1. A system for efficient resource utilization in data centres using virtualization, comprising: a physical infrastructure module including servers, storage, and network devices; a virtualization layer overlaying the physical infrastructure module, partitioning physical resources into virtual units; a resource allocation engine determining resource distribution based on demand and operational metrics; and a monitoring module tracking real-time resource utilization and performance metrics.

2. The system of claim 1, wherein the virtualization layer includes: a hypervisor managing the creation, execution, and termination of virtual machines on the physical servers.

3. The system of claim 1, further comprising: a load balancer distributing incoming network traffic across multiple virtual machines to optimize resource usage.

4. The system of claim 1, wherein the resource allocation engine employs: predictive algorithms anticipating future resource requirements and pre-emptively reallocating virtual resources accordingly.

5. The system of claim 1, further comprising: a storage virtualization unit segmenting physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand.

6. A method for efficient resource utilization in data centres using virtualization, comprising: partitioning physical resources in a data centre into virtual units; dynamically allocating virtual resources based on current and predicted demand; monitoring real-time utilization of both physical and virtual resources; and adjusting allocations in response to the monitored utilization.

7. The method of claim 6, further comprising: distributing incoming network traffic across multiple virtual resources using a load balancing mechanism, ensuring optimal resource usage.

8. The method of claim 6, including: segmenting physical storage resources into virtual storage pools; and resizing and provisioning virtual storage resources based on current storage demand.

9. The method of claim 6, wherein dynamically allocating resources involves: forecasting future resource requirements using historical data; and pre-emptively reallocating virtual resources based on the forecast to prevent resource contention.

10. The method of claim 6, further comprising: initiating migration of virtual machines or containers between physical servers in response to changing resource demands or maintenance requirements, ensuring uninterrupted operation and optimal resource distribution. Virtualization in Data Centers for Efficient Resource Utilization Abstract The present invention presents a system for optimizing resource utilization within data centers through virtualization, encompassing a physical infrastructure module housing servers, storage, and network devices, a virtualization layer superimposing the physical infrastructure to create virtual units from physical resources, a resource allocation engine configuring resource distribution based on real-time demand and operational metrics, and a monitoring module overseeing instantaneous resource usage and performance metrics. This system offers an integrated solution for enhanced efficiency by dynamically partitioning and allocating resources to match demand, optimizing data center operations through virtualization and adaptive resource management. , Claims:Claims :

1. A system for efficient resource utilization in data centres using virtualization, comprising: a physical infrastructure module including servers, storage, and network devices; a virtualization layer overlaying the physical infrastructure module, partitioning physical resources into virtual units; a resource allocation engine determining resource distribution based on demand and operational metrics; and a monitoring module tracking real-time resource utilization and performance metrics.

2. The system of claim 1, wherein the virtualization layer includes: a hypervisor managing the creation, execution, and termination of virtual machines on the physical servers.

3. The system of claim 1, further comprising: a load balancer distributing incoming network traffic across multiple virtual machines to optimize resource usage.

4. The system of claim 1, wherein the resource allocation engine employs: predictive algorithms anticipating future resource requirements and pre-emptively reallocating virtual resources accordingly.

5. The system of claim 1, further comprising: a storage virtualization unit segmenting physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand.

6. A method for efficient resource utilization in data centres using virtualization, comprising: partitioning physical resources in a data centre into virtual units; dynamically allocating virtual resources based on current and predicted demand; monitoring real-time utilization of both physical and virtual resources; and adjusting allocations in response to the monitored utilization.

7. The method of claim 6, further comprising: distributing incoming network traffic across multiple virtual resources using a load balancing mechanism, ensuring optimal resource usage.

8. The method of claim 6, including: segmenting physical storage resources into virtual storage pools; and resizing and provisioning virtual storage resources based on current storage demand.

9. The method of claim 6, wherein dynamically allocating resources involves: forecasting future resource requirements using historical data; and pre-emptively reallocating virtual resources based on the forecast to prevent resource contention.

10. The method of claim 6, further comprising: initiating migration of virtual machines or containers between physical servers in response to changing resource demands or maintenance requirements, ensuring uninterrupted operation and optimal resource distribution.

Description:Virtualization in Data Centers for Efficient Resource Utilization
Field of the Invention
[0001] The present invention is anchored in the domain of data center technologies and operations. Specifically, this invention focuses on the methodologies and systems associated with virtualization techniques aimed at optimizing resource allocation and utilization within data centers. At its essence, the invention seeks to revolutionize how computing, storage, and network resources are partitioned, allocated, and managed by decoupling them from underlying physical hardware. Through this innovative approach, the invention aspires to boost operational efficiency, enhance scalability, and reduce overhead costs, paving the way for more agile and responsive data center environments.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Virtualization has emerged as a transformative technology in the realm of data centers, revolutionizing the way computing resources are provisioned, managed, and utilized. Traditional data center models often suffer from underutilization of hardware resources, leading to increased costs, energy consumption, and inefficiencies. Virtualization addresses these challenges by creating virtual instances of servers, storage, and networking resources, allowing multiple workloads to run independently on a single physical machine. This approach optimizes resource utilization, enhances scalability, and improves overall data center efficiency.
[0004] VMware, a pioneer in virtualization technology, introduced server virtualization solutions that enable multiple virtual machines (VMs) to run on a single physical server. VMware's ESXi hypervisor separates the physical hardware from the virtualized instances, ensuring isolation and efficient resource allocation. This technology has led to significant improvements in data center efficiency by consolidating workloads and reducing hardware costs. The concept of server virtualization laid the foundation for broader data center virtualization practices.
[0005] Storage virtualization abstracts physical storage resources from applications and servers, creating a unified pool of storage that can be allocated dynamically to different workloads. Technologies like Storage Area Networks (SANs) provide centralized management and allocation of storage resources. IBM's SAN Volume Controller is an example of a product that implements storage virtualization, offering simplified management and improved utilization of storage devices across the data center.
[0006] Software-Defined Networking (SDN) virtualizes network infrastructure by separating the control plane from the data plane, allowing centralized management and orchestration of network resources. SDN enables dynamic allocation of network resources to different applications and services based on their requirements. OpenFlow, a widely adopted protocol for SDN, exemplifies the separation of control and data planes, leading to efficient network resource utilization and flexibility.
[0007] Virtual Desktop Infrastructure (VDI) extends virtualization to end-user computing by hosting desktop operating systems and applications on virtual machines in the data center. This centralizes management, security, and updates, while providing users with a consistent experience across devices. Citrix Virtual Apps and Desktops and VMware Horizon are examples of VDI solutions that optimize resource utilization, streamline management, and enhance security in the context of end-user computing.
[0008] Containerization, a lightweight form of virtualization, packages applications and their dependencies in isolated containers. Docker, along with orchestration platforms like Kubernetes, has revolutionized application deployment and scalability. Containers share the host OS kernel, resulting in minimal overhead and efficient utilization of system resources. This approach enables faster application deployment, seamless scaling, and efficient resource management.
[0009] Virtualization not only optimizes resource utilization but also contributes to energy-efficient data center management. Techniques like VM migration and consolidation allow data centers to dynamically allocate workloads to energy-efficient servers while powering down underutilized machines. Green computing initiatives by companies like Google and Facebook incorporate virtualization strategies to reduce carbon footprints and operational costs.
[00010] In summary, virtualization in data centers has revolutionized resource utilization and operational efficiency. From server and storage virtualization to network and desktop virtualization, the technology has advanced in various forms, enabling dynamic allocation of resources, simplified management, and reduced infrastructure costs. These prior art examples collectively demonstrate the evolution and widespread adoption of virtualization techniques to create more agile, scalable, and environmentally sustainable data center environments.
[00011]
[00012] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
Summary
[00013] Various objects, features, and advantages of the disclosed subject matter can be more fully appreciated with reference to the following detailed description of the disclosed subject matter when considered in connection with the following drawings, in which like reference numerals identify like elements.
[00014] The present invention is anchored in the domain of data center technologies and operations. Specifically, this invention focuses on the methodologies and systems associated with virtualization techniques aimed at optimizing resource allocation and utilization within data centers. At its essence, the invention seeks to revolutionize how computing, storage, and network resources are partitioned, allocated, and managed by decoupling them from underlying physical hardware. Through this innovative approach, the invention aspires to boost operational efficiency, enhance scalability, and reduce overhead costs, paving the way for more agile and responsive data center environments.
[00015] The introduced system revolutionizes resource utilization in data centers by harnessing the potential of virtualization, leading to unparalleled efficiency gains. The system is characterized by its core components: a physical infrastructure module incorporating servers, storage, and network devices, and a virtualization layer that seamlessly overlays this infrastructure. This layer skillfully partitions the physical resources into versatile virtual units, giving rise to a dynamic and adaptable environment.
[00016] To ensure optimized resource allocation, a resource allocation engine plays a pivotal role. This engine leverages real-time demand and operational metrics to strategically distribute resources across the virtual units. Furthermore, a sophisticated monitoring module continuously tracks resource utilization and performance metrics in real-time, ensuring a well-informed approach to resource management.
[00017] A key feature within the virtualization layer is the presence of a hypervisor - a fundamental element managing the creation, execution, and termination of virtual machines on the physical servers. This hypervisor guarantees seamless orchestration of virtual resources, translating into enhanced operational efficiency.
[00018] To refine resource allocation, a load balancer is integrated, effectively distributing incoming network traffic across multiple virtual machines. This approach optimizes resource utilization, preventing bottlenecks and ensuring the smooth operation of applications.
[00019] The resource allocation engine showcases predictive algorithms that proactively anticipate future resource requirements. This enables preemptive reallocation of virtual resources, ensuring that the environment remains responsive and adaptive to evolving needs.
[00020] Furthermore, the system introduces a storage virtualization unit, segmenting physical storage devices into dynamic virtual storage pools. This unique approach enables dynamic resizing and provisioning based on real-time demand, streamlining storage management and enhancing the agility of the infrastructure.
[00021] In essence, the system underscores the evolution of resource utilization within data centers. Through the synergy of physical and virtual components, it demonstrates a comprehensive understanding of modern data center requirements. By employing predictive algorithms, leveraging storage virtualization, and orchestrating resource allocation, the system offers an innovative solution to the ongoing challenge of efficient resource utilization in contemporary data centers.
[00022] The method introduced presents an innovative approach to enhancing resource utilization efficiency within data centers, harnessing virtualization to optimize operations. The process commences by intelligently partitioning the physical resources in a data center into adaptable virtual units. This foundation lays the groundwork for dynamic resource allocation that aligns with both current demand and predictive trends.
[00023] To achieve this, the method employs a multi-faceted approach. Real-time monitoring of resource utilization, encompassing both physical and virtual domains, provides crucial insights into performance. This real-time tracking forms the basis for continuous refinement of resource allocation strategies.
[00024] Integral to the method is the capacity to dynamically allocate virtual resources in response to changing demands. This allocation is facilitated through a combination of historical data analysis and predictive modeling. By forecasting future resource requirements based on historical trends, the method preemptively reallocates virtual resources, mitigating potential contention and ensuring seamless operation even during peak loads.
[00025] An essential enhancement to resource allocation is the load balancing mechanism. This mechanism effectively distributes incoming network traffic across multiple virtual resources. The outcome is optimal resource utilization, reducing the risk of bottlenecks and ensuring a balanced distribution of network traffic.
[00026] Storage management is equally addressed within the method. Physical storage resources are segmented into virtual storage pools, allowing for flexible resizing and provisioning based on prevailing storage demands. This dynamic approach aligns storage resources with current requirements, minimizing inefficiencies.
[00027] Furthermore, the method introduces proactive measures for maintaining optimal resource distribution. Migration of virtual machines or containers between physical servers is initiated in response to fluctuating resource demands or maintenance requirements. This proactive approach guarantees uninterrupted operation while simultaneously optimizing resource distribution across the data center.
[00028] In essence, the method revolutionizes resource utilization in data centers through virtualization-driven strategies. By effectively partitioning, allocating, and monitoring resources, it ensures optimal performance while adapting to changing demands. With features such as load balancing, predictive allocation, and seamless migration, the method addresses the complexities of modern data center operations, contributing to enhanced efficiency and performance.
[00029]
Brief Description of the Drawings
[00030] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00031] FIG. 1 represents an architectural overview of a system for efficient resource utilization in data centres using virtualization, according to some embodiments of the present disclosure.
[00032] FIG. 2 shows an exemplary detailed schematic flow diagram of a method for efficient resource utilization in data centres using virtualization, according to some embodiments of the present disclosure.
[00033]
Detailed Description
[00034] The following is a detailed description of exemplary embodiments to illustrate the principles of the invention. The embodiments are provided to illustrate aspects of the invention, but the invention is not limited to any embodiment. The scope of the invention encompasses numerous alternatives, modifications and equivalent; it is limited only by the claims.
[00035] In view of the many possible embodiments to which the principles of the present discussion may be applied, it should be recognized that the embodiments described herein with respect to the drawing figures are meant to be illustrative only and should not be taken as limiting the scope of the claims. Therefore, the techniques as described herein contemplate all such embodiments as may come within the scope of the following claims and equivalents thereof.
[00036] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different instances in the description and the figures may indicate similar or identical items.
[00037] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00038] The present invention is anchored in the domain of data center technologies and operations. Specifically, this invention focuses on the methodologies and systems associated with virtualization techniques aimed at optimizing resource allocation and utilization within data centers. At its essence, the invention seeks to revolutionize how computing, storage, and network resources are partitioned, allocated, and managed by decoupling them from underlying physical hardware. Through this innovative approach, the invention aspires to boost operational efficiency, enhance scalability, and reduce overhead costs, paving the way for more agile and responsive data center environments.
[00039] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00040] Data centres are critical for hosting and delivering applications and services in today's digital landscape. However, data centres often encounter issues such as underutilized resources, uneven workloads, and inefficient allocation of hardware. To mitigate these challenges, the proposed system 100 leverages virtualization to optimize resource utilization in data centres, ensuring that hardware resources are effectively shared and allocated based on real-time demand.
[00041] Data centres play a pivotal role in modern computing, but they often face challenges related to resource allocation and efficiency. According to a pictorially portrayal in FIG. 1, illustrating an architectural setup of the system 100 that addresses these challenges by utilizing virtualization to enhance resource utilization in data centres. By employing a physical infrastructure module 102, a virtualization layer 104, a resource allocation engine 106, and a monitoring module 108, this system 100 optimizes resource allocation based on demand and operational metrics. Detailed descriptions, examples, and scenarios illustrate how each component contributes to efficient resource utilization.
[00042] At the foundation of the system lies the physical infrastructure module, comprising servers, storage devices, and network equipment. These components form the backbone of data centres and provide the resources required to run applications and services. For example, a large e-commerce company operates a data centre housing multiple servers, storage arrays, and network switches. The physical infrastructure module constitutes the hardware foundation for hosting their online store and managing customer data.
[00043] The virtualization layer overlays the physical infrastructure module, partitioning physical resources into virtual units. This layer enables the creation of virtual machines (VMs), each of which operates as an independent environment with its own operating system and applications. For example, within the data centre, the virtualization layer creates multiple virtual machines on a single physical server. These VMs allow different applications, such as web servers and databases, to run independently, ensuring efficient resource utilization.
[00044] The heart of the system, the resource allocation engine, intelligently determines resource distribution based on demand and operational metrics. It optimizes the allocation of physical resources to virtual units, ensuring that hardware resources are used effectively. For example, during peak shopping seasons, the resource allocation engine identifies increased demand on the e-commerce website. It dynamically allocates more CPU and memory resources to the VM hosting the online store, ensuring smooth customer experiences.
[00045] To maintain real-time insight into resource usage and performance metrics, the monitoring module continuously tracks and reports on the state of the virtualized environment. It aids in identifying inefficiencies, bottlenecks, and opportunities for optimization. The monitoring module detects a sudden spike in network traffic on a specific virtual machine. This information prompts administrators to allocate additional network bandwidth, preventing performance degradation.

[00046] The virtualization layer incorporates a hypervisor, responsible for managing the creation, execution, and termination of virtual machines on the physical servers. For example, a hypervisor enables a single physical server to host multiple VMs, each running a different operating system. This facilitates compatibility for various applications, enhancing overall resource utilization.
[00047] To manage incoming network traffic, the system includes a load balancer that evenly distributes network requests across multiple virtual machines. This optimizes resource usage and prevents overload on any single VM. For example, an online gaming platform utilizes a load balancer to evenly distribute user requests to different VMs. This prevents server congestion during peak usage periods, ensuring smooth gameplay experiences.
[00048] The resource allocation engine employs predictive algorithms that anticipate future resource requirements. By pre-emptively reallocating resources, the system ensures optimal performance even during fluctuating workloads. For example, a video streaming service uses predictive algorithms to allocate more resources to specific VMs ahead of anticipated traffic surges, preventing video buffering and ensuring seamless playback.
[00049] Expanding the concept of virtualization, the system includes a storage virtualization unit. This unit segments physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand. For example, a healthcare provider uses a storage virtualization unit to allocate storage resources to electronic medical records. As the records grow in size, the system dynamically allocates more storage space without disrupting services.
[00050] Referring to one or more preceding embodiments, the system 100 for efficient resource utilization in data centres using virtualization offers a holistic approach to optimizing resource allocation and performance. By incorporating a physical infrastructure module, a virtualization layer, a resource allocation engine, and a monitoring module, the system ensures that data centres operate with enhanced efficiency and minimal resource waste. Through real-world examples and scenarios, this disclosure demonstrates how each component contributes to effective resource utilization, ensuring seamless operation of applications and services within data centres.
[00051] Modern data centres are critical for hosting a wide range of applications and services. However, managing the allocation of physical resources such as servers, storage, and network devices can be challenging, often leading to underutilization or resource contention. This comprehensive disclosure presents a method 200 for optimizing resource utilization within data centres using virtualization techniques.
[00052] Figuratively depicted in FIG. 2, representing a flow diagram of the method 200, encompasses steps of (at step 202) partitioning physical resources into virtual units, (at step 204) dynamically allocating virtual resources based on demand predictions, (at step 206) real-time monitoring of resource utilization, and (at step 208) adaptive adjustments to allocations. The method 200 enhances data centre efficiency by ensuring that physical resources are optimally utilized, leading to improved performance and reduced wastage. Detailed descriptions, practical examples, and use cases highlight how each step of the method contributes to efficient resource management in data centres.
[00053] The first step of the method 200 involves dividing the physical resources present in a data centre into smaller virtual units. This virtualization layer creates an abstraction that enables the efficient allocation of resources to different workloads. For instance, a data centre possesses a pool of physical servers. Through virtualization, these servers are partitioned into multiple virtual machines (VMs), each acting as an independent computing environment. This partitioning allows for optimized resource allocation and isolation of workloads.
[00054] The method dynamically allocates virtual resources based on both current demand and predictive analysis of future requirements. This approach ensures that resources are allocated precisely when and where they are needed, eliminating resource wastage. For instance, during peak hours of an e-commerce website, the method detects increased user traffic and allocates additional CPU and memory resources to the corresponding VMs. As the traffic subsides, the method reallocates these resources to other VMs, maintaining optimal utilization.
[00055] To maintain a clear understanding of resource consumption, the method continuously monitors the utilization of both physical and virtual resources. Real-time monitoring provides insights into resource patterns, bottlenecks, and potential areas for optimization. For instance, the method tracks CPU, memory, and network utilization across all VMs. In real-time, administrators can identify VMs operating at full capacity and allocate additional resources to ensure uninterrupted service.
[00056] The method's adaptability is a crucial aspect. By tracking resource utilization, the method makes informed decisions to adjust resource allocations as needed, optimizing performance and minimizing resource wastage. If a particular VM experiences a sudden surge in network traffic, the method detects the increased load and allocates additional network bandwidth to ensure smooth operations. Conversely, if a VM's utilization drops significantly, the method reallocates its resources to other VMs to prevent resource underutilization.
[00057] To evenly distribute incoming network traffic, the method incorporates a load balancing mechanism. This ensures that network requests are directed to different virtual resources, preventing overburdening and optimizing resource usage. For instance, a cloud-based application experiences a sudden influx of user requests. The load balancer efficiently distributes these requests across multiple VMs, preventing any single VM from becoming a performance bottleneck.
[00058] The method 200 extends beyond computational resources to include storage. It segments physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand fluctuations. For instance, an online file-sharing service uses the method to allocate storage resources. As users upload more files, the system dynamically increases the allocated storage space to meet demand, ensuring seamless user experiences.
[00059] To anticipate future resource needs, the method 200 employs predictive algorithms. By analyzing historical data, the method forecasts upcoming resource requirements and pre-emptively reallocates virtual resources to prevent contention. For instance, a content streaming platform uses predictive analysis to identify upcoming peak viewing times. The method reallocates resources to the appropriate VMs in advance, ensuring that users experience uninterrupted streaming during high-demand periods.
[00060] In an exemplary embodiment, the method 200 includes provisions for VM or container migration between physical servers. This migration ensures that VMs are positioned optimally to match changing resource demands or maintenance requirements. A social media platform employs VM migration to balance workloads. If one physical server experiences increased CPU utilization, the method migrates VMs to other underutilized servers, maintaining equilibrium and performance.
[00061] Referring to one or more preceding embodiments, the method 200 for efficient resource utilization in data centres using virtualization offers a comprehensive approach to optimizing resource allocation and performance. By combining partitioning, dynamic allocation, monitoring, and adaptive adjustments, the method enhances data centre efficiency, leading to improved performance, minimized resource wastage, and ultimately better user experiences. The examples and scenarios provided in this disclosure demonstrate the practical application of each step, highlighting the system's contribution to efficient data centre operations.
[00062] Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the subject matter described herein, but rather as descriptions of features that may be specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.
[00063] The term “memory,” as used herein relates to a volatile or persistent medium, such as a magnetic disk, or optical disk, in which a computer can store data or software for any duration. Optionally, the memory is non-volatile mass storage such as physical storage media. Furthermore, a single memory may encompass and in a scenario wherein computing system is distributed, the processing, memory and/or storage capability may be distributed as well.
[00064] Throughout the present disclosure, the term ‘server’ relates to a structure and/or module that include programmable and/or non-programmable components configured to store, process and/or share information. Optionally, the server includes any arrangement of physical or virtual computational entities capable of enhancing information to perform various computational tasks.
[00065] Throughout the present disclosure, the term “network” relates to an arrangement of interconnected programmable and/or non-programmable components that are configured to facilitate data communication between one or more electronic devices and/or databases, whether available or known at the time of filing or as later developed. Furthermore, the network may include, but is not limited to, one or more peer-to-peer network, a hybrid peer-to-peer network, local area networks (LANs), radio access networks (RANs), metropolitan area networks (MANS), wide area networks (WANs), all or a portion of a public network such as the global computer network known as the Internet, a private network, a cellular network and any other communication system or systems at one or more locations.
[00066] Throughout the present disclosure, the term “process”* relates to any collection or set of instructions executable by a computer or other digital system so as to configure the computer or the digital system to perform a task that is the intent of the process.
[00067] Throughout the present disclosure, the term ‘Artificial intelligence (AI)’ as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, preset targeting accuracy levels, and/or programmatically intelligent software.

Claims
I/We Claim:
1. A system for efficient resource utilization in data centres using virtualization, comprising:
a physical infrastructure module including servers, storage, and network devices;
a virtualization layer overlaying the physical infrastructure module, partitioning physical resources into virtual units;
a resource allocation engine determining resource distribution based on demand and operational metrics; and
a monitoring module tracking real-time resource utilization and performance metrics.
2. The system of claim 1, wherein the virtualization layer includes:
a hypervisor managing the creation, execution, and termination of virtual machines on the physical servers.
3. The system of claim 1, further comprising:
a load balancer distributing incoming network traffic across multiple virtual machines to optimize resource usage.
4. The system of claim 1, wherein the resource allocation engine employs:
predictive algorithms anticipating future resource requirements and pre-emptively reallocating virtual resources accordingly.
5. The system of claim 1, further comprising:
a storage virtualization unit segmenting physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand.
6. A method for efficient resource utilization in data centres using virtualization, comprising:
partitioning physical resources in a data centre into virtual units;
dynamically allocating virtual resources based on current and predicted demand;
monitoring real-time utilization of both physical and virtual resources; and
adjusting allocations in response to the monitored utilization.
7. The method of claim 6, further comprising:
distributing incoming network traffic across multiple virtual resources using a load balancing mechanism, ensuring optimal resource usage.
8. The method of claim 6, including:
segmenting physical storage resources into virtual storage pools; and
resizing and provisioning virtual storage resources based on current storage demand.
9. The method of claim 6, wherein dynamically allocating resources involves:
forecasting future resource requirements using historical data; and
pre-emptively reallocating virtual resources based on the forecast to prevent resource contention.
10. The method of claim 6, further comprising:
initiating migration of virtual machines or containers between physical servers in response to changing resource demands or maintenance requirements, ensuring uninterrupted operation and optimal resource distribution.

Virtualization in Data Centers for Efficient Resource Utilization
Abstract
The present invention presents a system for optimizing resource utilization within data centers through virtualization, encompassing a physical infrastructure module housing servers, storage, and network devices, a virtualization layer superimposing the physical infrastructure to create virtual units from physical resources, a resource allocation engine configuring resource distribution based on real-time demand and operational metrics, and a monitoring module overseeing instantaneous resource usage and performance metrics. This system offers an integrated solution for enhanced efficiency by dynamically partitioning and allocating resources to match demand, optimizing data center operations through virtualization and adaptive resource management.
, Claims:Claims
I/We Claim:
1. A system for efficient resource utilization in data centres using virtualization, comprising:
a physical infrastructure module including servers, storage, and network devices;
a virtualization layer overlaying the physical infrastructure module, partitioning physical resources into virtual units;
a resource allocation engine determining resource distribution based on demand and operational metrics; and
a monitoring module tracking real-time resource utilization and performance metrics.
2. The system of claim 1, wherein the virtualization layer includes:
a hypervisor managing the creation, execution, and termination of virtual machines on the physical servers.
3. The system of claim 1, further comprising:
a load balancer distributing incoming network traffic across multiple virtual machines to optimize resource usage.
4. The system of claim 1, wherein the resource allocation engine employs:
predictive algorithms anticipating future resource requirements and pre-emptively reallocating virtual resources accordingly.
5. The system of claim 1, further comprising:
a storage virtualization unit segmenting physical storage devices into virtual storage pools, allowing dynamic resizing and provisioning based on demand.
6. A method for efficient resource utilization in data centres using virtualization, comprising:
partitioning physical resources in a data centre into virtual units;
dynamically allocating virtual resources based on current and predicted demand;
monitoring real-time utilization of both physical and virtual resources; and
adjusting allocations in response to the monitored utilization.
7. The method of claim 6, further comprising:
distributing incoming network traffic across multiple virtual resources using a load balancing mechanism, ensuring optimal resource usage.
8. The method of claim 6, including:
segmenting physical storage resources into virtual storage pools; and
resizing and provisioning virtual storage resources based on current storage demand.
9. The method of claim 6, wherein dynamically allocating resources involves:
forecasting future resource requirements using historical data; and
pre-emptively reallocating virtual resources based on the forecast to prevent resource contention.
10. The method of claim 6, further comprising:
initiating migration of virtual machines or containers between physical servers in response to changing resource demands or maintenance requirements, ensuring uninterrupted operation and optimal resource distribution.