Computing Surveys     Hybrid Journal   (Followers: 23)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 11)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 4)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 12)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 3)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 1)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 9)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 21)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Advanced Engineering Materials     Hybrid Journal   (Followers: 24)
Advanced Science Letters     Full-text available via subscription   (Followers: 5)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 14)
Advances in Artificial Neural Systems     Open Access   (Followers: 4)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15)
Advances in Computer Science : an International Journal     Open Access   (Followers: 13)
Advances in Computing     Open Access   (Followers: 3)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 9)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
Advances in Materials Sciences     Open Access   (Followers: 16)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 35)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access  
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 7)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 9)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 3)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 6)
American Journal of Sensor Technology     Open Access   (Followers: 2)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 5)
Analysis in Theory and Applications     Hybrid Journal  
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 8)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 6)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 2)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 13)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 1)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 1)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 31)
Applied Medical Informatics     Open Access   (Followers: 9)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 4)
Archive of Numerical Software     Open Access  
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 5)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access  
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 3)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 8)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 7)
Basin Research     Hybrid Journal   (Followers: 3)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Bioinformatics     Hybrid Journal   (Followers: 232)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 16)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 31)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 45)
British Journal of Educational Technology     Hybrid Journal   (Followers: 119)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 12)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal  
Cell Communication and Signaling     Open Access   (Followers: 1)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 12)
Circuits and Systems     Open Access   (Followers: 13)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Communication Methods and Measures     Hybrid Journal   (Followers: 11)
Communication Theory     Hybrid Journal   (Followers: 18)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 47)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access  
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access  
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 1)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 8)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 12)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 4)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 13)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 27)
Computer     Full-text available via subscription   (Followers: 78)
Computer Aided Surgery     Hybrid Journal   (Followers: 3)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 8)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 22)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 10)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 1)
Computer Music Journal     Hybrid Journal   (Followers: 13)
Computer Physics Communications     Hybrid Journal   (Followers: 6)
Computer Science - Research and Development     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computer Science and Information Technology     Open Access   (Followers: 10)
Computer Science Education     Hybrid Journal   (Followers: 12)
Computer Science Journal     Open Access   (Followers: 20)
Computer Science Master Research     Open Access   (Followers: 9)
Computer Science Review     Hybrid Journal   (Followers: 10)

        1 2 3 4 5 6 | Last

Journal Cover Cluster Computing
  [SJR: 0.605]   [H-I: 24]   [1 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1573-7543 - ISSN (Online) 1386-7857
   Published by Springer-Verlag Homepage  [2329 journals]
  • Prediction method of icing thickness of transmission line based on MEAO
    • Authors: Wei Xiong; Hejin Yuan; Lang You
      Abstract: Transmission line icing is very important for safe operation of transmission network. Icing thickness of transmission line has characteristics including nonlinear growth, complicated influencing factors, long-term prediction and low accuracy. Based on intelligent prediction algorithms such as BP neutral network and support vector machine, the work proposed intelligent prediction method of icing thickness optimized by mind evolution algorithm. After modeling on basis of crucial factors of transmission line icing, we conducted simulation experiments of temperature, humidity and wire tension. Result shows that prediction model, with better performance than original intelligent method, can be used to more accurately predict icing thickness of transmission line.
      PubDate: 2017-05-20
      DOI: 10.1007/s10586-017-0923-3
       
  • Text mining and sustainable clusters from unstructured data in cloud
           computing
    • Authors: Ning Wang; Jianping Zeng; Maozhi Ye; Mingming Chen
      Abstract: Text mining (TM) is basically the Data mining on information. TM is a procedure of separating possibly helpful data from crude Data, to enhance the nature of the data benefit. The manuscript presents the essential idea of CC and TM firstly, and outlines out how TM is utilized as a part of CC. There is an enormous measure of consideration being cantered around enhancing the security applications in the web nowadays. The Internet measurements demonstrate that there were numerous sources that significantly rely on upon access to appropriate and secure. Determination part of the issue has been examined for long, so Author sets out taking a shot at the to begin with, while the remaining is still in thought organize. Author gives a bit of knowledge into the proposed work on robotizing therapeutic determination utilizing mining strategies and incorporates some underlying outcomes. A principled methodology is proposed to build up a keen data framework by breaking down the formless information. Develop the blame philosophy for discover the blame so that concentrate the superfluous data. The proposed technique is that investigation of rundown and literary theft examination and discovers the productivity that is the time multifaceted nature and increment the execution of framework utilizing group based methodology.
      PubDate: 2017-05-19
      DOI: 10.1007/s10586-017-0909-1
       
  • Study of cloud service queuing model based on imbedding Markov chain
           perspective
    • Authors: ZheXi Yang; Wei Liu; Duo Xu
      Abstract: A cloud service model has been built in this article to evaluate the QoS of cloud service system. The Markov chain of the viewpoint has been created by applying imbedding Markov chain approach. The random arrivals of cloud requests based on the non follow-up effectiveness characteristics of the Markov chain have been simulated. A cloud service queuing model has been set up by using queue waiting time, network delay time and server processing time as the measurable indicators of cloud service system serving level, and the effectiveness of the evaluating model of cloud service quality raised in this article has been validated by means of analysis and simulation.
      PubDate: 2017-05-19
      DOI: 10.1007/s10586-017-0907-3
       
  • Value of service based resource management for large-scale computing
           systems
    • Authors: Cihan Tunc; Dylan Machovec; Nirmal Kumbhare; Ali Akoglu; Salim Hariri; Bhavesh Khemka; Howard Jay Siegel
      Abstract: Task scheduling for large-scale computing systems is a challenging problem. From the users perspective, the main concern is the performance of the submitted tasks, whereas, for the cloud service providers, reducing operation cost while providing the required service is critical. Therefore, it is important for task scheduling mechanisms to balance users’ performance requirements and energy efficiency because energy consumption is one of the major operational costs. We present a time dependent value of service (VoS) metric that will be maximized by the scheduling algorithm that take into consideration the arrival time of a task while evaluating the value functions for completing a task at a given time and the tasks energy consumption. We consider the variation in value for completing a task at different times such that the value of energy reduction can change significantly between peak and non-peak periods. To determine the value of a task completion, we use completion time and energy consumption with soft and hard thresholds. We define the VoS for a given workload to be the sum of the values for all tasks that are executed during a given period of time. Our system model is based on virtual machines, where each task will be assigned a resource configuration characterized by the number of the homogeneous cores and amount of memory. For the scheduling of each task submitted to our system, we use the estimated time to compute matrix and the estimated energy consumption matrix which are created using historical data. We design, evaluate, and compare our task scheduling methods to show that a significant improvement in energy consumption can be achieved when considering time-of-use dependent scheduling algorithms. The simulation results show that we improve the performance and the energy values up to 49% when compared to schedulers that do not consider the value functions. Similar to the simulation results, our experimental results from running our value based scheduling on an IBM blade server show up to 82% improvement in performance value, 110% improvement in energy value, and up to 77% improvement in VoS compared to schedulers that do not consider the value functions.
      PubDate: 2017-05-19
      DOI: 10.1007/s10586-017-0901-9
       
  • Self-configuring cloud application mashup with goals and capabilities
    • Authors: Luca Sabatucci; Salvatore Lopes; Massimo Cossentino
      Abstract: Cloud mashup is a technique for the seamless composition of SaaS applications from several sources into a single integrated solution. This paper presents a general approach for automatically composing applications and services deployed over the Cloud. The proposed approach implies to encapsulate distributed processes into smart and autonomic entities, namely cloud capabilities. Despite the lack of a central mashup server, these processes are able to autonomously organize in order to establish different ways to address the desired result. The approach uses a couple of languages for describing respectively the mashup logic in terms of goals and the available functionalities in terms of capabilities. The explicit decoupling between user’s goals and capabilities provides the system the freedom to generate the orchestration plan at run-time, according to the contextual state. An industrial case study, conducted in for a scientific project, has provided the conditions for evaluating the running example of a B2B business process for a fashion enterprise.
      PubDate: 2017-05-19
      DOI: 10.1007/s10586-017-0911-7
       
  • Dynamic load balancing in distributed exascale computing systems
    • Authors: Seyedeh Leili Mirtaheri; Lucio Grandinetti
      Abstract: According to exascale computing roadmap, the dynamic nature of new generation scientific problems needs an undergoing review in the static management of computing resources. Therefore, it is necessary to present a dynamic load balancing model to manage the load of the system, efficiently. Currently, the distributed exascale systems are the promising solution to support the scientific programs with dynamic requests to resources. In this work, we propose a dynamic load balancing mechanism for distributed controlling of the load in the computing nodes. The presented method overcomes the challenges of dynamic behavior in the next generation problems. The proposed model considers many practical parameters including the load transition and communication delay. We also propose a compensating factor to minimize the idle time of computing nodes. We propose an optimized method to calculate this compensating factor. We estimate the status of nodes and also calculate the exact portion of the load that should be transferred to perform the optimized load balancing. The evaluation results show significant improvements regarding the performance by proposed load balancing in compared with some earlier distributed load balancing mechanisms.
      PubDate: 2017-05-19
      DOI: 10.1007/s10586-017-0902-8
       
  • Research on the Internet of Things and the development of smart city
           industry based on big data
    • Authors: Zhanyu Liu
      Abstract: Development of smart city and smart industry is a major concern in today’s world. By using the Internet of Things and big data analytics, can develop the smart city and smart industry. So a new approach called smart city industry based on big data (SCIB) is proposed. This helps to enhance the performance and to develop the smart city and smart industry even by using big data analytics. Here data are collected from the smart city and industrial appliances such as health care, education systems, congestion management and power grid. These data will be formed as a big data and that will be passed to data acquisition for digitalization. Further it will be stored with the help of cloud computing process. Now based on the application user’s requirement data processing, decision making and data transfer process will be done. In simulation section, it analyzes the performance and calculates the parameters such as delay, lifetime, failure rate, congestion rate and throughput to know the performance of the proposed approach. The proposed SCIB approach will help to increase the throughput and lifetime at the same time it reduces the delay, failure rate and congestion rate.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0910-8
       
  • Support for spot virtual machine purchasing simulation
    • Authors: Ao Zhou; Shangguang Wang; Qibo Sun; Jinglin Li; Qinglin Zhao; Fangchun Yang
      Abstract: With the rapid progress of cloud computing technology, a growing number of big data application providers begin to deploy applications on virtual machines rented from infrastructure as a service providers. Current infrastructure as a service provider offers diverse purchasing options for the application providers. There are mainly three types of purchasing options: reserved virtual machine, on-demand virtual machine and spot virtual machine. The spot virtual machine is a specific type of virtual machine that employs a dynamic pricing model. Because can be stopped by the infrastructure as a service providers without notice, the spot virtual machine is suitable for large-scale divisible applications, such as big data analysis. Therefore, spot virtual machine is chosen by many big data application providers for its low rental cost per hour. When spot virtual machine is chosen, a major issue faced by the big data application providers is how to minimize the virtual machine rental cost while meet service requirements. Many optimal spot virtual machine purchasing approaches have been presented by the researchers. However, there is a shortage of simulators that enable researchers to evaluate their newly proposed spot virtual machine purchasing approach. To fill this gap, in this paper, we propose SpotCloudSim to support for dynamic virtual machine pricing model simulation. SpotCloudSim provides an extensible interface to help researchers implement new spot virtual machine purchasing approach. In addition, SpotCloudSim can also study the behavior of the newly proposed spot virtual machine purchasing approaches. We demonstrate the capabilities of SpotCloudSim by using three spot virtual machine purchasing approaches. The results indicate the benefits of our proposed simulation system.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0882-8
       
  • An ideal IoT solution for real-time web monitoring
    • Authors: Pedro Diogo; Nuno Vasco Lopes; Luis Paulo Reis
      Abstract: For the internet of things (IoT) to fully emerge, it is necessary to design a suitable system architecture and specific protocols for this environment. The former to provide horizontal solutions, breaking away the current paradigm of silos solutions, and thus, allowing the creation of open and interoperable systems; while the latter will offer efficient and scalable communications. This paper presents the latest standards and ongoing efforts to develop specific protocols for IoT. Furthermore, this paper presents a new system, with the most recent standards for IoT. Its design, implementation and evaluation will be also described. The proposed system is based on the latest ETSI M2M specification (ETSI TC M2M in ETSI TS 103 093 V2.1.1. http://www.etsi.org/deliver/etsi_ts/103000_103099/103093/02.01.01_60/ts_103093v020101p.pdf, 2013b) and the MQTT protocol (IBM, Eurotech in MQTT V3.1 Protocol Specification pp 1–42, http://public.dhe.ibm.com/software/dw/webservices/ws-mqtt/MQTT_V3.1_Protocol_Specific.pdf, 2010). With this solution it is possible to show how we can create new applications to run over it and the importance of designing specifically tailored for IoT communication protocols in order to support real-time applications.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0861-0
       
  • The numerical method for the optimal supporting position and related
           optimal control for the catalytic reaction system
    • Authors: Qiyu Liu; Qunxiong Zhu; Xin Yu; Zhiqiang Geng; Longjin Lv
      Abstract: This paper considers the numerical approximation for the optimal supporting position and related optimal control of a catalytic reaction system with some control and state constraints, which is governed by a nonlinear partial differential equations with given initial and boundary conditions. By the Galerkin finite element method, the original problem is projected into a semi-discrete optimal control problem governed by a system of ordinary differential equations. Then the control parameterization method is applied to approximate the control and reduce the original system to an optimal parameter selection problem, in which both the position and related control are taken as decision variables to be optimized. This problem can be solved as a nonlinear optimization problem by a particle swarm optimization algorithm. The numerical simulations are given to illustrate the effectiveness of the proposed numerical approximation method.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0898-0
       
  • Reactive power pricing using cloud service considering wind energy
    • Authors: D. Danalakshmi; S. Kannan; V. Thiruppathy Kesavan
      Abstract: This paper proposes a transparent and reliable method between the suppliers and consumers for optimal reactive power pricing. The electric power suppliers compute the optimal reactive power using optimal reactive power dispatch problem by considering nodal voltage stability index ‘I’ as one of the constraints. The computed optimal reactive power of the generator is included in the reactive power pricing. The pricing method to the suppliers based on the opportunity cost method is presented and a detailed analysis using 62 bus Indian utility system has been carried out by considering diverse cases. In this proposed pricing method, the services of the cloud technology have been used to provide transparent pricing based on the demands of the consumers. The power demands at the consumers’ site is calculated without the human involvement using the Internet of Things and the same is uploaded in the cloud. In reactive power pricing, the system operator acts as a mediator between the suppliers and consumers. Based on the demand and availability of power, the system operator provides the cost for the service to the consumer through cloud.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0896-2
       
  • EPACO: a novel ant colony optimization for emerging patterns based
           classification
    • Authors: Zulfiqar Ali; Waseem Shahzad
      Abstract: In this paper, a novel approach for discovering emerging patterns has been proposed. Majority of the existing algorithms for the discovery of emerging patterns are tree-based which involve growth and shrinking of trees for this purpose. These algorithms follow greedy search approach for discovery of emerging patterns. The proposed approach utilizes the diversity of ant colony optimization and avoids complexity and greedy search of tree-based algorithms for discovery of emerging patterns. The experiments show that the proposed approach provides higher accuracy than existing state of the art classifiers as well as emerging pattern-based classifiers.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0894-4
       
  • Fast lightweight reconfiguration of virtual constellation for obtaining of
           earth observation big data
    • Authors: Lijun Dong; Hong Yao; Rajiv Ranjan; Feng Zhang; Mengqi Pan
      Abstract: Earth observation (EO) big data is playing the increasingly important role in spatial sciences. To obtain adequate EO data, virtual constellation is proposed to overcome the limitation of traditional EO facilities, by combining the existing space and ground segment capabilities. However, the current configuration pattern of virtual constellation is tightly coupled with the specific application requirements. This leads to the costly reconfigurations. Although the pattern of software defined satellite network can decouple topology reconfigurations from application requirements, it cannot be directly applied to the reconfigurations of virtual constellations because of some drawbacks. To address the problem, we propose a model of LEO-ground links control-covering (LGLC) to implement fast and lightweight reconfiguration for virtual constellation. LGLC uses a bipartite graph model to formalize the dispatch problem of the control information of virtual constellation reconfiguration, and the optimum solution can be got by the classical algorithm in polynomial time. According to the strategy obtained, only if a few satellites and stations receive the control information, virtual constellation can be reconfigured quickly. We also establish some metrics to evaluate the effect of LGLC. Extensive experiments are conducted to confirm the above claims.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0905-5
       
  • Energy-aware auto-scaling algorithms for Cassandra virtual data centers
    • Authors: Emiliano Casalicchio; Lars Lundberg; Sogand Shirinbab
      Abstract: Apache Cassandra is an highly scalable and available NoSql datastore, largely used by enterprises of each size and for application areas that range from entertainment to big data analytics. Managed Cassandra service providers are emerging to hide the complexity of the installation, fine tuning and operation of Cassandra virtual data centers (VDCs). This paper address the problem of energy efficient auto-scaling of Cassandra VDC in managed Cassandra data centers. We propose three energy-aware autoscaling algorithms: Opt, LocalOpt and LocalOpt-H. The first provides the optimal scaling decision orchestrating horizontal and vertical scaling and optimal placement. The other two are heuristics and provide sub-optimal solutions. Both orchestrate horizontal scaling and optimal placement. LocalOpt consider also vertical scaling. In this paper: we provide an analysis of the computational complexity of the optimal and of the heuristic auto-scaling algorithms; we discuss the issues in auto-scaling Cassandra VDC and we provide best practice for using auto-scaling algorithms; we evaluate the performance of the proposed algorithms under programmed SLA variation, surge of throughput (unexpected) and failures of physical nodes. We also compare the performance of energy-aware auto-scaling algorithms with the performance of two energy-blind auto-scaling algorithms, namely BestFit and BestFit-H. The main findings are: VDC allocation aiming at reducing the energy consumption or resource usage in general can heavily reduce the reliability of Cassandra in term of the consistency level offered. Horizontal scaling of Cassandra is very slow and make hard to manage surge of throughput. Vertical scaling is a valid alternative, but it is not supported by all the cloud infrastructures.
      PubDate: 2017-05-18
      DOI: 10.1007/s10586-017-0912-6
       
  • Energy efficient key agreement scheme for ubiquitous and continuous remote
           healthcare systems using data mining technique
    • Authors: Saleh M. Al-Saleem; Aftab Ali; Naveed Khan
      Abstract: Wireless body area networks (WBANs) based ubiquitous and fully automated healthcare systems provide a platform to share medical information. Energy efficiency and communication security will increase the confidence of the users in adopting such remote healthcare systems. Key agreement and authentication schemes play an important role in the security of remote healthcare systems. The nodes in a WBAN exchange information in order to complete the key agreement and authentication process. In the literature, numerous schemes have used heavy mathematical calculations or overloaded with excessive information exchange. This paper presents a bloom filter-based key agreement scheme using k-mean clustering for WBANs. The key agreement and authentication is performed in clustered environment using k-mean clustering. This makes the scheme more robust and energy efficient. The keys are generated from the EKG values of the human body. The proposed mechanism is energy efficient and secure, due to its more efficient key generation and less memory utilizations for remote healthcare systems. Moreover, the proposed scheme is analyzed and compared with a state-of-the-art scheme in terms of energy consumption, memory utilizations, processing complexity, and false positive rate (FPR). The results show that the proposed scheme outperform significantly the other scheme by consuming less energy and efficient memory utilization, while achieving a very low FPR and linear running complexity.
      PubDate: 2017-05-13
      DOI: 10.1007/s10586-017-0903-7
       
  • Heart rate variability based stress index service model using bio-sensor
    • Authors: Hyun Yoo; Kyungyong Chung
      Abstract: As infinite competition and materialism have become severe in the current society, stress management has emerged as a main topic. There are many causes that create stress, including external factors and personal events. Also, stress has different levels, depending on an individuals’ subjective analysis. Stress has high correlations with cardiovascular disorders and mental illness. In particular, long-term stress leads to lowered immunity, which makes people more exposed to various diseases, and brings personal and social costs. With the rapid development of the IoT, it has been easy to analyze and manage stress with the use of sensors and communications technology relating to the human body and its surroundings. This study proposes a heart-rate variability-based stress index service using a biosensor. The proposed method collects a variety of information in dual physical environments (such as temperature, humidity, and brightness) from IoT devices, and analyzes it in real-time. The discomfort index and wind chill temperature index offered by the Korea Meteorological Administration, and the temperature, humidity, noise, and brightness collected from a biosensor are the most clear factors to digitize the physical environments of stress. Also, a smart health platform analyzes different heart rates depending on individual conditions, and monitors current status. For a heart rate, the frequency of the R-R value and low frequency (LF) are analyzed. For R-R value, a maximum value detection algorithm is applied. For LF analysis, Fourier transform is used. Generally, fast Fourier transform is unable to analyze the relation between time and frequency. Accordingly, applied is a short time Fourier transform in which window size is limited in a graph so as to express an effect made by changing time effectively. A stress index is comprised of discomfort level, wind chill temperature, noise, brightness, and heart rate. The notification of risk is given to the user by signal lights indicating stability, warning, or danger. The stress index service enables a user to check the stress index in real-time over a smart health platform at any place and at any time. Therefore, it serves as a tool to notify one’s acquaintances of a risk when one faces an emergent situation or is about to be at risk.
      PubDate: 2017-05-12
      DOI: 10.1007/s10586-017-0879-3
       
  • Object recognition and 3D reconstruction of occluded objects using
           binocular stereo
    • Authors: L. Priya; Sheila Anand
      Abstract: Object recognition is one of the key areas in computer vision which comprises of object detection, recognition and reconstruction. The image of the object to be recognized is captured using camera and matched with pre-stored templates of the model object. Recognizing 3D view of the object is difficult in the presence of object occlusion and view-point invariants. This paper focuses on the problem of occlusion and provides a solution for handling self and inter-object occlusion. Self-occlusion has been addressed by the suitable calibration of the cameras and a novel algorithm has been proposed to address inter-object occlusion. A modified geometric mapping technique has been proposed for the 3D reconstruction of the recognized object. Real-time setup has been used to test the proposed solutions to identify objects of multiple shapes and sizes. The results show that the performance of the algorithm was superior and enabled recognition of objects with 80% occlusion or less.
      PubDate: 2017-05-12
      DOI: 10.1007/s10586-017-0891-7
       
  • Cloud-based learning system for answer ranking
    • Authors: Li Wei Yuan; Lei Su; Yin Zhang; Guang Fang; Peng Shu
      Abstract: Community question answering (Q&A) is a new knowledge-sharing model where a large number of questions and answers are accumulated through the user’s submission. When the user submits a new question, the Q&A system can provide the accurate answers list by the learning model. The traditional ranking algorithm mainly uses a large number of labeled data to train the model. However, a ranking model trained in the source domain may lead to poor performance in the target domain because of the lack of labeled training samples in the new domain. To address this challenge, this paper proposes a transfer learning algorithm based on feature selection for ranking. Suppose that the source domain and the target domain share the low-dimensional feature representation, and due to the user features exist share knowledge in source domain and target, so we use the user features are integrated into the answer space. Then the features of the target domain are shared for knowledge transfer. Furthermore, to improve the computational efficiency for the huge amount of data in the community Q&A, the learning model is distributed and processed by the Spark technology. Experimental results show that the proposed method could effectively exploit the cross-domain knowledge to enhance the effect of ranking.
      PubDate: 2017-05-12
      DOI: 10.1007/s10586-017-0888-2
       
  • Research on the parameter inversion problem of prestack seismic data based
           on improved differential evolution algorithm
    • Authors: Qinghua Wu; Zhixin Zhu; Xuesong Yan
      Abstract: The parameter inversion technology composed by intelligent algorithm and AVO inversion for prestack seismic data provides a comparatively effective identification method for oil-gas exploration. However, traditionally intelligent iterative algorithm, such as, genetic algorithm, shows many disadvantages in solving this problem, including highly depending on initial model, fast convergence in algorithm and being easy to fall into local optimal. Therefore, an unsatisfied inversion performance is produced. In order to solve the above problems, this paper proposes a parameter inversion method based on improved differential evolution algorithm which is better in solving parameter inversion problems of prestack seismic data. In the proposed algorithm, aims at the Aki and Rechard approximation formula used specific initialization strategy, then the initialization parameter curve more smooth. Otherwise, the new algorithm has many advantages, such as, fast computing speed, simple operation, a low independence to initial model and good global convergence, this algorithm is the right choice in solving the parameter inversion problem based on pre-stack seismic data of real number encoding.
      PubDate: 2017-05-12
      DOI: 10.1007/s10586-017-0895-3
       
  • Space–time visualization analysis of bus passenger big data in
           Beijing
    • Authors: Jianqin Zhang; Zhihong Chen; Yaqiong Liu; Mingyi Du; Weijun Yang; Liang Guo
      Abstract: It is possible to quantify individual motion trajectories with the rapid development of sensor applications such as mobile positioning and wireless communication, and the characteristics like a large number, long time series and fine spatiotemporal granularity of GPS location data, bus IC data, and mobile phone data provide a hopeful premise for the study of human behavior. Based on a large amount of mobile information equipment, the effective mining of these data and the use of reasonable processing methods can make the processing results closer to reflect the actual human behavior patterns, and better serve the real traffic life. In this paper, by discussing the results of previous studies on human mobility, spatial interpolation method is used to discrete bus passenger flow obtained from big data of Beijing bus IC card into the continues area distribution, and we analyze the changed trend of passenger flow in Beijing of the whole day by utilizing the Spatial-temporal method. To a certain extent, the analysis of urban bus passenger distribution studied from Beijing bus IC data can understand the rules of human behavior and provide reliable data guidance for reasonable decision-making on Beijing passenger traffic planning, such like solving problem effectively that the number of bus passenger and the number of bus station does not match.
      PubDate: 2017-05-12
      DOI: 10.1007/s10586-017-0890-8
       
 
 
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