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the Rising Prospects of Cloud Robotic applications

The Rising Prospects of Cloud Robotic Applications

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IEEE international conference on Computational Cybernetics

作者： S. Jordán T. Haidegger L. Kovács I. Felde I. Rudas Budapest University of Technology and Economics (BME) óbuda University (óU)

ISBN: (纸本)9781479900626

Cloud Robotics is an emerging field within robotics, currently covering various application domains and robot network paradigms. this paper provides a structured, systematic overview of the numerous definitions, concepts and technologies linked to Cloud Robotics and cloud technologies in a broader sense. It also presents a roadmap for the near future, describing development trends and emerging application areas. Cloud Robotics may have a significant role in the future as an explicitly human-centered technology, capable of addressing the dire needs of our society.

关键词： cloud robotics distributed systems cloud computing networked robotics

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WOW: Self-Organizing Wide Area Overlay Networks of Virtual Workstations

WOW: Self-Organizing Wide Area Overlay Networks of Virtual W...

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international Symposium on High Performance distributed computing

作者： A. Ganguly A. Agrawal P.O. Boykin R. Figueiredo Advanced Computing and Information Systems Laboratory University of Florida Gainesville FL USA

this paper describes WOW, a distributed system that combines virtual machine, overlay networking and peer-to-peer techniques to create scalable wide-area networks of virtual workstations for high-throughput computing. the system is architected to: facilitate the addition of nodes to a pool of resources through the use of system virtual machines (VMs) and self-organizing virtual network links; to maintain IP connectivity even if VMs migrate across network domains; and to present to end-users and applications an environment that is functionally identical to a local-area network or cluster of workstations. We describe a novel, extensible user-level decentralized technique to discover, establish and maintain overlay links to tunnel IP packets over different transports (including UDP and TCP) and across firewalls. We also report on several experiments conducted on a testbed WOW deployment with 118 P2P router nodes over PlanetLab and 33 VMware-based VM nodes distributed across six firewalled domains. Experiments show that the latency in joining a WOW network is of the order of seconds: in a set of 300 trials, 90% of the nodes self-configured P2P routes within 10 seconds, and more than 99% established direct connections to other nodes within 200 seconds. Experiments also show that the testbed delivers good performance for two unmodified, representative benchmarks drawn from the life-sciences domain. the testbed WOW achieves an overall throughput of 53 jobs/minute for PBS-scheduled executions of the MEME application (with average single-job sequential running time of 24.1s) and a parallel speedup of 13.5 for the PVM-based fastDNAml application. Experiments also demonstrate that the system is capable of seamlessly maintaining connectivity at the virtual IP layer for typical client/server applications (NFS, SSH, PBS) when VMs migrate across a WAN

关键词： Workstations Peer to peer computing Voice mail Virtual machining Computer networks distributed computing Local area networks TCPIP Testing Virtual manufacturing

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Simulating Cyber Attacks and Designing Malware using Python

Simulating Cyber Attacks and Designing Malware using Python

引用

international conference on Signal Processing and Integrated Networks (SPIN)

作者： Akash Ankit Shubham Inder Anuj Sharma Rahul Johari Deo Prakash Vidyarthi SWINGER: Security Wireless IoT Network Group of Engineering and Research University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Dwarka New Delhi India Royal Melbourne Institute of Technology (RMIT University) Melboume Victoria Australia Parallel and Distributed System Lab School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

In this Internet era, we have become heavily dependent on the World Wide Web and it has become a basic amenity for humans. A normal user can be trapped easily in this vicious web if not careful enough. It is a field that requires users to be on their toes every time they try to connect to this enormous interconnection of networks. Reports and Surveys have said that in the coming years, Cybercrime could become the biggest threat. In this proposed work, the authors have deployed applications and designed malware for the purpose of simulating various kinds of cyber-attacks so that they could study their effects & affects and ultimately devise solutions to resolve the vulnerabilities in a system. these applications included networking concepts & protocols and a software based keylogger which was developed with no malicious intent, but to analyse the architectural view or design of a malware and to study the stages of a malware attack like entry, distribution, exploitation, infection and execution. Efforts have been made to demonstrate spooting attacks with an idea of identifying vulnerabilities and security loopholes in a particular system that can be exploited by an attacker if not resolved within time.

关键词： Surveys Protocols Malware Internet Web sites Security Signal resolution

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Prototyping of Low-Cost Configurable Sparse Neural Processing Unit with Buffer and Mixed-Precision Reshapeable MAC Array

Prototyping of Low-Cost Configurable Sparse Neural Processin...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Binyi Wu Wolfgang Furtner Bernd Waschneck Christian Mayr Faculty of Electrical and Computer Engineering Technische Universit¨at Dresden Dresden Germany Division of Power and Sensor Systems Infineon Technologies Munich Germany Centre for Tactile Internet with Human-in-the-loop (CeTI) Technische Universität Dresden Dresden Germany

More recently, it has become possible to run deep learning algorithms on edge devices such as microcontrollers due to continuous improvements in neural network optimization algorithms such as quantization and neural architecture search. Nonetheless, most of the embedded hardware available today still falls short of the requirements of running deep neural networks. As a result, specialized processors have emerged to improve the inference efficiency of deep learning algorithms. However, most are not for edge applications that require efficient and low-cost hardware. therefore, we design and prototype a low-cost configurable sparse Neural Processing Unit (NPU). the NPU has a built-in buffer and a reshapable mixed-precision multiply-accumulator (MAC) array. the computing and memory resources of the NPU are parameterized, and different NPUs can be derived. Besides, users can also conFigure the NPU at runtime to fully utilize the resources. In our experiments, the 200MHz NPU with only 32 MACs is more than 32 times faster than the 400MHzSTM32H7 when inferring MobileNet-Vl. Besides, the yielded NPUs can achieve roofline or even beyond roofline performance. the buffer and reshapeable MAC array push the NPU’s attainable performance to the roofline, while the feature of supporting sparsity allows the NPU to obtain performance beyond the roofline.

关键词： Deep learning Runtime Quantization (signal) Program processors Neural networks Random access memory Prototypes

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A distributed graph based approach for rough classifications considering dominance relations between overlapping classes

A distributed graph based approach for rough classifications...

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international conference on Intelligent Systems: theories and applications (SITA)

作者： K Laghmari M Ramdani C Marsala FSTM Laboratoire Informatique de Mohammedia Mohammedia Maroc LIP6 UMR 7606 UPMC Univ Paris 06 CNRS Paris France

Several data from real world applications involves overlapping classes. Data is allowed to belong to multiple classes with different membership degrees. In this paper, we explore a different concept characterizing social networks, documents, and most of biological and chemical datasets: data could have multiple classes, but dominant classes are better noticed than dominated classes. For example, a document could discuss economy and politics, but it would be more focused on politics. A molecule could have multiple odors, but experts could notice some odors better than others. We are interested in this type of data, where a dominance relation exists between classes. Experts could easily make mistakes because dominated classes are hardly noticed. Data incoherence is a serious problem but not the only one. there is too much irrelevant and redundant attributes. Unfortunately this increases the computational time of generating classifiers. Our first challenge is to find an adapted model to overlapping classes considering dominance relations. the second challenge is to find the most relevant attributes. Finally the third challenge is to ensure that the approach gives results in an acceptable time. We address those challenges by taking advantage of the rough set theory, which is suited for incoherent data and allows multiple classes and attributes selection. the proposed approach works in a parallel and decentralized way to reduce the computational time. We tested it on real chemical data and the collected results are very promising.

关键词： Approximation methods Training Databases Decision trees Servers Chlorine Symmetric matrices

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Artificial Intelligence in Smart Mobile Communication Systems: A Review

Artificial Intelligence in Smart Mobile Communication System...

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IEEE international conference on Emerging & Sustainable technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Adebajo-Akinpelu Victor O Moses Oluwafemi Onibonoje Ayodeji Olalekan Salau Department of Electrical/Electronics and Computer Engineering Afe Babalola Univerisity Ado-Ekiti Ado-Ekiti Nigeria Dept of Electrical/Electronics & Computer Engineering Afe Babalola University Ado Ekiti Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Communication and information service systems are undergoing rapid advancements driven by the evolution of telecommunications and computer technology. the convergence of these fields has led to significant growth in digital networks, which has spurred extensive research and exploration. However, optimizing the use of these networks with minimal additional costs—while integrating features such as video conferencing, email services, and remote database access— remains a substantial technological challenge. this study addresses the limitations of current mobile communication networks by exploring potential enhancements through the application of smart computing solutions, particularly artificial intelligence (AI). the research methodology involves a comprehensive review of existing mobile communication technologies and their integration with AI. this includes examining advancements in AI and machine learning (ML) as applied to mobile networks, with a focus on improving performance, flexibility, and automation. the results of the review indicate that AI and ML have significant potential to enhance network operations. By leveraging vast data generated within 5G systems, these technologies can optimize resource utilization, improve service quality, and support diverse emerging applications. Despite these advancements, challenges such as reliability, speed trade-offs, complexity, privacy, and security persist. the findings highlight the need for further research in AI, including deep neural network acceleration, parallel computing, cloud computing, and distributed deep learning systems. Such research is crucial for enabling mobile communication networks to achieve higher throughput and ultra-low latency. Conclusively, while AI-enabled communication systems offer promising solutions to many challenges, simplifying AI implementation is essential for practical deployment. this will ensure that future communication networks can effectively meet the growing demands and evolving

关键词： Deep learning Privacy Reviews 5G mobile communication parallel processing throughput Complexity theory Security Resource management Artificial intelligence

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Optimal Deployment of Heterogeneous Wireless Nodes in Integrated LTElWi-Fi Networks

Optimal Deployment of Heterogeneous Wireless Nodes in Integr...

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IEEE Annual Ubiquitous computing, Electronics & Mobile Communication conference (UEMCON)

作者： Noha A. Elmosilhy Ahmed M. Abd El-Haleem Mahmoud M. Elmesalawy Canadian International College (CIC) Cairo Egypt Faculty of Engineering Helwan University Cairo Egypt

Optimal placement of small cells in integrated LTE/Wi-Fi heterogeneous network architecture is considered one of the key approaches that can be used to increase the system capacity and enhance the coverage to meet the unexpected explosion of mobile data traffic. Co-operation and interworking between different Radio Access technologies (RATs) introduce the LTE/Wi-Fi Aggregation (LWA) which allows the traffic aggregation between Wi-Fi Access Point (WAP) and LTE small cell on the level of Radio Access Network (RAN). In this paper, the effectiveness of the optimal deployment of heterogeneous wireless small nodes in a hotspot zone is considered and explored. the deployment of different wireless small nodes is formulated as an optimization problem with the objective of (i) Maximizing the total system throughput while considering the minimum received Signal-to-Interference-plus-Noise Ratio (SINR)/Signal-to-Noise Ratio (SNR) requirements for LTE/Wi-Fi coverage (ii) Choosing the optimal number of small cells which can guarantee the coverage of the considered hotspot zone (iii) Choosing the optimal formation of WAPs Basic Service Sets (BSSs). the objective function is formulated as a Mixed Integer Non-Linear Programming (MINLP) problem and solved using genetic algorithm. the performance of the proposed optimal deployment approach is compared to the uniform distributed deployment algorithm in terms of system throughput in which a significant improvement is noticed when the proposed approach is adopted.

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Modelling distributed Fault-Tolerant High Availability Storage Cluster Based on Block-Chain Concepts for Tracking Scientific-Research Progress

Modelling Distributed Fault-Tolerant High Availability Stora...

引用

international IEEE conference on Intelligent Systems, IS

作者： Vladimir Valkanov Mihail Petrov Daniel Rusev Irina Radeva Faculty of Mathematics and Informatics University of Plovdiv "Paisii Hilendarski" Plovdiv Bulgaria Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (数字)9781728154565

ISBN: (纸本)9781728154572

the aim of the paper is to outline the prerequisites for the introduction of a model for integrating an intended interface platform for storing information regarding results and background information from scientific research, over a blockchain network. the state of the art will describe the actual concept of the technology and the main article will introduce the in-depth architecture of a software prototype GenBankChain, a distributed blockchain network for storing results of experiments and research data. the project is based over a research and the development of a concept for utilizing the existing infrastructure of the Institute for Plant Genetic Resources "K. Malkov", Sadovo, but the described model is based over existing concepts from the Block-chain research community and the resulting architecture can be used for building a class of applications based over this concept. the main purpose of the article is to address a practical approach for implementing a theoretical concept and to propose an implementation solution for a real-world problem.

关键词： Organizations Genetics Servers Software distributed databases Information services

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High Performance Database Processing

High Performance Database Processing

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international conference on Advanced Information Networking and applications (AINA)

作者： David Taniar Clayton School of Information Technology Monash University Clayton VIC Australia

the sizes of databases have seen exponential growth in the past, and such growth is expected to accelerate in the future, with the steady drop in storage cost accompanied by a rapid increase in storage capacity. Many years ago, a terabyte database was considered to be large, but nowadays they are sometimes regarded as small, and the daily volumes of data being added to some databases are measured in terabytes. In the future, petabyte and exabyte databases will be common. With such volumes of data, it is evident that the sequential processing paradigm will be unable to cope, for example, even assuming a data rate of 1 terabyte per second, reading through a petabyte database will take over 10 days. To effectively manage such volumes of data, it is necessary to allocate multiple resources to it, very often massively so. the processing of databases of such astronomical proportions requires an understanding of how high-performance systems and parallelism work. Besides the massive volume of data in the database to be processed, some data has been distributed across the globe in a Grid environment. these massive data centres are also a part of the emergence of Cloud computing, where data access has shifted from local machines to powerful servers hosting web applications and services, making data access across the Internet using standard web browsers pervasive. this adds another dimension to such systems. this talk, based on our recent published book [1], discusses fundamental understanding of parallelism in data-intensive applications, and demonstrates how to develop faster capabilities to support them. this includes the importance of indexing in parallel systems [2-4], specialized algorithms to support various query processing [5-9], as well as objectoriented scheme [10-12]. parallelism in databases has been around since the early 1980s, when many researchers in this area aspired to build large special-purpose database machines -- databases employing dedicated specialized

关键词： distributed databases parallel processing Query processing Bioinformatics Algorithm design and analysis

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Survey and Performance Test of Python-based Libraries for parallel Processing 2020

Survey and Performance Test of Python-based Libraries for Pa...

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the 9th international conference on Smart Media and applications

作者： TaeHong Kim YoonSeok Cha ByeonChun Shin ByungRae Cha Gwangju Metro-city S. Korea Chonnam National Uniersity S. Korea

ISBN: (纸本)9781450389259

By the Fourth Industrial Revolution and the 10 strategic technology of the Gartner Group, Artificial Intelligence(AI) technology was important and affected many areas. One of the ways to accelerate AI services is the Python-based parallel processing library. High-level programming languages such as Python are increasingly used to provide intuitive interfaces to libraries written in lower-level languages and for assembling applications from various components. this migration towards orchestration rather than implementation, coupled with the growing need for parallel computing (e.g., due to big data and the end of Moore's law), necessitates rethinking how parallelism is expressed in programs.[1] In this paper, take a look at a Python-based distributed parallel processing library, one of the ways to accelerate AI services, and use it to compare serial and parallel processing times.

关键词： Artificial Intelligence

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