In traditional data center numbers of services are run onto the dedicated physical servers. Most of the
time, these data centers are not used their full capacity in term of resources. Virtualization allows the
movement of VM from one host to the another host ,which is called virtual machine migration, so these
data centers can consolidate their services onto lesser number of physical servers than originally required.
Virtual machine placement is the part of the VM migration. To map the virtual machines to the physical
machines is called the VM placement. In other word, VM placement is the process to select the
appropriate host for the given VM. For the efficient utilization of the physical resources, VM should be
placed on to the suitable host. So many virtual machine placement algorithms have been proposed by
different researchers that run under cloud computing environment. Most of the VM placement algorithms
try to achieve some goal. This goal can either saving energy by shutting down some severs or it can be
maximizing the resources utilization. Four steps are involved in the VM machine migration process. First
step is to select the PM which is overload or undreloaded, next step is to select one or more VM, and then
select the PM where selected VM can be placed and last step is to transfer the VM. Selecting the suitable
host is one of the challenging task in the migration process, because wrong selection of host can increased
the number of migration, resource wastage and energy consumption. This paper only focuses to the third
step that is selecting a suitable PM that can host the VM. It shows an analysis of different existing Virtual
Machine’s placement algorithms with their anomalies.
Virtual Machine Migration Techniques in Cloud Environment: A Surveyijsrd.com
Cloud is an emerging technology in the world of information technology and is built on the key concept of virtualization. Virtualization separates hardware from software and has benefits of server consolidation and live migration. Live migration is a useful tool for migrating OS instances across distant physical of data centers and clusters. It facilitates load balancing, fault management, low-level system maintenance and reduction in energy consumption. In this paper, we survey the major issues of virtual machine live migration. There are various techniques available for live migration and different parameters are considered for migration.
Live virtual machine migration based on future prediction of resource require...Tapender Yadav
This document gives the brief description of the work done during the Summer Internship at Institute for Development and Research in Banking Technology (IDRBT), Hyderabad. The project was undertaken from May 2014 - July 2014 under the exemplary guidance of Dr. G. R. Gangadharan, Asst. Professor, IDRBT, Hyderabad.
Inroduction to Virtualization and Video Playback during a Live Migrated Virtual Machine hosting the server with its time analysis.
OS- Ubuntu
Hypervisor- KVM
Resumption of virtual machines after adaptive deduplication of virtual machin...IJECEIAES
In cloud computing, load balancing, energy utilization are the critical problems solved by virtual machine (VM) migration. Live migration is the live movement of VMs from an overloaded/underloaded physical machine to a suitable one. During this process, transferring large disk image files take more time, hence more migration and down time. In the proposed adaptive deduplication, based on the image file size, the file undergoes both fixed, variable length deduplication processes. The significance of this paper is resumption of VMs with reunited deduplicated disk image files. The performance measured by calculating the percentage reduction of VM image size after deduplication, the time taken to migrate the deduplicated file and the time taken for each VM to resume after the migration. The results show that 83%, 89.76% reduction overall image size and migration time respectively. For a deduplication ratio of 92%, it takes an overall time of 3.52 minutes, 7% reduction in resumption time, compared with the time taken for the total QCOW2 files with original size. For VMDK files the resumption time reduced by a maximum 17% (7.63 mins) compared with that of for original files.
Virtual Machine Migration Techniques in Cloud Environment: A Surveyijsrd.com
Cloud is an emerging technology in the world of information technology and is built on the key concept of virtualization. Virtualization separates hardware from software and has benefits of server consolidation and live migration. Live migration is a useful tool for migrating OS instances across distant physical of data centers and clusters. It facilitates load balancing, fault management, low-level system maintenance and reduction in energy consumption. In this paper, we survey the major issues of virtual machine live migration. There are various techniques available for live migration and different parameters are considered for migration.
Live virtual machine migration based on future prediction of resource require...Tapender Yadav
This document gives the brief description of the work done during the Summer Internship at Institute for Development and Research in Banking Technology (IDRBT), Hyderabad. The project was undertaken from May 2014 - July 2014 under the exemplary guidance of Dr. G. R. Gangadharan, Asst. Professor, IDRBT, Hyderabad.
Inroduction to Virtualization and Video Playback during a Live Migrated Virtual Machine hosting the server with its time analysis.
OS- Ubuntu
Hypervisor- KVM
Resumption of virtual machines after adaptive deduplication of virtual machin...IJECEIAES
In cloud computing, load balancing, energy utilization are the critical problems solved by virtual machine (VM) migration. Live migration is the live movement of VMs from an overloaded/underloaded physical machine to a suitable one. During this process, transferring large disk image files take more time, hence more migration and down time. In the proposed adaptive deduplication, based on the image file size, the file undergoes both fixed, variable length deduplication processes. The significance of this paper is resumption of VMs with reunited deduplicated disk image files. The performance measured by calculating the percentage reduction of VM image size after deduplication, the time taken to migrate the deduplicated file and the time taken for each VM to resume after the migration. The results show that 83%, 89.76% reduction overall image size and migration time respectively. For a deduplication ratio of 92%, it takes an overall time of 3.52 minutes, 7% reduction in resumption time, compared with the time taken for the total QCOW2 files with original size. For VMDK files the resumption time reduced by a maximum 17% (7.63 mins) compared with that of for original files.
Virtualization is the creation of a virtual (rather than actual) version of something, such as an operating system, a server, a storage device or network resources.
Classification of Virtualization Environment for Cloud ComputingSouvik Pal
Cloud Computing is a relatively new field gaining more popularity day by day for ramified applications among the Internet users.
Virtualization plays a significant role for managing and coordinating the access from the resource pool to multiple virtual machines on
which multiple heterogeneous applications are running. Various virtualization methodologies are of significant importance because it
helps to overcome the complex workloads, frequent application patching and updating, and multiple software architecture. Although
a lot of research and study has been conducted on virtualization, a range of issues involved have mostly been presented in isolation
of each other. Therefore, we have made an attempt to present a comprehensive survey study of different aspects of virtualization. We
present our classification of virtualization methodologies and their brief explanation, based on their working principle and underlying
features.
Implementation of Monitoring System for Cloud ComputingIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Scheduler Support for Video-oriented Multimedia on Client-side VirtualizationHwanju Kim
Hwanju Kim, Jinkyu Jeong, Jaeho Hwang, Joonwon Lee, and Seungryoul Maeng, “Scheduler Support for Video-oriented Multimedia on Client-side Virtualization”, ACM Multimedia Systems (MMSys), Chapel Hill, North Carolina, USA, Feb. 2012.
This is the Complete Information about Data Replication you need, i am focused on these topics:
What is replication?
Who use it?
Types ?
Implementation Methods?
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...IJERA Editor
Cloud Computing has emerged as the most trust worthy and secure technology amongst its users. Migration of
virtual machine is an important aspect of this technology. Migration of instances makes data centers and clusters
handier in the terms of its administration and management. Intrinsically, Migration is done to boost the
processing power of computers and it is done by procuring the power management, load balancing, fault
tolerance, reducing response time and increasing the quality of service. Because the use of this technique is
highly dependent on cloud computing infrastructure architecture in some cloud infrastructure, such as
Eucalyptus the virtual machine migration technique has not been used yet.
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
Virtualization Technology using Virtual Machines for Cloud ComputingIJMER
Cloud computing is the delivery of computing and storage capacity as a service to a community of end users. The name “cloud computing” comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts services with a user's software, data and computation over a network. End users access cloud-based applications through a web browser or mobile application or a light-weight desktop while the business software and user's data are stored on servers at a remote location. Proponents claim that cloud computing environment allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables IT industry to more rapidly adjust resources to meet fluctuating and unpredictable business demand. In this paper, we present a system that uses virtualization technology to allocate the data center resources dynamically based on the application demands and support green computing by optimizing the number of servers in use. This method multiplexes virtual to physical resources adaptively based on the changing demand. We use the concept of skewness metric to combine virtual machines with different resource characteristics appropriately so that the capacities of servers are well utilized.
Virtualization is the creation of a virtual (rather than actual) version of something, such as an operating system, a server, a storage device or network resources.
Classification of Virtualization Environment for Cloud ComputingSouvik Pal
Cloud Computing is a relatively new field gaining more popularity day by day for ramified applications among the Internet users.
Virtualization plays a significant role for managing and coordinating the access from the resource pool to multiple virtual machines on
which multiple heterogeneous applications are running. Various virtualization methodologies are of significant importance because it
helps to overcome the complex workloads, frequent application patching and updating, and multiple software architecture. Although
a lot of research and study has been conducted on virtualization, a range of issues involved have mostly been presented in isolation
of each other. Therefore, we have made an attempt to present a comprehensive survey study of different aspects of virtualization. We
present our classification of virtualization methodologies and their brief explanation, based on their working principle and underlying
features.
Implementation of Monitoring System for Cloud ComputingIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Scheduler Support for Video-oriented Multimedia on Client-side VirtualizationHwanju Kim
Hwanju Kim, Jinkyu Jeong, Jaeho Hwang, Joonwon Lee, and Seungryoul Maeng, “Scheduler Support for Video-oriented Multimedia on Client-side Virtualization”, ACM Multimedia Systems (MMSys), Chapel Hill, North Carolina, USA, Feb. 2012.
This is the Complete Information about Data Replication you need, i am focused on these topics:
What is replication?
Who use it?
Types ?
Implementation Methods?
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...IJERA Editor
Cloud Computing has emerged as the most trust worthy and secure technology amongst its users. Migration of
virtual machine is an important aspect of this technology. Migration of instances makes data centers and clusters
handier in the terms of its administration and management. Intrinsically, Migration is done to boost the
processing power of computers and it is done by procuring the power management, load balancing, fault
tolerance, reducing response time and increasing the quality of service. Because the use of this technique is
highly dependent on cloud computing infrastructure architecture in some cloud infrastructure, such as
Eucalyptus the virtual machine migration technique has not been used yet.
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
Virtualization Technology using Virtual Machines for Cloud ComputingIJMER
Cloud computing is the delivery of computing and storage capacity as a service to a community of end users. The name “cloud computing” comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts services with a user's software, data and computation over a network. End users access cloud-based applications through a web browser or mobile application or a light-weight desktop while the business software and user's data are stored on servers at a remote location. Proponents claim that cloud computing environment allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables IT industry to more rapidly adjust resources to meet fluctuating and unpredictable business demand. In this paper, we present a system that uses virtualization technology to allocate the data center resources dynamically based on the application demands and support green computing by optimizing the number of servers in use. This method multiplexes virtual to physical resources adaptively based on the changing demand. We use the concept of skewness metric to combine virtual machines with different resource characteristics appropriately so that the capacities of servers are well utilized.
A Strategic Evaluation of Energy-Consumption and Total Execution Time for Clo...idescitation
Cloud computing is a very budding area in the
research field and as well as in the IT enterprises. Cloud
Computing is basically on-demand network access to a
collection of physical resources which can be provisioned
according to the need of cloud user under the supervision of
Cloud Service provider interaction. In this era of rapid usage
of Internet all over the world, Cloud computing has become
the center of Internet-oriented business place. For enterprises,
cloud computing is the worthy of consideration and they try to
build business systems with minimal costs, higher profits and
more choice; for large-scale industry, energy consumption
and total execution tome are the two important aspects of
cloud computing. In the current scenario, IT Enterprises are
trying to minimize the energy-consumption which, in turn,
maximizes the profit of the industry. And they are also trying
to reduce total execution time which, in turn, is concerned
with providing better Quality of Service (QoS). Therefore, in
this paper we have made an attempt to evaluate energy-
consumption and total execution time using CloudSim
simulator which helps to make evaluation performance of
energy consumption and total execution time of user
application.
A Strategic Evaluation of Energy-Consumption and Total Execution Time for Clo...Souvik Pal
Cloud computing is a very budding area in the
research field and as well as in the IT enterprises. Cloud
Computing is basically on-demand network access to a
collection of physical resources which can be provisioned
according to the need of cloud user under the supervision of
Cloud Service provider interaction. In this era of rapid usage
of Internet all over the world, Cloud computing has become
the center of Internet-oriented business place. For enterprises,
cloud computing is the worthy of consideration and they try to
build business systems with minimal costs, higher profits and
more choice; for large-scale industry, energy consumption
and total execution tome are the two important aspects of
cloud computing. In the current scenario, IT Enterprises are
trying to minimize the energy-consumption which, in turn,
maximizes the profit of the industry. And they are also trying
to reduce total execution time which, in turn, is concerned
with providing better Quality of Service (QoS). Therefore, in
this paper we have made an attempt to evaluate energyconsumption
and total execution time using CloudSim
simulator which helps to make evaluation performance of
energy consumption and total execution time of user
application.
Virtual Machine Migration and Allocation in Cloud Computing: A Reviewijtsrd
Cloud computing is an emerging computing technology that maintains computational resources on large data centers and accessed through internet, rather than on local computers. VM migration provides the capability to balance the load, system maintenance, etc. Virtualization technology gives power to cloud computing. The virtual machine migration techniques can be divided into two categories that is pre copy and post copy approach. The process to move running applications or VMs from one physical machine to another is known as VM migration. In migration process the processor state, storage, memory and network connection are moved from one host to another.. Two important performance metrics are downtime and total migration time that the users care about most, because these metrics deals with service degradation and the time during which the service is unavailable. This paper focus on the analysis of live VM migration Techniques in cloud computing. Khushbu Singh Chandel | Dr. Avinash Sharma "Virtual Machine Migration and Allocation in Cloud Computing: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29556.pdfPaper URL: https://www.ijtsrd.com/computer-science/computer-network/29556/virtual-machine-migration-and-allocation-in-cloud-computing-a-review/khushbu-singh-chandel
TASK SCHEDULING USING AMALGAMATION OF MET HEURISTICS SWARM OPTIMIZATION ALGOR...Journal For Research
Cloud Computing is the latest networking technology and also popular archetype for hosting the application and delivering of services over the network. The foremost technology of the cloud computing is virtualization which enables of building the applications, dynamically sharing of resources and providing diverse services to the cloud users. With virtualization, a service provider can guarantee Quality of Service to the user at the same time as achieving higher server consumption and energy competence. One of the most important challenges in the cloud computing environment is the VM placemnt and task scheduling problem. This paper focus on Metaheuristic Swarm Optimisation Algorithms(MSOA) deals with the problem of VM placement and Task scheduling in cloud environment. The MSOA is a simple parallel algorithm that can be applied in different ways to resolve the task scheduling problems. The proposed algorithm is considered an amalgamation of the SO algorithm and the Cuckoo search (CS) algorithm; called MSOACS. The proposed algorithm is evaluated using Cloudsim Simulator. The results proves the reduction of the makespan and increase the utilization ratio of the proposed MSOACS algorithm compared with SOA algorithms and Randomised Allocation Allocation (RA).
DYNAMIC ALLOCATION METHOD FOR EFFICIENT LOAD BALANCING IN VIRTUAL MACHINES FO...acijjournal
This paper proposes a Dynamic resource allocation method for Cloud computing. Cloud computing is a model for delivering information technology services in which resources are retrieved from the internet through web-based tools and applications, rather than a direct connection to a server. Users can set up
and boot the required resources and they have to pay only for the required resources. Thus, in the future providing a mechanism for efficient resource management and assignment will be an important objective of Cloud computing. In this project we propose a method, dynamic scheduling and consolidation mechanism that allocate resources based on the load of Virtual Machines (VMs) on Infrastructure as a service (IaaS). This method enables users to dynamically add and/or delete one or more instances on the basis of the load and the conditions specified by the user. Our objective is to develop an effective load balancing algorithm using Virtual Machine Monitoring to
maximize or minimize different performance parameters(throughput for example) for the Clouds of
different sizes (virtual topology de-pending on the application requirement).
Role of Virtual Machine Live Migration in Cloud Load BalancingIOSR Journals
Abstract: Cloud computing has touched almost every field of the life. Hence number of cloud application
consumers is increasing every day and so as the number of application request to the cloud provider. This leads
increment of workload in many of the cloud nodes. The motive to use load balancing concepts in cloud
environment is to efficiently utilize available resources keeping in mind that no any single system is heavily
loaded or not a single system is idle during the active phase of the request completion. Even though cloud
computing being a software facility most often, how does it actually performs well in heavily loaded
environment at processor level, is discussed in the paper. This paper aims to throw some light on what is cloud
load balancing and what is the role of Virtual machine migration in improving it.
Keywords: Cloud load balancing, Live Migration, Migration, Virtualization, Virtual machine.
Application of selective algorithm for effective resource provisioning in clo...ijccsa
Modern day continued demand for resource hungry services and applications in IT sector has led to
development of Cloud computing. Cloud computing environment involves high cost infrastructure on one
hand and need high scale computational resources on the other hand. These resources need to be
provisioned (allocation and scheduling) to the end users in most efficient manner so that the tremendous
capabilities of cloud are utilized effectively and efficiently. In this paper we discuss a selective algorithm
for allocation of cloud resources to end-users on-demand basis. This algorithm is based on min-min and
max-min algorithms. These are two conventional task scheduling algorithm. The selective algorithm uses
certain heuristics to select between the two algorithms so that overall makespan of tasks on the machines is
minimized. The tasks are scheduled on machines in either space shared or time shared manner. We
evaluate our provisioning heuristics using a cloud simulator, called CloudSim. We also compared our
approach to the statistics obtained when provisioning of resources was done in First-Cum-First-
Serve(FCFS) manner. The experimental results show that overall makespan of tasks on given set of VMs
minimizes significantly in different scenarios.
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.
dynamic resource allocation using virtual machines for cloud computing enviro...Kumar Goud
Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs., we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of “skewness” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing imbalance, we will mix completely different of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.
Index Terms—Cloud computing, resource management, virtualization, green computing.
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
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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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.
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Survey on virtual machine placement techniques in cloud computing environment
1. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 4, August 2014
Survey on Virtual Machine Placement Techniques in
Cloud Computing Environment
Rajeev Kumar Gupta and R. K. Pateriya
Department of Computer Science & Engineering, MANIT, Bhopal, India
ABSTRACT
In traditional data center numbers of services are run onto the dedicated physical servers. Most of the
time, these data centers are not used their full capacity in term of resources. Virtualization allows the
movement of VM from one host to the another host ,which is called virtual machine migration, so these
data centers can consolidate their services onto lesser number of physical servers than originally required.
Virtual machine placement is the part of the VM migration. To map the virtual machines to the physical
machines is called the VM placement. In other word, VM placement is the process to select the
appropriate host for the given VM. For the efficient utilization of the physical resources, VM should be
placed on to the suitable host. So many virtual machine placement algorithms have been proposed by
different researchers that run under cloud computing environment. Most of the VM placement algorithms
try to achieve some goal. This goal can either saving energy by shutting down some severs or it can be
maximizing the resources utilization. Four steps are involved in the VM machine migration process. First
step is to select the PM which is overload or undreloaded, next step is to select one or more VM, and then
select the PM where selected VM can be placed and last step is to transfer the VM. Selecting the suitable
host is one of the challenging task in the migration process, because wrong selection of host can increased
the number of migration, resource wastage and energy consumption. This paper only focuses to the third
step that is selecting a suitable PM that can host the VM. It shows an analysis of different existing Virtual
Machine’s placement algorithms with their anomalies.
KEYWORDS
Virtual machine, data centers, virtualization, migration, power saving
1. INTRODUCTION
During the last several decades, cloud computing is the new emerging technology in the field of
computer science. It became so famous because of their cheap, on-demand and pay as use
services [1]. Cloud computing provide three type of services that is Software as a Service (SaaS),
Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) [2] and it can be deploy in
three different way that is private, public and protected [3][4]. Private cloud can only access
within an organization, public cloud can be access anywhere in the word and the hybrid cloud is
the combination of private and public cloud. Private cloud offer more security than public cloud.
DOI : 10.5121/ijccsa.2014.4401 1
2. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 4, August 2014
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Fig. 1 cloud computing model
Virtualization [5, 6] is the key technology behind the cloud computing. It increased the resource
utilization by sharing the physical resources among multiple users. Virtual machine monitor
(Hypervisor) is responsible for all management related to the VM i.e. VM creation, destruction
and scheduling. It is a small software program which reside between the hardware and the host
OS must be installed onto the each host of the data center.
Fig.2 Cloud framework
Hypervisor create the VM for each user according to the user’s requirement. These VMs are
independent. One or more VM can assign to the user and each VM can run multiple applications.
Furthermore, numbers of virtual machines are hosted on a single host. In the cloud environment
resource required by the VM are changed dynamically, sometimes resource required by the VM
are not fulfil by the PM in which VM are currently running. This problem can be solved either by
adding some resources or by migrating VM. VM migration [7, 8,] is the process of moving VM
from one physical machine to another physical machine. VM migration solves the problem such
as fault tolerance, load balancing and resource consolidation etc. VM migration process consists
of four steps. First step is to select the PM from which the VM is migrated, second step is to
select the VM for the migration, next step is to select the PM, where the selected VM will be
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placed and last step is to transfer the VM. Out of these four step third step i.e. VM placement is
the more challenging task, because it directly affect the system performance. VM placement can
be defined as a mapping between the VM and the PM. In the cloud environment there are number
of host and each host run number of VMs. If the number of physical and virtual machines are less
then static VM placement can be possible, but if the number of virtual machine and physical
machine are more, dynamic VM placement methods is required. If n is the total number of virtual
machine and m is the total number of host then the number of possible mapping can be calculate
by the following equation [9]
3
Number of possible mapping = mn
This indicates as the number of virtual and physical machine are increased, virtual machine
placement becomes a challenging task.
2. CLASSIFICATION OF VM PLACEMENT ALGORITHMS
Goal of the VM placement can either saving energy by shutting down some severs or it can be
maximizing the resources utilization. Based on these goal placement algorithm are classified into
two type.
i. Power Based approach
ii. Application QoS based approach
Main aim of the power based approach is to save the energy. In these approach VM map to the
physical machines in such a `way, that each servers can utilized their maximum efficiency and the
other servers can be shut down depending on load conditions. While in the Application QoS
based approach a VM map to the PM with the aim of maximizing the QoS delivered by the
service provider.
3. LITERATURE SURVEY
VM placement problem is a non deterministic problem. Number of virtual machine placement
algorithms have been proposed [10, 11, 12] that run under cloud computing environment. This
section explains some of the exiting virtual machine placement approaches and their anomalies.
3.1. Heuristic based approach
3.1.1. First Fit
It is a greedy approach. In this approach scheduler visits the PM sequentially one by one and
placed VM to first PM that has enough resources. Each time when the new VM arrived, scheduler
starts searching the PM sequentially in the data center till it finds the first PM that has enough
resources. If none of the physical machine satisfied the resource requirement of the VM, then new
PM is activated and assigns VM to the newly activated PM. Main problem with this approach is
that load on the system can imbalanced.
3.1.2. Single Dimensional Best Fit
This methods use the single dimension (CPU, memory, bandwidth etc.) for placing a VM. When
VM arrived, scheduler visit the Physical Machines in the decreasing order of their capacity used
in a single dimension and place the VM to the first PM that has the enough resources. That means
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VM place to the PM which used the maximum capacity along with the given dimension. Problem
with approach is that it can increase the resource imbalancing because resource in the cloud is
multi-dimension (CPU, memory, bandwidth etc.). So there may be a situation where a host utilize
their full CPU capacity while other resources such as memory and bandwidth are underutilized.
N. Rodrigo et al. [17], proposed a heuristic for the mapping between VM and PM. Main aim of
this approach is to balance the CPU utilization on each PM. Only CPU utilization is consider as a
load metric, so after the mapping only amount of available CPU is check instead of whole PM.
Objective function of this method is to minimize the standard deviation of residual CPU in each
PM.
If there is n host in the data centers and m is the number of VM in each host then objective
function can be define as
4
=
=
PM is the reaming CPU capacity of the ith PM, cpui
Where rcpui
PM is the total CPU capacity of
the ith PM and is the CPU used by the jth VM.
Problem with this approach is that they only consider the CPU capacity for mapping between the
PM and VM. So other resource can be imbalance.
3.1.3. Volume Based Best Fit
This heuristic used the volume of the VM for placing a VM. This approach visits the Physical
Machines in a decreasing order of their volume and place VM to the first PM that has the enough
resources. That means Physical Machine which has the maximum volume will be considered first.
Sandpipier [13, 14] is a Xen based automated system, which is used for detecting and mitigating
the hot spot. It use the sand-volume to place the virtual machine, which is given by the formula
Sand-volume= * *
Where cpu, net and mem are the normalized utilization of the cpu, network and memory
respectively. In this method Physical Machines are visited in the decreasing order of their sand-volume
and place VM to the first PM that has the enough resources. So the Physical Machine
which has the maximum sand-volume will be considered first.
This approach may select the wrong PM because they are not considered the shape of the
resource utilization. Main reason to select the wrong PM is to convert 3D (CPU, network,
memory) resource information into the 1D that is sand-volume. So if two PM having the same
sand-volume then both physical machines are equally suitable for placing VM, this may not be
possible.
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3.1.4. Dot Product Based Fit
In this heuristic resource requirement of virtual machine and the total capacity of the physical
machine along the specified dimensions are expressed as vectors. Dot product of these two
vectors is calculated and then PMs are arranged into the decreasing order of their dot product.
VectorDot [7] method use the dot product of resource utilization vector ( ) of physical
machine and resource requirement vector of virtual machine ( ) to select physical machine
and choose the physical machine which having lowest dot product.
For the proper utilization of the resources it is necessary that the virtual machine which required
more CPU and less memory should be placed on the physical machine which has low CPU and
more memory utilization. This method seems good, but it can choose the wrong PM, because they
the not using the length of virtual machine ( ) and the remaining capacity of the physical
machine.
3.2 Constraint based approach
Constraint based approaches are use in the combinatorial search problems [15]. In these approach
some constraint are apply and these constraint must be fulfil during VM placement. These
constraints are
Capacity Constraints: For all dimension (CPU, memory and bandwidth) of a given physical
machine, sum of the resource utilize by all VMs running in that host should be less than or equal
to the total available capacity of that physical machine
i
cpu Ci
cpu j mi
i
mem Ci
mem j mi
i
bw Ci
bw j mi
Where Ci
cpu , Ci
mem and Ci
bw is the total cpu, memory and bandwidth capacity of the ith host
respectively and ui
cpu, ui
mem, and ui
bw are the total CPU, Memory and bandwidth used by the all
VM in the ith host respectively.
Placement Constraints: All virtual machines must be placed on to the available host.
SLA constraint: VM should be placed to the PM where it fulfils the SLA.
Quality of services (QoS) constraint: Some quality of services constraint such as throughput,
availability etc. must be considered during the VM placement.
Constraint Programming is useful where the input data is already known. That means we know
the demands of the VMs, before calculating the cost function.
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3.3 Bin packing problem
Bin packing problem [16] is a NP hard problem. If PM and the VM are consider as a three
dimension object, then VM placement problem is similar to the bin packing problem where item
represent the VM and container represent the PM. In the bin packing problem number of item
(VM) are placed inside a large container (PM). The aim is to places a number of items into a
single container as possible. So that the number of container required to packing the item is
minimized.
Bin packing problem is different from the VM placement problem. In the bin packing problem
bins can be placed side by side or one on top of the other. But in the case of VM placement,
placing VMs side by side or one on top of the other is not a valid operation. This is because the
resource cannot be reused by any other VM, once a resource is utilized by a VM.
3.4 Stochastic Integer Programming
Stochastic Integer Programming is used to optimize the problems, which involve some unknown
data. VM placement problem can be consider as a Stochastic Integer Programming because
resource demand of the VM are known or it can be estimated and the objective is to find the
suitable host which consume less energy and minimize the resources wastages.
Stochastic Integer Programming can be use where the future demands of the resources are not
known, but their probability distributions are known or it can be calculated.
3.5 Genetic Algorithm
Genetic algorithm is a global search heuristics. It is useful where objective functions changed
dynamically. This approach is inspired by the evolutionary biology such as inheritance.
Genetic Algorithm can be use to solve the bin packing problem with some constraints. It is useful
for the static VM placements, where the resource demands do not vary during a predefine period
of time.
4. CONCLUSION
Efficient placement of the VM can improved the overall performance of the system. Virtual
machine placement is a technique which maps the VM to the appropriate PM. Since the size of
the data center is large in the cloud computing environment, so selecting a proper host for placing
the VM is a very challenging task during the virtual machine migration. In this paper number of
VM placement approach are explained with their anomalies. Each placement algorithm performs
well under some specific conditions. So it is a critical task to choose a technique that is suitable
for both the cloud user and cloud provider.
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