Social phishers cleverly devise stringent methods to secretly obtain login-names and passwords by forming seemingly friendly connections through microblogs and various social media platforms. They adapt these techniqu...
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This experimental work examines data movement in molecular dynamics (MD) workflows, comparing the Dynamic and Asynchronous Data Streamliner (DYAD) middleware with traditional, industry-standard I/O systems such as XFS...
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ISBN:
(纸本)9798350364613;9798350364606
This experimental work examines data movement in molecular dynamics (MD) workflows, comparing the Dynamic and Asynchronous Data Streamliner (DYAD) middleware with traditional, industry-standard I/O systems such as XFS and Lustre. DYAD moves MD simulation frames to analytics processes, providing enhanced flexibility and efficiency for dynamic data transfers and in situ analytics. At the same time, traditional I/O storage systems provide durability and scalability for high-performance computing (HPC) systems. The study integrates MD workflows with common simulation codes, facilitating immediate capture and transfer of MD frames to a staging area. It explores various molecular models, from simple to complex, assessing data management performance and scalability. Different producer-consumer pairs, molecular models, and data transaction frequency enable testing across small to large-scale HPC scenarios, from single-node configurations to large, distributed environments. The findings reveal that adaptive mechanisms for minimizing synchronization, direct network communication between producer and consumer processes, and optimizations of both data movement and synchronization are crucial for performance and scalability in MD workflows.
This paper studies the network based distributed mobile cloud cooperation architecture and QoS guarantee mechanism of end-to-end computing and control. By implanting cloud computing resources in the mobile communicati...
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In this research paper, we explore the essential role of High Performance computing (HPC) in the current technological era, highlighting its extensive use in various sectors, while also considering growing alarm over ...
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ISBN:
(纸本)9798350363074;9798350363081
In this research paper, we explore the essential role of High Performance computing (HPC) in the current technological era, highlighting its extensive use in various sectors, while also considering growing alarm over its environmental footprint. High performance computingsystems are essential for managing large data sets and solving complex challenges. However, their significant contribution to escalating energy consumption and carbon emissions in the information and communication technology (ICT) sector cannot be ignored. Our study identifies the increasing energy demands and environmental challenges associated with HPC activities, including resource use, electrical waste and greenhouse gas emissions. It highlights the importance of understanding these environmental impacts in detail. It also contributes to the ongoing dialogue on sustainable computing, promoting a harmonious future where technological progress and environmental sustainability can coexist in unison.
This work continues a cycle of research grounded in the foundational theories of granular computing introduced by Zadeh, rough set theory proposed by Pawlak, and particularly the concept-dependent granulation methodol...
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The fifth generation of cellular communications (5G) provides enough performance to carry on scenarios that require low latency such as robot control remote computing. In this work, it is presented an experiment focus...
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ISBN:
(纸本)9798350319347;9798350319354
The fifth generation of cellular communications (5G) provides enough performance to carry on scenarios that require low latency such as robot control remote computing. In this work, it is presented an experiment focused on the trajectory management of a 5G connected arm robot end-effector with image processing in the Edge. This use case, which is integrated into a Non-Public 5G network (NPN), provides several improvements in terms of network configuration to enable the development of Multi-Access Edge computing (MEC) use cases by enhancing uplink throughput.
This research aims to explore and develop original approaches for improving the scalability and efficiency of distributed network computingsystems. The escalating demand for high-performance computing and the widespr...
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ISBN:
(纸本)9783031671944;9783031671951
This research aims to explore and develop original approaches for improving the scalability and efficiency of distributed network computingsystems. The escalating demand for high-performance computing and the widespread integration of interconnected devices present a critical challenge in optimizing resource allocation and load balancing within distributed networks. The study will investigate cutting-edge algorithms, employ machine learning techniques, and devise adaptive strategies to dynamically distribute computing tasks across network nodes. The primary objective is to enhance system scalability, minimize response times, and maximize resource utilization, contributing significantly to the progression of network technologies in distributedcomputing environments. The research findings are expected to have substantial implications for various applications, including cloud computing, edge computing, and Internet of Things (IoT) ecosystems.
In recent years, companies have shifted their software systems from monolithic architectures to distributed architectures such as microservices. It is not a silver bullet that solves growing complexity, and technical ...
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ISBN:
(纸本)9781665464598
In recent years, companies have shifted their software systems from monolithic architectures to distributed architectures such as microservices. It is not a silver bullet that solves growing complexity, and technical debt still accumulates during development and maintenance activities. Researchers have defined suites of anti-patterns to detect technical debt in monolithic systems, but these anti-patterns cannot be directly applied to distributedsystems. This paper presents a method to identify anti-patterns in distributedsystems using heterogeneous dependencies. To do this, we first identify multiple types of explicit and implicit entities and dependencies that can be extracted from distributedsystems. Using these dependencies, we create unified models to represent distributedsystems and study the models to identify and define new anti-patterns based on fundamental design principles. In our preliminary research, we identified and defined three new anti-patterns and revised three existing anti-patterns for two systems. We have confirmed that two of these anti-patterns are real problems that cannot be captured by existing approaches, and these results may facilitate further research into automated anti-pattern detection in distributedsystems.
The Internet of Things (IoT) driven latency-critical applications are deployed on lightweight Micro-Clouds at the network's edge. Renting physical space from geographically distributed colocation datacenters conne...
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ISBN:
(纸本)9798350304817
The Internet of Things (IoT) driven latency-critical applications are deployed on lightweight Micro-Clouds at the network's edge. Renting physical space from geographically distributed colocation datacenters connected via a Wide Area Network (WAN) is a cost-effective way of deploying Micro-Clouds, despite WANs' dynamic communication latency from traffic congestion. However, this deployment approach can limit Micro-Clouds to operate within a soft power budget, as colocation datacenter providers utilize it to add more servers and lower capital costs through oversubscribing power infrastructure. As a result, Micro-Clouds use extreme energy reduction measures like power capping and task throttling to address power overdraw events, where power consumption exceeds soft power budget limits, which reduces the performance of latency-critical applications. We propose a solution where a dynamic power budget can be achieved by adding renewable energy sources to the existing soft power budget without upgrading power delivery systems. To take advantage of this, we propose a dynamic, decentralized task-scheduling algorithm called DEMOTS. DEMOTS effectively utilizes the available dynamic power budget in a WAN with varying degrees of network traffic congestion, thereby avoiding the need for extreme energy reduction measures. We implement DEMOTS on a simulation test-bed. Compared to state-of-the-art baseline using MCOP for decentralized task-scheduling in Micro-Clouds, DEMOTS reduces Power Overdraw Impact up to 19%, Task Latency Increase Impact up to 47%, and Task Schedule Time Impact up to 49%.
The application of distributed Intrusion Detection System (DIDS) in campus network is a security technology which aims at monitoring and analyzing network attacks. With the increasing number of campus network users an...
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