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arXiv 2019年

作者： Wang, Zhaoguo Zhao, Changgeng Mu, Shuai Chen, Haibo Li, Jinyang Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Department of Computer Science New York University Department of Computer Science Stony Brook University

In recent years, Raft has overtaken Paxos as the consensus algorithm of choice. [53] While many have pointed out similarities between the two protocols, no one has formally mapped out their relationships. In this paper, we show how Raft and Paxos are formally related despite their surface differences. Based on the formal mapping between the two protocols, we show how to automatically port a certain class of optimizations from Paxos to Raft with guaranteed correctness. As case studies, we port and evaluate two optimizations, Mencius and Paxos Quorum Lease to Raft. Copyright © 2019, The Authors. All rights reserved.

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Thermosim: Deep learning based framework for modeling and simulation of thermal-aware resource management for cloud computing environments

arXiv

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arXiv 2020年

作者： Gill, Sukhpal Singh Tuli, Shreshth Toosi, Adel Nadjaran Cuadrado, Felix Garraghan, Peter Bahsoon, Rami Lutfiyya, Hanan Sakellariou, Rizos Rana, Omer Dustdar, Schahram Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Delhi India Faculty of Information Technology Monash University ClaytonVIC Australia Spain School of Computing and Communications Lancaster University United Kingdom School of Computer Science University of Birmingham Birmingham United Kingdom Department of Computer Science University of Western Ontario LondonON Canada School of Computer Science University of Manchester Oxford Road ManchesterUK United Kingdom School of Computer Science and Informatics Cardiff University CardiffUK United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Laboratory School of Computing and Information Systems University of Melbourne Australia

Current cloud computing frameworks host millions of physical servers that utilize cloud computing resources in the form of different virtual machines. Cloud Data Center (CDC) infrastructures require significant amounts of energy to deliver large scale computational services. Moreover, computing nodes generate large volumes of heat, requiring cooling units in turn to eliminate the effect of this heat. Thus, overall energy consumption of the CDC increases tremendously for servers as well as for cooling units. However, current workload allocation policies do not take into account effect on temperature and it is challenging to simulate the thermal behaviour of CDCs. There is a need for a thermal-aware framework to simulate and model the behaviour of nodes and measure the important performance parameters which can be affected by its temperature. In this paper, we propose a lightweight framework, ThermoSim, for modelling and simulation of thermal-aware resource management for cloud computing environments. This work presents a Recurrent Neural Network based deep learning temperature predictor for CDCs which is utilized by ThermoSim for lightweight resource management in constrained cloud environments. ThermoSim extends the CloudSim toolkit helping to analyse the performance of various key parameters such as energy consumption, service level agreement violation rate, number of virtual machine migrations and temperature during the management of cloud resources for execution of workloads. Further, different energy-aware and thermal-aware resource management techniques are tested using the proposed ThermoSim framework in order to validate it against the existing framework (Thas). The experimental results demonstrate the proposed framework is capable of modelling and simulating the thermal behaviour of a CDC and ThermoSim framework is better than Thas in terms of energy consumption, cost, time, memory usage and prediction accuracy. Copyright © 2020, The Authors. All rights rese

关键词： Cloud computing

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Teaching clean code

Teaching clean code

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2018 Combined Workshops of the German Software Engineering Conference, SE-WS 2018

作者： Dietz, Linus W. Manner, Johannes Harrer, Simon Lenhard, Jörg Department of Informatics Technical University of Munich Germany Distributed Systems Group University of Bamberg Germany Department of Mathematics and Computer Science Karlstad University Sweden

Learning programming is hard - teaching it well is even more challenging. At university, the focus is often on functional correctness and neglects the topic of clean and maintainable code, despite the dire need for developers with this skill set within the software industry. We present a feedbackdriven teaching concept for college students in their second to third year that we have applied and refined successfully over a period of more than six years and for which received the faculty's teaching award. Evaluating the learning process within a semester of student submissions (n=18) with static code analysis tools shows satisfying progress. Identifying the correction of the in-semester programming assignments as the bottleneck for scaling the number of students in the course, we propose using a knowledge base of code examples to decrease the time to feedback and increase feedback quality. From our experience in assessing student code, we have compiled such a knowledge base with the typical issues of Java learners' code in the format of before/after comparisons. By simply referencing the problem to the student, the quality of feedback can be improved, since such comparisons let the student understand the problem and the rationale behind the solution. Further speed-up is achieved by using a curated list of static code analysis checks to help the corrector in identifying violations in the code swiftly. We see this work as a foundational step towards online courses with hundreds of students learning how to write clean code. © 2018 CEUR-WS. All rights reserved.

关键词： Students

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Foundational Competencies and Responsibilities of a Research Software Engineer

arXiv

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arXiv 2023年

作者： Goth, Florian Alves, Renato Braun, Matthias Castro, Leyla Jael Chourdakis, Gerasimos Christ, Simon Cohen, Jeremy Druskat, Stephan Erxleben, Fredo Grad, Jean-Noël Hagdorn, Magnus Hodges, Toby Juckeland, Guido Kempf, Dominic Lamprecht, Anna-Lena Linxweiler, Jan Löffler, Frank Martone, Michele Schwarzmeier, Moritz Seibold, Heidi Thiele, Jan Philipp Waldow, Harald von Wittke, Samantha Institute for Theoretical Physics and Astrophysics University of Würzburg Germany European Molecular Biology Laboratory Heidelberg Germany Cluster of Excellence IntCDC University of Stuttgart Germany ZB MED Information Centre for Life Sciences Cologne Germany School of Computation Information and Technology Technical University of Munich Garching Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Leibniz University Hannover Department of Cell Biology and Biophysics Computational Biology Germany Imperial College London London United Kingdom Institute for Software Technology Berlin Germany Humboldt-Universität zu Berlin Department of Computer Science Berlin Germany Helmholtz-Zentrum Dresden-Rossendorf Germany Institute for Computational Physics University of Stuttgart Germany Geschäftsbereich IT Charité Universitätsmedizin Berlin Germany The Carpentries United States Heidelberg University Scientific Software Center Germany Institute of Computer Science University of Potsdam Germany Technische Universität Braunschweig Germany Michael Stifel Center Jena Friedrich Schiller University Jena Germany Leibniz Supercomputing Centre Garching Germany Mathematical Modeling and Analysis TU Darmstadt Germany IGDORE Munich Germany Weierstrass Institute Berlin Germany Leibniz University Hannover Institute of Applied Mathematics Scientific Computing Hannover Germany Johann Heinrich von Thünen Institute Centre for Information Management Germany

The term Research Software Engineer, or RSE, emerged a little over 10 years ago as a way to represent individuals working in the research community but focusing on software development. The term has been widely adopted and there are a number of high-level definitions of what an RSE is. However, the roles of RSEs vary depending on the institutional context they work in. At one end of the spectrum, RSE roles may look similar to a traditional research role. At the other extreme, they resemble that of a software engineer in industry. Most RSE roles inhabit the space between these two extremes. Therefore, providing a straightforward, comprehensive definition of what an RSE does and what experience, skills and competencies are required to become one is challenging. In this community paper we define the broad notion of what an RSE is, explore the different types of work they undertake, and define a list of foundational competencies as well as values that outline the general profile of an RSE. Further research and training can build upon this foundation of skills and focus on various aspects in greater detail. We expect that graduates and practitioners will have a larger and more diverse set of skills than outlined here. On this basis, we elaborate on the progression of these skills along different dimensions. We look at specific types of RSE roles, propose recommendations for organisations, and give examples of future specialisations. An appendix details how existing curricula fit into this framework. © 2023, CC BY.

关键词： computer aided software engineering

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Issues and Suggestions for the Development of a Biodiversity Data Visualization Support Tool

Issues and Suggestions for the Development of a Biodiversity...

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20th Eurographics/IEEE VGT Conference on Visualization, EuroVis 2018

作者： Kaur, Pawandeep Klan, Friederike König-Ries, Birgitta Heinz-Nixdorf Endowed Chair for Distributed Information Systems Department of Mathematics and Computer Science Friedrich-Schiller-Universität Jena Germany

ISBN: (纸本)9783038680604

Visualizations are an important tool to transport information. However, finding the right visualization can be challenging. Using the biodiversity research domain as a showcase, we investigate where exactly these challenges are and what a tool should look like that helps scientists overcome them. Our results are based on a survey we performed. © 2018 Eurographics Association. All rights reserved.

关键词： Visualization

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MovCloud: A Cloud-enabled Framework to Analyse Movement Behaviors

MovCloud: A Cloud-enabled Framework to Analyse Movement Beha...

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IEEE International Conference on Cloud Computing Technology and science

作者： Shreya Ghosh Soumya K Ghosh Rajkumar Buyya Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Indian Institute of Technology Kharagpur Kharagpur India Cloud Computing and Distributed Systems (CLOUDS) Lab The University of Melbourne Australia

Understanding human interests and intents from movement data are fundamental challenges for any location-based service. With the pervasiveness of sensor embedded smartphones and wireless networks and communication, the availability of spatio-temporal mobility trace (timestamped location information) is increasingly growing. Analysing these huge amount of mobility data is another major concern. This paper proposes a cloud-based framework named MovCloud to efficiently manage and analyse mobility data. Specifically, the framework presents a hierarchical indexing schema to store trajectory data in different spatio-temporal resolution, clusters the trajectories based on semantic movement behaviour instead of only raw latitude, longitude point and resolves mobility queries using MapReduce paradigm. MovCloud is implemented over Google Cloud Platform (GCP) and an extensive set of experiments on real-life data yield the effectiveness of the proposed framework. MovCloud has achieved ～ 28% better clustering accuracy and also executed three times faster than the baseline methods.

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STLDAS: Secure Two Level Deduplication and Auditing of Shared Data in Cloud

STLDAS: Secure Two Level Deduplication and Auditing of Share...

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IEEE Region 10 Symposium

作者： C M Geeta G Mithila Lakshmi R G Shreyas Raju S Raghavendra Rajkumar Buyya K R Venugopal S S Iyengar L M Patnaik Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne Australia Bangalore University Bengaluru India Department of Computer Science and Engineering Florida International University USA INSA National Institute of Advanced Studies Indian Institute of Science Campus Bangalore India

With the cloud repository service furnished by the cloud computing, users can comfortably arrange themselves as a cluster and distribute information effectively. In order to empower public verifier to audit the distributed information, clients in the cluster need to Figure out signatures on complete chunks of collaborative information. Every client in the cluster modifies and signs his respective chunks, and deploys in the cloud server. Hence specific chunks of shared information are normally signed by specific clients. If anyone of the customers' is found malicious, he is immediately repudiated from the cluster. The prevailing clients in the cluster are permitted to re-sign the chunks that were earlier signed by this eliminated client. This approach is inefficient due to the massive amount of collaborative information in the cloud. By exploiting the approach of proxy re-signatures, the CSP is acknowledged to re-sign chunks in support of the prevailing clients during customer repudiation. When many clients deploy the same information to the cloud repository, repository space has identical copies, hence deduplication technology is usually utilized to lower the capacity and bandwidth prerequisites of the utilities by removing repetitious information and hoarding only an original replica of them. In order to assimilate both data honesty and deduplication in cloud, we present a novel Secure Two Level Deduplication and Auditing of Shared Data in Cloud (STLDAS) mechanism. Experimental results show that our mechanism achieves secure deduplication and appreciable improvement in tag generation.

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HomeCA: Scalable Secure IoT Network Integration 49

HomeCA: Scalable Secure IoT Network Integration

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49. Jahrestagung der Gesellschaft fur Informatik: 50 Jahre Gesellschaft fur Informatik - Informatik fur Gesellschaft, INFORMATIK 2019 - 49th Annual Meeting of the German Informatics Society: 50 years of the German Informatics Society - computer science for Society, INFORMATICS 2019

作者： Müller, Robert Schmitt, Corinna Kaiser, Daniel Waldvogel, Marcel Department of Computer and Information Science Distributed Systems Laboratory Universität Konstanz Konstanz78457 Germany Research Institute Code Universität der Bundeswehr München Werner-Heisenberg-Weg 39 Neubiberg85577 Germany Security and Networking Research Group Netlab Maison du Nombre 6 University of Luxembourg Avenue de la Fonte Esch-sur-Alzette4364 Luxembourg

ISBN: (纸本)9783885796886

Integrating Internet of Things (IoT) devices into an existing network is a nightmare. Minimalistic, unfriendly user interfaces, if any;badly chosen security methods, most notably the defaults;lack of long term security;and bugs or misconAgurations are plentiful. As a result, an increasing number of owners operate unsecure devices. Our investigations into the root causes of the problems resulted in the development of Home CertiAcate Authority (HomeCA). HomeCAincludes a comprehensive set of secure, vendor-independent interoperable practices based on existing protocols and open standards. HomeCA avoids most of the current pitfalls in network integration by design. Long-term protocol security, permission management, and secure usage combined with simpliAed device integration and secure key updates on ownership acquisition pave the way toward scalable, federated IoT security. © 2019 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Network security

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Geo-Cloudlet: Time and Power Efficient Geospatial Query Resolution using Cloudlet

Geo-Cloudlet: Time and Power Efficient Geospatial Query Reso...

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International Conference on Advanced Computing, ICAC

作者： Jaydeep Das Anwesha Mukherjee Soumya K. Ghosh Rajkumar Buyya Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal India Department of Computer Science Mahishadal Raj College Purba Medinipur West Bengal India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne VIC Australia

ISBN: (数字)9781728152868

ISBN: (纸本)9781728152875

Geospatial data analysis is an emerging area of research today due to the potential to enable varied location-aware services. The existing centralized cloud-based analysis becomes time and computing-intensive for huge amount of geospatial data processing. This paper addresses the challenge of time and power-efficiency in QoS-aware geospatial query resolution. We propose a cloudlet based hierarchical paradigm, namely Geo-Cloudlet, where the cloudlets contain the geospatial data of the districts. The state and national level geospatial data are stored inside the state cloud and country cloud respectively. The query resolution is performed by either the cloudlet or by the state cloud or country cloud depending upon the geographical region related to the query. The experimental analysis illustrates that the proposed architecture Geo-Cloudlet reduces the latency up to 61.3% and power consumption up to 61.1% over the use of only remote cloud servers for geospatial query resolution.

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