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نتیجه جستجو - سیستم های توزیع شده

تعداد مقالات یافته شده: 11
ردیف عنوان نوع
1 Efficient techniques for time-constrained information dissemination using location-based social networks
تکنیک های کارآمد برای زمان محدود انتشار اطلاعات محرمانه با استفاده از شبکه های اجتماعی مبتنی بر مکان-2017
Social networks have undergone an explosive growth in recent years. They constitute a central part of users everyday lives as they are used as major tools for the spread of information, ideas and notifications among the members of the network. In this work we investigate the use of location-based social networks as a medium of emergency notifica tion, for efficient dissemination of emergency information among members of the social network under time constraints. Our objective is the following: given a location-based social network comprising a number of mobile users, the social relationships among the users, the set of recipients, and the corresponding timeliness requirements, our goal is to select an appropriate subset of users so that the spread of information is maximized, time constraints are satisfied and costs are considered. We propose LATITuDE, our system that investigates the interactions among the members of the social network to infer their social relationships, and develop scalable dissemination mechanisms that select the most efficient set of users to initiate the dissemination process in order to maximize the information reach among the appropriate receivers within a time window. Our detailed experimental results illustrate that our approach is practical, effectively addresses the problem of informing the appropriate set of users within a deadline when an emergency event occurs, uses a small number of messages, and consistently outperforms its competitors.
Keywords: Distributed systems | Social networks | Information dissemination
مقاله انگلیسی
2 MidHDC: Advanced topics on middleware services for heterogeneous distributed computing: Part 2✩
MidHDC: Advanced topics on middleware services for heterogeneous distributed computing: Part 2-2017
Currently distributes systems support different computing paradigms like Cluster Computing, Grid Computing, Peer-to-Peer Computing, and Cloud Computing all involving elements of heterogeneity. These computing distributed systems are often characterized by a variety of resources that may or may not be coupled with specific platforms or environments. All these topics challenge today researchers, due to the strong dynamic behavior of the user communities and of resource collections they use. The second part of this special issue presents advances in allocation algorithms, service selection, VM consolidation and mobility policies, scheduling multiple virtual environments and scientific workflows, optimization in scheduling process, energy-aware scheduling models, failure Recovery in shared Big Data processing systems, distributed transaction processing middleware, data storage, trust evaluation, information diffusion, mobile systems, integration of robots in Cloud systems.
Keywords: Middleware services | Resource management | Mobile computing | Cloud computing | HPC | Heterogeneous distributed systems
مقاله انگلیسی
3 Improving the robustness and performance of parallel joins over distributed systems
بهبود کارایی و کارایی اتصالات موازی در سیستم های توزیع شده-2017
High-performance data processing systems typically utilize numerous servers with large amounts of memory. An essential operation in such environment is the parallel join, the performance of which is critical for data intensive operations. In many real-world workloads, data skew is omnipresent. Techniques that do not cater for the possibility of data skew often suffer from performance failures and memory problems. State-of-the-art methods designed to handle data skew propose new ways to distribute computation that avoid hotspots. However, this comes at the expense of global collection of statistics, redundant computation, duplication of data or increased network communication. In this light, performance could be further improved by removing the dependency on global skew knowledge and broadcasting. In this paper, we propose a new method called PRPQ (partial redistribution & partial query), with targets for efficient and robust joins with large datasets over high performance clusters. We present the detailed implementation of our approach and compare its performance with current implementations. The experimental results demonstrate that the proposed algorithm is scalable and robust and can also outperform the state-of-the-art approach with less network communication, figures that confirm our theoretical analysis.
Keywords: Parallel joins | Data skew | Robust | High performance computing
مقاله انگلیسی
4 Persisting big-data: The NoSQL landscape
تداوم داده های بزرگ: چشم انداز NoSQL-2017
The growing popularity of massively accessed Web applications that store and analyze large amounts of data, being Facebook, Twitter and Google Search some prominent examples of such applications, have posed new requirements that greatly challenge tra ditional RDBMS. In response to this reality, a new way of creating and manipulating data stores, known as NoSQL databases, has arisen. This paper reviews implementations of NoSQL databases in order to provide an understanding of current tools and their uses. First, NoSQL databases are compared with traditional RDBMS and important concepts are explained. Only databases allowing to persist data and distribute them along different computing nodes are within the scope of this review. Moreover, NoSQL databases are divided into different types: Key-Value, Wide-Column, Document-oriented and Graph oriented. In each case, a comparison of available databases is carried out based on their most important features.
Keywords:NoSQL databases|Relational databases|Distributed systems|Database persistence|Database distribution|Big data
مقاله انگلیسی
5 A Multi-Agent Case-Based Reasoning Architecture for Phishing Detection
معماری استنتاجی مبتنی بر مورد چند عاملی برای تشخیص سرقت اطلاعات -2017
Security threats are becoming very sophisticated and pervasive everywhere. Phishing threats in particular has a changeable nature and short life cycle that complicates the detection process. In this paper, we introduce a Multi-Agent System (MAS) as an adaptive intelligent technique that acts on top of distributed Case-Based Reasoning (CBR) Phishing Detection Systems (CBR-PDSs) as a Phishing Detection System Architecture (PDSA) that runs on large scale globally to constitute a robust worldwide Phishing Threat Intelligence (PTI) environment. The global collaborations of PTI introduces a proactive phishing detection technique, quarantines phishing threats via global threats sharing, and minimizes users’ susceptibilities to hard-to-detect spear or advanced phishing attacks. Also, combining two intelligent systems in a unified interactive architecture facilitates the prediction process, increases the accuracy rate, easily tackles the dynamic and changeable behaviors of advanced phishing threats, and minimizes the false negative rate as well. The proposed architecture illustrates the consolidated interaction between intelligent agents and distributed CBR-PDSs in a PTI framework.
Keywords: Phishing Detection | Agents Technology | Case-Based Reasoning | Distributed Systems
مقاله انگلیسی
6 Persisting big-data: The NoSQL landscape
تداوم داده های بزرگ :چشم انداز NoSQL-2017
The growing popularity of massively accessed Web applications that store and analyze large amounts of data, being Facebook, Twitter and Google Search some prominent examples of such applications, have posed new requirements that greatly challenge tra ditional RDBMS. In response to this reality, a new way of creating and manipulating data stores, known as NoSQL databases, has arisen. This paper reviews implementations of NoSQL databases in order to provide an understanding of current tools and their uses. First, NoSQL databases are compared with traditional RDBMS and important concepts are explained. Only databases allowing to persist data and distribute them along different computing nodes are within the scope of this review. Moreover, NoSQL databases are divided into different types: Key-Value, Wide-Column, Document-oriented and Graph oriented. In each case, a comparison of available databases is carried out based on their most important features.
Keywords:NoSQL databases|Relational databases|Distributed systems|Database persistence|Database distribution|Big data
مقاله انگلیسی
7 Failure Analysis and Prediction for Big-Data Systems
تحلیل شکست و پیش بینی برای سیستم های داده های بزرگ-2016
Motivated by the high complexity of today’s datacenters, a large body of studies tries to understand workloads and resource utilization in datacenters. However, there is little work on exploring unsuccessful job and task executions. In this article, we study and predict three types of unsuccessful executions in traces of a Google datacenter, namely fail, kill, and eviction. We first quantitatively show their strongly negative impact on machine time and the resulting task slowdown. We analyze patterns of unsuccessful jobs and tasks, particularly focusing on their interdependencies, and we uncover their root causes by inspecting key workload and system attributes. Furthermore, we develop three on-line prediction models that can classify jobs and events into four classes upon arrival time, using independent or nested Neural Networks. We explore different combinations of feature sets and techniques to reduce the computational overhead. Our evaluation results show that the proposed models can accurately classify 94.4% of jobs and 76.8% of events into four classes.
Index Terms: Distributed Systems | Reliability | availability and serviceability | Neural nets.
مقاله انگلیسی
8 Privacy in Internet of Things: A Model and Protection Framework
حفظ حریم خصوصی در اینترنت اشیاء: مدل و چارچوب حفاظت-2015
A new form of computation is being evolved to include massive number of diverse set of conventional computing systems, sensors, devices, equipments, software and information services and apps. This new form of computing environment is known as the “Internet-of-Things” (IoT). The adoption of IoT is fast and the “things” are becoming integral part of people day-to-day life as well as essential elements in the businesses everyday activities and processes. Open characteristics of IoT environments raises privacy concern as “things” are autonomous with some degree of authority to sharing their capabilities and knowledge to fulfil their individual or collective tasks. As such privacy becomes central and an inherit computational aspect of the “things”. The work presented here is based on modelling IoT as Cooperative Distributed Systems (CDS). It proposes a novel approach of analysing and modelling privacy concepts and concerns. Privacy protection is captured as a form of “sensitive information” management at the interaction level. A privacy protection management framework for CDS at the interaction level is proposed. The application of the framework has been demonstrated by extending Contract Net Protocol (CNP) to support privacy protection for CDS.
Keywords: Privacy | IoT | Cooperative Distributed Systems (CDS)
مقاله انگلیسی
9 Trends in big data analytics
روندهایی در تجزیه و تحلیل داده های بزرگ-2014
One of the major applications of future generation parallel and distributed systems is in big-data analytics. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size. Beyond their sheer magnitude, these datasets and associated applications’ considerations pose significant challenges for method and software development. Datasets are often distributed and their size and privacy considerations warrant distributed techniques. Data often resides on platforms with widely varying computational and network capabilities. Considerations of fault-tolerance, security, and access control are critical in many applications (Dean and Ghemawat, 2004; Apache hadoop). Analysis tasks often have hard deadlines, and data quality is a major concern in yet other applications. For most emerging applications, data-driven models and methods, capable of operating at scale, are as-yet unknown. Even when known methods can be scaled, validation of results is a major issue. Characteristics of hardware platforms and the software stack fundamentally impact data analytics. In this article, we provide an overview of the stateof-the-art and focus on emerging trends to highlight the hardware, software, and application landscape of big-data analytics. Keywords: Big-data Analytics Data centers Distributed systems
مقاله انگلیسی
10 روند تجزیه و تحلیل داده های بزرگ
سال انتشار: 2014 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 43
یکی از کاربردهای عمده نسل آتی سیستم های موازی و توزیع شده، مربوط به تحلیل داده های بزرگ است. مخازن داده برای چنین کاربردهایی امروزه بیش از چندین اگزابایت بوده و به سرعت نیز در حال افزایش هستند. علیرغم حجم بسیار زیاد این مخازن، این دیتاست ها و همچنین اپلیکیشن های نظیر آنها، چالش های عمده ای را برای متدها و نرم افزارهای برنامه نویسی مربوطه ایجاد کرده اند. دیتاست ها معمولا توزیع شده بوده و نیز حجم آنها و دسترسی مجاز به آنها توسط تکنیک های توزیع شده تضمین شده است. داده ها معمولا روی یک پلت فورم با قابلیت محاسباتی و شبکه ای بالا، مقیم هستند. توجه به میزان تحمل خطا، امنیت، و کنترل دسترسی موضوع مهمی در بسیاری از کاربردهاست (Dean and Ghemawat, 2004; Apache hadoop). تسک های (task) تحلیلی معمولا ضرب العجل های معینی دارند و نیز در آنها کیفیت داده ها مهم ترین مخاطره نسبت به دیگر کاربردهاست. برای بیشتر کاربردهای درحال ظهور، مدل ها و متدهای مبتنی بر داده، که قادر به عملیات در مقیاس های مختلف هستند، هنوز برایمان ناشناخته است. حتی درصورتی که متدهای شناخته شده مقیاس پذیر باشند، اعتبارسنجی نتایج آنها موضوع مهمی خواهد بود. مشخصات پلت فورم های سخت افزاری و نیز پشته های نرم افزاری، اساسا تحلیل داده ها را تحت تاثیر قرار داده اند. در این مقاله، ما با مرور به روزترین تکنولوژی، بررسی بر گرایش های در حال ظهور در در این زمینه خواهیم داشت تا براین اساس تشریحی بر سخت افزار، نرم افزار و دورنمای کاربردی تحلیل داده های بزرگ ارائه دهیم.
کلمات کلیدی: داده های بزرگ | تجزیه و تحلیل | مراکز داده | سیستم های توزیع شده
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