Cache replacement algorithms are critical building blocks of storage systems. This paper examines the characteristics of metadata caches and argues that they inherently exhibit correlated references, even when the corresponding data accesses do not contain correlated references. The presence of correlated references reduces the effectiveness of cache replacement algorithms because these references are often mistakenly categorized as hot blocks. Clock2Q+ is specifically designed for metadata caches and has been implemented in vSAN and VDFS, two flagship storage products of VMware by Broadcom. Similar to S3-FIFO, Clock2Q+ uses three queues; however, Clock2Q+ introduces a correlation window in the Small FIFO queue, where blocks in this window do not set the reference bit. This simple enhancement allows Clock2Q+ to outperform state-of-the-art replacement algorithms. Compared to S3-FIFO, the second-best performing algorithm, Clock2Q+ achieves up to a 28.5% lower miss ratio on metadata traces. Clock2Q+ possesses the essential properties required for large-scale storage systems: it has low CPU overhead on cache hits, low memory overhead, scales efficiently to multiple CPUs, and is both ea
A study of VMware ESXi 5.1 server has been carried out to find the optimal set of parameters which suggest usage of different resources of the server. Feature selection algorithms have been used to extract the optimum set of parameters of the data obtained from VMware ESXi 5.1 server using esxtop command. Multiple virtual machines (VMs) are running in the mentioned server. K-means algorithm is used for clustering the VMs. The goodness of each cluster is determined by Davies Bouldin index and Dunn index respectively. The best cluster is further identified by the determined indices. The features of the best cluster are considered into a set of optimal parameters.
Virtualization technology has provided many benefits to organizations, but it cannot provide automation. This causes operational expenditure (OpEx) inefficiencies, which are solved by cloud computing (vCloud Director vApps). Organizations have adopted virtualization technology to reduce IT costs and meet business needs. In addition to improved CapEx efficiency, virtualization has enabled organizations to respond to business needs faster. While virtualization has dramatically optimized core IT infrastructures, organizations struggle to reduce OpEx costs. Because virtualization only addresses server consolidation, administrators are faced with the manual and resource-intensive day-to-day tasks of managing the rest of the data center: networking, storage, user management. This manuscript presents details on how leverage vApps based on a virtualized platform to improve CapEx efficiency in today s data center. The combination of virtualization and cloud computing can transform the data center into a dynamic, scalable, and agile resource capable of achieving significant CapEx and OpEx cost savings.
Web client fingerprinting has become a widely used technique for uniquely identifying users, browsers, operating systems, and devices with high accuracy. While it is beneficial for applications such as fraud detection and personalized experiences, it also raises privacy concerns by enabling persistent tracking and detailed user profiling. This paper introduces an advanced fingerprinting method using WebAssembly (Wasm) - a low-level programming language that offers near-native execution speed in modern web browsers. With broad support across major browsers and growing adoption, WebAssembly provides a strong foundation for developing more effective fingerprinting methods. In this work, we present a new approach that leverages WebAssembly's computational capabilities to identify returning devices-such as smartphones, tablets, laptops, and desktops across different browsing sessions. Our method uses subtle differences in the WebAssembly JavaScript API implementation to distinguish between Chromium-based browsers like Google Chrome and Microsoft Edge, even when identifiers such as the User-Agent are completely spoofed, achieving a false-positive rate of less than 1%. The fingerprint is
This paper of work examines the SolarWinds attack, designed on Orion Platform security incident. It analyses the persistent threats agents and potential technical attack techniques to gain unauthorized access. In 2020 SolarWinds attack indicates an initial breach disclosure on Orion Platform software by malware distribution on IT and government organizations such as Homeland Security, Microsoft and Intel associated with supply chains leaks consequences from small loopholes in security systems. Hackers increased the number of infected company and businesses networks during the supply-chain attack, hackers were capable to propagate the attack by using a VMware exploit. On the special way they started to target command injections, privilege escalations, and use after free platforms of VMware. In this way, they gained access to Virtual Machines and in the east way pivot other servers. This literature review aim to analyze the security gap regarding to SolarWinds incident on Orion Platform, the impact on industry and financial sectors involving the elements of incident response plan. Therefore, this research paper ensures specifications of proper solutions for possible defense security
Cloud computing has transformed the way organizations manage and scale their IT infrastructure by offering flexible, scalable, and cost-effective solutions. However, the Infrastructure as a Service (IaaS) model faces performance challenges primarily due to the limitations imposed by virtualization technology. This paper focuses on designing an effective virtualization technique for IaaS, aiming to improve infrastructure-level performance. Through a systematic literature review and a design, development, and evaluation approach, various virtualization techniques such as full virtualization, paravirtualization, and hardware-assisted virtualization are explored. The study also considers the role of hypervisors like Xen, KVM, and VMware ESXi in improving performance. The proposed solution seeks to optimize resource utilization, minimize latency, and enhance overall throughput in IaaS environments. Finally, the research discusses the potential application of this virtualization technique for public cloud computing solutions tailored for Ethiopian Small and Medium Enterprises (ESMEs) using platforms like Amazon EC2.
In this work, we propose a testbed environment to capture the attack strategies of an adversary carrying out a cyber-attack on an enterprise network. The testbed contains nodes with known security vulnerabilities which can be exploited by hackers. Participants can be invited to play the role of a hacker (e.g., black-hat, hacktivist) and attack the testbed. The testbed is designed such that there are multiple attack pathways available to hackers. We describe the working of the testbed components and discuss its implementation on a VMware ESXi server. Finally, we subject our testbed implementation to a few well-known cyber-attack strategies, collect data during the process and present our analysis of the data.
ATLASv2 is based on a previously generated dataset included in "ATLAS: A Sequence-based Learning Approach for Attack Investigation." The original ATLAS dataset is comprised of Windows Security Auditing system logs, Firefox logs, and DNS logs via WireShark. In ATLASv2, we aim to enrich the ATLAS dataset with higher quality background noise and additional logging vantage points. This work replicates the ten attack scenarios described in ATLAS, but extends the logging to include Sysmon logs and events tracked through VMware Carbon Black Cloud. The main contribution of ATLASv2 is to improve the quality of the benign system activity and the integration of the attack scenarios. Instead of relying on automated scripts to generate activity, we had two researchers use the victim machines as their primary work stations throughout the course of the engagement. This allowed us to capture system logs on actual user behavior. Additionally, the researchers conducted the attacks in a lab setup allowing the integration of the attack into the work flow of the victim user. This allows the ATLASv2 dataset to provide realistic system logs that mirror the system log activity generated in real-world atta
Virtualization started to gain traction in the domain of information technology in the early 2000s when managing resource distribution was becoming an uphill task for developers. As a result, tools like VMWare, Hyper V (hypervisor) started making inroads into the software repository on different operating systems. VMWare and Hyper V could support multiple virtual machines running on them with each having their own isolated environment. Due to this isolation, the security aspects of virtual machines (VMs) did not differ much from that of physical machines (having a dedicated operating system on hardware). The advancement made in the domain of linux containers (LXC) has taken virtualization to an altogether different level where resource utilization by various applications has been further optimized. But the container security has assumed primary importance amongst the researchers today and this paper is inclined towards providing a brief overview about comparisons between security of container and VMs.
This manuscript presents teaching and curriculum design for Information Technology classes. Today, students demand hands-on activities for the newest technologies. It is feasible to satisfy this appetite for exciting education by employing server virtualization technologies to teach advanced concepts with extensive hands-on assignments. Through utilization of virtualized servers, students are able to deploy, secure and manage virtual machines and networks in a contained environment. Various techniques, assessment tools and experiences will be analyzed and presented by this manuscript. Previous teaching cases for Information Systems or Information Technology classes are done using non-commercial products, such as free VMware Server or VMware Player. Such products have very limited functionality in terms of networking, storage and resource management. Several advanced datacenter functions, such as Distributed Power Management (DPM), vMotion and others, are not available in desktop versions of that type of virtualization software. This manuscript introduces the utilization of commercial software, such as vSphere 4.1, with full datacenter functionality and operations for teaching Infor
Virtualization has gained astonishing popularity in recent decades. It is applied in several application domains, including mainframes, personal computers, data centers, and embedded systems. While the benefits of virtualization are no longer to be demonstrated, it often comes at the price of performance degradation compared to native execution. In this work, we conduct a comparative study on the performance outcome of VMWare, KVM, and Docker against compute-intensive, IO-intensive, and system benchmarks. The experiments reveal that containers are the way-to-go for the fast execution of applications. It also shows that VMWare and KVM perform similarly on most of the benchmarks.
Over a past few decades, VM's or Virtual machines have sort of gained a lot of momentum, especially for large scale enterprises where the need for resource optimization & power save is humongous, without compromising with performance or quality. They are a perfect environment to experiment with new applications/technologies in a completely secure and closed environment. This paper discusses how the VM technology can be leveraged to solve day to day requirement of an odd hundreds or thousands of people, organization-wide, with new computational resources using a cluster of heterogeneous low or high-end machines, independent of underlying OS, thereby maximizing resource utilization. It takes into account both opensource (like VirtualBox) & other proprietary technologies (like VMWare Workstations) available till date to propose a viable solution using cloud computing concept. The ease of scalability to multiple folds for optimizing performance & catering to an even larger set are some of the salient features of this approach. Using the snapshot feature, the state of any VM instance could be saved & served back again on request. Now, this implementation is also served b
This paper is about three virtualization modes: VMware, Parallels, and Boot Camping. The trade off of their testing is the hardware requirements. The main question is, among the three, which is the most suitable? The answer actually varies from user to user. It depends on the user needs. Moreover, it is necessary to consider its performance, graphics, efficiency and reliability, and interoperability, and that is our major scope. In order to take the final decision in choosing one of the modes it is important to run some tests, which costs a lot in terms of money, complexity, and time consumption. Therefore, in order to overcome this trade off, most of the research has been done through online benchmarking and my own anticipation. The final solution was extracted after comparing all previously mentioned above and after rigorous testing made which will be introduced later in this document.
How can one recognize coordination languages and technologies? As this report shows, the common approach that contrasts coordination with computation is intellectually unsound: depending on the selected understanding of the word "computation", it either captures too many or too few programming languages. Instead, we argue for objective criteria that can be used to evaluate how well programming technologies offer coordination services. Of the various criteria commonly used in this community, we are able to isolate three that are strongly characterizing: black-box componentization, which we had identified previously, but also interface extensibility and customizability of run-time optimization goals. These criteria are well matched by Intel's Concurrent Collections and AstraKahn, and also by OpenCL, POSIX and VMWare ESX.
We discuss how VMware is solving the following challenges to harness data to operate our ML-based anomaly detection system to detect performance issues in our Software Defined Data Center (SDDC) enterprise deployments: (i) label scarcity and label bias due to heavy dependency on unscalable human annotators, and (ii) data drifts due to ever-changing workload patterns, software stack and underlying hardware. Our anomaly detection system has been deployed in production for many years and has successfully detected numerous major performance issues. We demonstrate that by addressing these data challenges, we not only improve the accuracy of our performance anomaly detection model by 30%, but also ensure that the model performance to never degrade over time.
In virtualized data centers, consolidation of Virtual Machines (VMs) on minimizing the number of total physical machines (PMs) has been recognized as a very efficient approach. This paper considers the energy-efficient consolidation of VMs in a Cloud Data center. Concentrating on CPU-intensive applications, the objective is to schedule all requests non-preemptively, subjecting to constraints of PM capacities and running time interval spans, such that the total energy consumption of all PMs is minimized (called MinTE for abbreviation). The MinTE problem is NP-complete in general. We propose a self-adaptive approached called SAVE. The approach makes decisions of the assignment and migration of VMs by probabilistic processes and is based exclusively on local information, therefore it is very simple to implement. Both simulation and real environment test show that our proposed method SAVE can reduce energy consumption about 30% against VMWare DRS and 10-20% against EcoCloud on average.
Access control is an important component for web services such as a cloud. Current clouds tend to design the access control mechanism together with the policy language on their own. It leads to two issues: (i) a cloud user has to learn different policy languages to use multiple clouds, and (ii) a cloud service provider has to customize an authorization mechanism based on its business requirement, which brings high development cost. In this work, a new access control policy language called PERM modeling language (PML) is proposed to express various access control models such as access control list (ACL), role-based access control (RBAC) and attribute-based access control (ABAC), etc. PML's enforcement mechanism is designed in an interpreter-on-interpreter manner, which not only secures the authorization code with sandboxing, but also extends PML to all programming languages that support Lua. PML is already adopted by real-world projects such as Intel's RMD, VMware's Dispatch, Orange's Gobis and so on, which proves PML's usability. The performance evaluation on OpenStack, CloudStack and Amazon Web Services (AWS) shows PML's enforcement overhead per request is under 5.9us.
Storage replication is one of the essential requirements for network environments. While many forms of Network Attached Storage (NAS), Storage Area Networks (SAN) and other forms of network storage exist, there is a need for a reliable synchronous storage replication technique between distant sites (less than 1 mile). Such technology allows setting new standards for network failover and failback systems for virtual servers; specifically, addressing the growing need for effective disaster recovery (DR) planning. The purpose of this manuscript is to identify newest technologies such as SAN/iQ and Storage VMotion that allow for remote storage synchronous replication for virtual servers. This study provides an analysis and a comparison of various SANs that create solutions for enterprise needs. Additionally, the interoperability of these technologies with the industry s leading product VMware ESX Server will be discussed.
Virtualization is a framework of dividing the resources of a computer into multiple execution environments which offers a lot of benefits including flexibility, security, ease to configuration and reduction of cost but at the same time it also brings a certain degree of performance overhead. Furthermore, Virtual Machine Monitor (VMM) is the core component of virtual machine (VM) system and its effectiveness greatly impacts the performance of the whole system. This review paper will try to describe the basic knowledge about various virtual machine monitors such as VMware and VirtualBox. It also discussed and explores the benchmark LINPACK and CloudSim available for cloud computing. This benchmark and CloudSim can be used to measure the performance of two different virtual machine monitors in terms of processing speed, time, bandwidth, quality and response of the cloud computing network.