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Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
Base paper ppt-. A load balancing model based on cloud partitioning for the ...Lavanya Vigrahala
A load balancing model based on cloud partitioning for the public cloud. -Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Dear students get fully solved assignments
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Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Load Balancing In Distributed ComputingRicha Singh
Load Balancing In Distributed Computing
The goal of the load balancing algorithms is to maintain the load to each processing element such that all the processing elements become neither overloaded nor idle that means each processing element ideally has equal load at any moment of time during execution to obtain the maximum performance (minimum execution time) of the system
A load balancing model based on cloud partitioning for the public cloud. ppt Lavanya Vigrahala
Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Performance Comparision of Dynamic Load Balancing Algorithm in Cloud ComputingEswar Publications
Cloud computing as a distributed paradigm, it has the latent to make over a large part of the Cooperative industry. In cloud computing it’s automatically describe more technologies like distributed computing, virtualization, software, web services and networking. We review the new cloud computing technologies, and indicate the main challenges for their development in future, among which load balancing problem stands out and attracts our attention Concept of load balancing in networking and in cloud environment both are widely different. Load balancing in networking its complete concern to avoid the problem of overloading and under loading in any sever networking cloud computing its complete different its involves different elements metrics such as security, reliability, throughput, tolerance, on demand services, cost etc. Through these elements we avoiding various node problem of distributing system where many services waiting for request and others are heavily loaded and through these its increase response time and degraded performance optimization. In this paper first we classify algorithms in static and dynamic. Then we analyzed the dynamic algorithms applied in dynamics environments in cloud. Through this paper we have been show compression of various dynamics algorithm in which we include honey bee algorithm, throttled algorithm, Biased random algorithm with different elements and describe how and which is best in cloud environment with different metrics mainly used elements are performance, resource utilization and minimum cost. Our main focus of paper is in the analyze various load
balancing algorithms and their applicability in cloud environment.
Client-Centric Consistency
Provide guarantees about ordering of operations only for a single client, i.e.
Effects of an operations depend on the client performing it
Effects also depend on the history of client’s operations
Applied only when requested by the client
No guarantees concerning concurrent accesses by different clients
Assumption:
Clients can access different replicas, e.g. mobile users
Review of Some Checkpointing Schemes for Distributed and Mobile Computing Env...Eswar Publications
Fault Tolerance Techniques facilitate systems to carry out tasks in the incidence of faults. A checkpoint is a local state of a process saved on stable storage. In a distributed system, since the processes in the system do not share memory; a global state of the system is defined as a combination of local states, one from each process. In case of a fault in distributed systems, checkpointing enables the execution of a program to be resumed from a previous consistent global state rather than resuming the execution from the commencement. In this way, the sum of constructive processing vanished because of the fault is appreciably reduced. In this paper, we talk about various issues related to the checkpointing for distributed systems and mobile computing environments. We also confer
various types of checkpointing: coordinated checkpointing, asynchronous checkpointing, communication induced
checkpointing and message logging based checkpointing. We also present a survey of some checkpointing algorithms for distributed systems.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
UNIT IV FAILURE RECOVERY AND FAULT TOLERANCE 9
Basic Concepts-Classification of Failures – Basic Approaches to Recovery; Recovery in
Concurrent System; Synchronous and Asynchronous Checkpointing and Recovery; Check
pointing in Distributed Database Systems; Fault Tolerance; Issues - Two-phase and Nonblocking
Commit Protocols; Voting Protocols; Dynamic Voting Protocols;
Reactive by example (DevOpsDaysTLV 2019)Eran Harel
The reactive manifesto is meant to guide you in building Responsive, Resilient, Elastic (scalable), and Message Driven systems. But these are all bombastic words which are quite meaningless without a good context or good examples. This talk will walk you through a story of improving a real life service, bringing it to perform well, and link the steps to the reactive manifesto cornerstones.
Videos link: https://youtu.be/Fg1SJufaHOs
ieee standard base paper.-Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...IEEEGLOBALSOFTTECHNOLOGIES
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DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Privacy preserving public auditing fo...IEEEGLOBALSOFTTECHNOLOGIES
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Base paper ppt-. A load balancing model based on cloud partitioning for the ...Lavanya Vigrahala
A load balancing model based on cloud partitioning for the public cloud. -Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Load Balancing In Distributed ComputingRicha Singh
Load Balancing In Distributed Computing
The goal of the load balancing algorithms is to maintain the load to each processing element such that all the processing elements become neither overloaded nor idle that means each processing element ideally has equal load at any moment of time during execution to obtain the maximum performance (minimum execution time) of the system
A load balancing model based on cloud partitioning for the public cloud. ppt Lavanya Vigrahala
Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Performance Comparision of Dynamic Load Balancing Algorithm in Cloud ComputingEswar Publications
Cloud computing as a distributed paradigm, it has the latent to make over a large part of the Cooperative industry. In cloud computing it’s automatically describe more technologies like distributed computing, virtualization, software, web services and networking. We review the new cloud computing technologies, and indicate the main challenges for their development in future, among which load balancing problem stands out and attracts our attention Concept of load balancing in networking and in cloud environment both are widely different. Load balancing in networking its complete concern to avoid the problem of overloading and under loading in any sever networking cloud computing its complete different its involves different elements metrics such as security, reliability, throughput, tolerance, on demand services, cost etc. Through these elements we avoiding various node problem of distributing system where many services waiting for request and others are heavily loaded and through these its increase response time and degraded performance optimization. In this paper first we classify algorithms in static and dynamic. Then we analyzed the dynamic algorithms applied in dynamics environments in cloud. Through this paper we have been show compression of various dynamics algorithm in which we include honey bee algorithm, throttled algorithm, Biased random algorithm with different elements and describe how and which is best in cloud environment with different metrics mainly used elements are performance, resource utilization and minimum cost. Our main focus of paper is in the analyze various load
balancing algorithms and their applicability in cloud environment.
Client-Centric Consistency
Provide guarantees about ordering of operations only for a single client, i.e.
Effects of an operations depend on the client performing it
Effects also depend on the history of client’s operations
Applied only when requested by the client
No guarantees concerning concurrent accesses by different clients
Assumption:
Clients can access different replicas, e.g. mobile users
Review of Some Checkpointing Schemes for Distributed and Mobile Computing Env...Eswar Publications
Fault Tolerance Techniques facilitate systems to carry out tasks in the incidence of faults. A checkpoint is a local state of a process saved on stable storage. In a distributed system, since the processes in the system do not share memory; a global state of the system is defined as a combination of local states, one from each process. In case of a fault in distributed systems, checkpointing enables the execution of a program to be resumed from a previous consistent global state rather than resuming the execution from the commencement. In this way, the sum of constructive processing vanished because of the fault is appreciably reduced. In this paper, we talk about various issues related to the checkpointing for distributed systems and mobile computing environments. We also confer
various types of checkpointing: coordinated checkpointing, asynchronous checkpointing, communication induced
checkpointing and message logging based checkpointing. We also present a survey of some checkpointing algorithms for distributed systems.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
UNIT IV FAILURE RECOVERY AND FAULT TOLERANCE 9
Basic Concepts-Classification of Failures – Basic Approaches to Recovery; Recovery in
Concurrent System; Synchronous and Asynchronous Checkpointing and Recovery; Check
pointing in Distributed Database Systems; Fault Tolerance; Issues - Two-phase and Nonblocking
Commit Protocols; Voting Protocols; Dynamic Voting Protocols;
Reactive by example (DevOpsDaysTLV 2019)Eran Harel
The reactive manifesto is meant to guide you in building Responsive, Resilient, Elastic (scalable), and Message Driven systems. But these are all bombastic words which are quite meaningless without a good context or good examples. This talk will walk you through a story of improving a real life service, bringing it to perform well, and link the steps to the reactive manifesto cornerstones.
Videos link: https://youtu.be/Fg1SJufaHOs
ieee standard base paper.-Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Privacy preserving public auditing fo...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
A survey of various scheduling algorithm in cloud computing environmenteSAT Journals
Abstract Cloud computing is known as a provider of dynamic services using very large scalable and virtualized resources over the Internet. Due to novelty of cloud computing field, there is no many standard task scheduling algorithm used in cloud environment. Especially that in cloud, there is a high communication cost that prevents well known task schedulers to be applied in large scale distributed environment. Today, researchers attempt to build job scheduling algorithms that are compatible and applicable in Cloud Computing environment Job scheduling is most important task in cloud computing environment because user have to pay for resources used based upon time. Hence efficient utilization of resources must be important and for that scheduling plays a vital role to get maximum benefit from the resources. In this paper we are studying various scheduling algorithm and issues related to them in cloud computing. Index Terms: cloud computing, scheduling, algorithm
A survey of various scheduling algorithm in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Cloud Computing Load Balancing Algorithms Comparison Based SurveyINFOGAIN PUBLICATION
Cloud computing is an online primarily based computing. This computing paradigm has increased the employment of network wherever the potential of 1 node may be used by alternative node. Cloud provides services on demand to distributive resources like info, servers, software, infrastructure etc. in pay as you go basis. Load reconciliation is one amongst the vexing problems in distributed atmosphere. Resources of service supplier have to be compelled to balance the load of shopper request. Totally different load reconciliation algorithms are planned so as to manage the resources of service supplier with efficiency and effectively. This paper presents a comparison of assorted policies used for load reconciliation.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
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Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
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JAVA(All Domains)
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Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
Harnessing the cloud for securely outsourcing large scale systems of linear e...Muthu Samy
Sybian Technologies Pvt Ltd
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...IEEEGLOBALSOFTTECHNOLOGIES
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DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...IEEEGLOBALSOFTTECHNOLOGIES
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DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...IEEEGLOBALSOFTTECHNOLOGIES
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Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Error tolerant resource allocation and payment minimization for cloud system
1. CLOUING
Error-Tolerant Resource Allocation and Payment Minimization for
Cloud System
ABSTRACT:
With virtual machine (VM) technology being increasingly mature, compute resources in cloud
systems can be partitioned in fine granularity and allocated on demand. We make three
contributions in this paper: 1) we formulate a deadline-driven resource allocation problem based
on the cloud environment facilitated with VM resource isolation technology, and also propose a
novel solution with polynomial time, which could minimize users’ payment in terms of their
expected deadlines. 2) By analyzing the upper bound of task execution length based on the
possibly inaccurate workload prediction, we further propose an error-tolerant method to
guarantee task’s completion within its deadline. 3) We validate its effectiveness over a real VM-
facilitated cluster environment under different levels of competition. In our experiment, by
tuning algorithmic input deadline based on our derived bound, task execution length can always
be limited within its deadline in the sufficient-supply situation; the mean execution length still
keeps 70 percent as high as user specified deadline under the severe competition. Under the
original-deadline-based solution, about 52.5 percent of tasks are completed within 0.95-1.0 as
high as their deadline, which still conforms to the deadline-guaranteed requirement. Only 20
percent of tasks violate deadlines, yet most (17.5 percent) are still finished within 1.05 times of
deadlines.
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2. EXISTING SYSTEM:
In literatures, traditional optimization problems are often subject to the precise prediction of
task’s characteristic (or execution property), which is nontrivial to realize in practice.
Traditional job scheduling is often formulated as a kind of combinatorial optimization problem
(or queue-based multiprocessor scheduling problem, due to the nonguaranteed performance
isolation for multiple tasks running on the same machines. That is, most of the existing
deadline-driven task scheduling solutions (from single cluster environment confined in LAN to
the Grid computing environment suitable for WAN are also strictly subject to the queuing
model under which a single machine’s multiple resources cannot be further split to smaller
fractions at will. This will eventually cause the raw-grained resource allocation, relatively low
resource utilization and suboptimal task execution efficiency
DISADVANTAGES OF EXISTING SYSTEM:
Users may wish to minimize their payments when guaranteeing their service level such that
their tasks can be finished before deadlines. Such a deadline-guaranteed resource allocation
with minimized payment is rarely studied in literatures. Moreover, inevitable errors in
predicting task workloads will definitely make the problem harder.
PROPOSED SYSTEM:
We make three contributions in this paper:
1) We formulate a deadline-driven resource allocation problem based on the cloud environment
facilitated with VM resource isolation technology, and also propose a novel solution with
polynomial time, which could minimize users’ payment in terms of their expected deadlines.
2) By analyzing the upper bound of task execution length based on the possibly inaccurate
workload prediction, we further propose an error-tolerant method to guarantee task’s
completion within its deadline.
3. 3) We validate its effectiveness over a real VM-facilitated cluster environment under different
levels of competition.
ADVANTAGES OF PROPOSED SYSTEM:
All the theoretical conclusions are confirmed with our experiments. Specifically, in the situation
with relatively sufficient resources, the worst case tasks under the stricter deadline-based
allocation only take as about 0.75 times as their deadlines to complete, as compared to the 1.2
times of the deadlines under the original user-predefined deadline based allocation. We also
observe that in the competitive environment, the latter algorithm performs much more stable
than the former instead, which means that the latter tolerates the resource competition better.
We also confirm the effectiveness of our solution via the distribution of the number of tasks
with respect to execution times and user payments: in the competitive situation, majority of
tasks can be guaranteed to be completed within deadlines.
SYSTEM ARCHITECTURE:
5. RAM - 256 MB(min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE CONFIGURATION:-
Operating System : Windows XP
Programming Language : JAVA
Java Version : JDK 1.6 & above.
REFERENCE:
Sheng Di, Member, IEEE, and Cho-Li Wang, Member, IEEE-“Error-Tolerant Resource
Allocation and Payment Minimization for Cloud System” IEEE TRANSACTIONS ON
PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 6, JUNE 2013.
DOMAIN: WIRELESS NETWORK PROJECTS