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مرکز اطلاعات علمی SID1
مرکز اطلاعات علمی SID
اسکوپوس
مرکز اطلاعات علمی SID
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strs
نویسندگان: 

RAHMATI BAHAREH | RAHMANI AMIR MASOUD

اطلاعات دوره: 
  • سال: 

    2017
  • دوره: 

    3
  • شماره: 

    2
  • صفحات: 

    75-80
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    15869
  • دانلود: 

    17196
چکیده: 

High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications.Sometimes accessing data becomes a bottleneck for the whole cloud workflow system and decreases the performance of the system dramatically. Job scheduling and data replication are two important techniques which can enhance the performance of data-intensive applications. It is wise to integrate these techniques into one framework for achieving a single objective. In this paper, we integrate data replication and job scheduling with the aim of reducing response time by reduction of data access time in cloud computing environment.This is called data replication-based scheduling (DRBS). Simulation results show the effectiveness of our algorithm in comparison with well-known algorithms such as random and round-robin……

آمار یکساله:  

بازدید 15869

دانلود 17196 استناد 0 مرجع 0
نویسندگان: 

Sooezi Nafise | ABRISHAMI SAEID | Lotfian Majid

اطلاعات دوره: 
  • سال: 

    2018
  • دوره: 

    1
  • شماره: 

    1
  • صفحات: 

    33-42
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    12476
  • دانلود: 

    7413
چکیده: 

Nowadays, cloud computing and other distributed computing systems have been developed to support various types of workflows in applications. Due to the restrictions onthe use ofone cloud provider, the concept of multiple clouds as been proposed. Inmultipleclouds, schedulingworkflowswithlarge amounts ofdata is a wellknownNP-Hard problem. The existing scheduling algorithms have not paid attention to the data dependency issues and their importance in scheduling criteria such as time and cost. In this paper, we propose a communicationbased algorithm for workflows with huge volumes of data in a multi-cloud environment. The proposed algorithm changes the definition of the Partial Critical Paths(PCP) to minimize the cost of workflow executionwhile meeting a user defined deadline.

آمار یکساله:  

بازدید 12476

دانلود 7413 استناد 0 مرجع 0
نویسندگان: 

اطلاعات دوره: 
  • سال: 

    2017
  • دوره: 

    34
  • شماره: 

    3
  • صفحات: 

    0-0
تعامل: 
  • استنادات: 

    315
  • بازدید: 

    3247
  • دانلود: 

    9195
کلیدواژه: 
چکیده: 

آمار یکساله:  

بازدید 3247

دانلود 9195 استناد 315 مرجع 0
گارگاه ها آموزشی
نویسندگان: 

اطلاعات دوره: 
  • سال: 

    2020
  • دوره: 

    150
  • شماره: 

    -
  • صفحات: 

    0-0
تعامل: 
  • استنادات: 

    2
  • بازدید: 

    0
  • دانلود: 

    114
کلیدواژه: 
چکیده: 

آمار یکساله:  

بازدید 0

دانلود 114 استناد 2 مرجع 0
اطلاعات دوره: 
  • سال: 

    2019
  • دوره: 

    0
  • شماره: 

    5
تعامل: 
  • بازدید: 

    1470
  • دانلود: 

    0
چکیده: 

MAJOR PART OF INTERNET USERS ARE DEVICES WHICH ARE CONNECTED TO EACH OTHER ON THE INTERNET AND ARE EXCHANGING DATA WITH INTERNET BROKERS TO RECEIVE REQUESTED SERVICES. MANAGING AND ACCOUNTING WELL TO IOT REQUESTS NEEDS MAXIMUM PROCESSING POWER, SPEED IN DATA TRANSFER AND PROPER COMBINING SERVICES IN MINIMUM TIME. THIS MANY DEVICES IN IOT, MADE SOLVING PROBLEMS IN THIS AREA TO USE ABILITIES AND FACILITIES OF cloud environment. HENCE COMBINING SERVICES IN cloud environment IS PAID ATTENTION RECENTLY. IN THIS RESEARCH WE WANT TO GIVE AN ALGORITHM WITH APPROACH OF IMPROVING FACTORS PROPOUNDED IN THE PROBLEM COMBINING SERVICE COMPOSITION PROBLEM LIKE NUMBER OF cloudS INVOLVED IN GIVING SERVICES, NUMBER OF SERVICES STUDIED BEFORE FULFILLING USERS REQUESTS AND LOAD BALANCE BETWEEN cloudS. IN THIS PAPER WE USE THE FACTOR, SIMILARITY MEASURE, TO FIND THE MOST SUITABLE cloud AND COMPOSITION PLAN IN EACH PHASE WHICH IN ADDITION TO IMPROVING QOS METRICS PROPOUNDED IN PREVIOUS PAPERS, IT CAUSED IMPROVING QOS METRIC OF LOAD BALANCING BETWEEN cloudS, PREVENTION OF FORMATION OF BOTTLENECK IN cloudS ENTRANCE, DECREASING THE PROBABILITY OF TEMPORARILY FAILING OF ANY OF cloudS AND CONSEQUENTLY INCREASING THE USERS’ SATISFACTION.

آمار یکساله:  

بازدید 1470

دانلود 0
نویسندگان: 

JUNIOR W.

اطلاعات دوره: 
  • سال: 

    2017
  • دوره: 

    94
  • شماره: 

    -
  • صفحات: 

    93-108
تعامل: 
  • استنادات: 

    315
  • بازدید: 

    8045
  • دانلود: 

    9195
کلیدواژه: 
چکیده: 

آمار یکساله:  

بازدید 8045

دانلود 9195 استناد 315 مرجع 0
strs
نویسندگان: 

ABAZARI FARZANEH | ANALOUI MORTEZA | TAKABI HASSAN

اطلاعات دوره: 
  • سال: 

    2017
  • دوره: 

    9
  • شماره: 

    3
  • صفحات: 

    25-36
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    15111
  • دانلود: 

    6130
چکیده: 

cloud computing is a dynamic environment that offers variety of on-demand services with low cost. However, customers face new security risks due to shared infrastructure in the cloud. Co-residency of virtual machines on the same physical machine, leads to several threats for cloud tenants. cloud administrators are often encountered with a more challenging problem since they have to work within a fixed budget for cloud hardening. The problem is how to select a subset of countermeasures to be within the budget and yet minimize the residual damage to the cloud caused by malicious VMs. We address this problem by introducing a novel multi-objective attack response system. We consider response cost, co-residency threat, and virtual machines interactions to select optimal response in face of the attack. Optimal response selection as a multi-objective optimization problem calculates alternative responses, with minimum threat and cost. Our method estimates threat level based on the collaboration graph and suggests proper countermeasures based on threat type with minimum cost. Experimental result shows that our system can suggest optimal responses based on the current state of the cloud.

آمار یکساله:  

بازدید 15111

دانلود 6130 استناد 0 مرجع 0
نویسندگان: 

Pourghaffari A. | BARARI M.

اطلاعات دوره: 
  • سال: 

    2019
  • دوره: 

    10
  • شماره: 

    2
  • صفحات: 

    177-188
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    15002
  • دانلود: 

    17742
چکیده: 

With advances in virtualization technology, cloud computing has become the most powerful and promising platform for business, academia, public and government organizations. Scheduling these workflows and load balancing to get better success rate becomes a challenging issue in cloud computing. In this paper, we used Cats and Dragonfly Optimization (CSO-DA) algorithm to balance the Load in the process of allocating resources to virtual machines in cloud computing in order to improve the speed and accuracy of scheduling. The proposed method consists of the following steps: initialization of the algorithm and cloud computing, determining the number of virtual machines and the number of tasks, implementing a dragonfly optimization algorithm for choosing the best host and implementing a cat collapse algorithm for balancing the load and Schedule tasks between virtual machines. Our experiments show that as far as run time, response time, task immigration and significant load balances are concerned, our proposed model combining cat and dragonfly optimization algorithms achieved better performance in allocating resources and load balance between virtual machines than other methods.

آمار یکساله:  

بازدید 15002

دانلود 17742 استناد 0 مرجع 0
نویسندگان: 

MANSOURI N. | JAVIDI M.M.

اطلاعات دوره: 
  • سال: 

    2019
  • دوره: 

    15
  • شماره: 

    3
  • صفحات: 

    282-293
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    16818
  • دانلود: 

    10097
چکیده: 

As grow as the data-intensive applications in cloud computing day after day, data popularity in this environment becomes critical and important. Hence to improve data availability and efficient accesses to popular data, replication algorithms are now widely used in distributed systems. However, most of them only replicate the static number of replicas on some requested chosen sites and it is obviously not enough for more reasonable performance. In addition, the failure of request is one of the most common issue within the data centers. To compensate these problems, we, propose a new data replication strategy to provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage. The proposed replication strategy has three different steps which are the identification of data file to replicate, placing new replicas, and replacing replicas. In the first step, it finds the most requested files for replication. In the second step, it selects the best site by consideration of the frequency of requests for replica, the last time the replica was requested, failure probability, centrality factor and storage usage) for storing new replica to reduce access time. In the third step, the replacement decision is made in order to provide better resource usage. The proposed strategy can ascertain the importance of valuable replicas based on the number of accesses in future, the availability of the file, the last time the replica was requested, and size of replica. Our proposed algorithm evaluated by cloudSim simulator and results confirmed the better performance of hybrid replication strategy in terms of mean response time, effective network usages, replication frequency, degree of imbalance, and number of communications.

آمار یکساله:  

بازدید 16818

دانلود 10097 استناد 0 مرجع 0
نویسندگان: 

قبائی آرانی مصطفی

اطلاعات دوره: 
  • سال: 

    1399
  • دوره: 

    50
  • شماره: 

    3 (پیاپی 93)
  • صفحات: 

    1329-1341
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    24
  • دانلود: 

    30
چکیده: 

کشسانی، به عنوان یک از مهم ترین ویژگی هایی محسوب می شود که فناوری رایانش ابری را از دیگر فناوری های رایانش توزیعی، متمایز می کند. این ویژگی، از این حقیقت بهره می گیرد که فرایند تخصیص دهی منابع، به عنوان رویه ای محسوب می شود که می توان آن را به صورت پویا اجرا نمود. ارایه راهکاری کارامد برای بهبود خاصیت کشسانی هم برای ارایه دهندگان و هم برای کاربران سرویس های رایانش ابری مفید و کارآمد واقع خواهد شد. ارایه دهندگان خواهند توانست با راهکاری که در این مقاله طراحی، ارزیابی و توسعه داده خواهد شد، خاصیت کشسانی سرویس های ابری خود را ارزیابی کرده و آن ها را بهبود بخشیده و مزیت کمی یا کیفی خود در رقابت با سایر رقبا را افزایش دهند. در این مقاله، راهکاری ترکیبی برای بهبود خاصیت کشسانی با استفاده مدیریت بافر و مدیریت متمرکز کشسانی ارایه می شود. مدیریت بافر وظیفه کنترل صف ورودی درخواست را به عهده دارد و مدیریت کشسانی با استفاده از یادگیری تقویتی، کنترل خاصیت کشسانی سیستم را به عهده دارد. موثر بودن راهکار پیشنهادی تحت سه بار کاری واقعی Google Cluster، Yahoo Cluster و Wikipedia ارزیابی شده است. نتایج آزمایشات نشان می دهد که راهکار پیشنهادی در مقایسه با دو راهکار CTMC و ControCity موجب کاهش زمان پاسخگویی 15. 2 درصد، و افزایش بهره وری به میزان 13. 2 درصد و افزایش خاصیت کشسانی را درحد 19. 8 درصد نشان می دهد.

آمار یکساله:  

بازدید 24

دانلود 30 استناد 0 مرجع 0
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