Server Consolidation Technique Research Articles

Comprehensive survey on energy-aware server consolidation techniques in cloud computing

The objective of cloud computing is to provide seamless services using virtualization technology over the Internet to serve the Quality of Service (QoS)-driven end users requirements. In order to provide various services like Software as a Service, Platform as a Service, Infrastructure as a Service, the cloud server’s datacenters are kept active, which have large electrical consumption. Due to improper utilization of resources, optimizing the servers energy consumption becomes a significant challenge for service vendors from environmental and economic perspectives as well. The challenge to provide services with a low energy consumption profile opens up a new dimension of optimized server use for intelligent management of resources (such as CPU/disk/memory), with reduced power consumption through server consolidation. This enables fewer active physical servers to provide the required services without compromising the QoS. This article presents a narrative recent advancement comprehensive as well as systematic survey of existing energy-efficient techniques along with their limitations and the challenges associated in implementing them.

Server consolidation: A technique to enhance cloud data center power efficiency and overall cost of ownership

Cloud computing is a well-known technology that provides flexible, efficient, and cost-effective information technology solutions for multinationals to offer improved and enhanced quality of business services to end-users. The cloud computing paradigm is instigated from grid and parallel computing models as it uses virtualization, server consolidation, utility computing, and other computing technologies and models for providing better information technology solutions for large-scale computational data centers. The recent intensifying computational demands from multinationals enterprises have motivated the magnification for large complicated cloud data centers to handle business, monetary, Internet, and commercial applications of different enterprises. A cloud data center encompasses thousands of millions of physical server machines arranged in racks along with network, storage, and other equipment that entails an extensive amount of power to process different processes and amenities required by business firms to run their business applications. This data center infrastructure leads to different challenges like enormous power consumption, underutilization of installed equipment especially physical server machines, CO2 emission causing global warming, and so on. In this article, we highlight the data center issues in the context of Pakistan where the data center industry is facing huge power deficits and shortcomings to fulfill the power demands to provide data and operational services to business enterprises. The research investigates these challenges and provides solutions to reduce the number of installed physical server machines and their related device equipment. In this article, we proposed server consolidation technique to increase the utilization of already existing server machines and their workloads by migrating them to virtual server machines to implement green energy-efficient cloud data centers. To achieve this objective, we also introduced a novel Virtualized Task Scheduling Algorithm to manage and properly distribute the physical server machine workloads onto virtual server machines. The results are generated from a case study performed in Pakistan where the proposed server consolidation technique and virtualized task scheduling algorithm are applied on a tier-level data center. The results obtained from the case study demonstrate that there are annual power savings of 23,600 W and overall cost savings of US$78,362. The results also highlight that the utilization ratio of already existing physical server machines has increased to 30% compared to 10%, whereas the number of server machines has reduced to 50% contributing enormously toward huge power savings.

Nash equilibrium based replacement of virtual machines for efficient utilization of cloud data centers

Workload uncertainty has been increased with the integration of the Internet of Things to the computing grid i.e. edge computing and cloud data centers. Therefore, efficient resource utilization in cloud data centers become more challenging. Dynamic consolidation of virtual machines on optimal number of processing machines can increase the efficiency of resource utilization in cloud data centers. This process requires the migration of virtual machines from the under-utilized and over-utilized processing machines to other suitable machines. In this work, the problem of efficient replacement of virtual machines is solved using a game theory based well known technique, Nash Equilibrium (NE). We designed a nash equilibrium based dual on two players, over-load manager and under-load manager, to deduce the dominant strategy profiles for various scenarios during consolidation cycles. Dominant strategy profile is the set of strategies where every player has no incentive in deviation, thus leading to equilibrium position. A virtual machines redeployment algorithm, Nash Equilibrium based Virtual Machines Replacement (NE-VMR), has been proposed on the basis of the dominant strategy profiles for efficient consolidation. Experiment results show that NE-VMR is a more efficient server consolidation technique, saved 30% energy and improved 35% quality of service as compared to baselines.

Utilization Driven Model for Server Consolidation in Cloud Data Centers

The application of cloud computing has diversified with the adoption of Internet of Things (IoTs) and edge computing. However, it has increased the uncertainty of workload demand; thus, the efficient utilization of cloud computing resources become more challenging. Traditionally, dynamic consolidation of workload inside cloud data centers relies on identifying overload and under-load hosts using either static or dynamic threshold value. In this paper, we propose a Utilization Driven Model (UDM) model to estimate the number of under-utilized and over-utilized processing machines through percentile ranks of low and high utilization from mean value of resource utilization of hosts and the value of mean absolute deviation of resource demand. UDM swiftly reacts to any change in workload demand and adapts the system to the current demand of resource utilization. The UDM approach not only impacts the energy consumption and quality of service but also increases the elastic nature of cloud by robustly managing the sudden changes in workload. Experiment results show that UDM is an efficient server consolidation technique, improving 30% energy, 40% quality of service compared to contemporary techniques. Thus, the UDM is more robust to support stochastic resource demand compared to traditional techniques.

Challenges of server consolidation in virtualized data centers and open research issues: a systematic literature review

With the increasing demands for cloud computing services, the development of technologies based on virtualization in data centers was noticed. In the virtualized data center, the efficient mapping of virtual machines to physical machines is done using the consolidation technique. Due to the advantages of the server consolidation technique, a large body of research has been done in this field. A comprehensive study on the different server consolidation solutions has not been done yet, though. In this study, a systematic review has been done on a set of researches related to server consolidation. After investigating the considered researches, their proposed solutions were categorized into three groups based on the type of decision making for running the consolidation process. Groups involve static method, dynamic method (including threshold-based and periodic-based adaptation) and prediction-based dynamic method. Thereafter, we discussed handling the challenges presented in each research by investigating the proposed approach for developing consolidation technique. Then, the open issues in each study were expressed. Finally, the objectives, evaluation parameters, optimization methods and the affecting parameters of server consolidation in all studies were investigated and analyzed.

Server Consolidation Schemes in Cloud Computing Environment: A Review

Cloud computing is a new paradigm which deliver computing resources as utility. Datacenters as cloud infrastructure encounter with several issues such as power management for the sake of economic viewpoint. Researches show that high rate of power wastage in large scale datacenters is related to sprawl resource usage making low utilization. More recently, server consolidation techniques have been developed to maximize resource utilization in at least used number of physical servers. This technique is applied in virtualization environment which allows physical servers to host several operating systems and related applications. Server consolidation approach abstracts system under study into NP-hard bin-packing problem. Several works have been done in literature to solve server consolidation problem. This paper analyses the papers and compare them with parameters derived from research context. Commonalities and differences are argued. Then, open issues and challenges are concluded to work in future.

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

SummaryAt the virtualized data centers, services are presented by active virtual machines (VMs) in physical machines (PMs). The manner in which VMs are mapped to PMs affects the performance of data centers and the energy efficiency. By employing the server consolidation technique, it is possible to configure the VMs on a smaller number of PMs, while the quality of service is guaranteed. In this way, the rate of active PM utilization increases and fewer active PMs would be required. Moreover, the server consolidation technique reacts to the management of underloaded and overloaded PMs by using the VM migration technology. Considering the capabilities of the server consolidation technique and its role in developing the cloud computing infrastructure, many researches have been conducted in this context. Still, a comprehensive and systematic study has not yet been performed on various consolidation techniques to check the capabilities, advantages, and disadvantages of current approaches. In this paper, a systematic study is conducted on a number of credible researches related to server consolidation techniques. In order to do so and by studying the selected works, proposed solutions are categorized based on the type of decision for running the consolidation algorithm in 4 groups of static method, dynamic method, prediction‐based dynamic method, and hybrid method. Thereafter, the advantages and disadvantages of suggested approaches are studied and compared in each research by specifying the technique and idea applied therein. In addition, by categorizing aims of researches and specifying assessment parameters, optimization approaches and type of architecture, a possibility has been provided to get familiarized with the views of the researchers.

Server Consolidation Techniques in Virtualized Data Centers: A Survey

Data centers and their applications are exponentially growing. Consequently, their energy consumption and environmental impacts have also become increasingly more important. Virtualization technologies are widely used in modern data centers to ease the management of the data center and to reduce its energy consumption. Data centers that employ virtualization technologies are typically called virtualized or cloud data centers . Virtualization technologies enable virtual machine (VM) live migration, which allows the VMs to be freely moved among physical machines (PMs) with negligible downtime. Thus, several VMs can be packed on a single PM so as to let the PM run in its more energy-efficient working condition. This technique is called server consolidation and is an effective and widely used approach to reduce total energy consumption in data centers. Server consolidation can be done in various ways and by considering various parameters and effects. This paper presents a survey and taxonomy for server consolidation techniques in cloud data centers. Special attention has been devoted to the parameters and algorithmic approaches used to consolidate VMs onto PMs. In this end, we also discuss open challenges and suggest areas for further research.

Server Consolidation Schemes in Cloud Computing Environment: A Review

Cloud computing is a new paradigm which deliver computing resources as utility. Datacenters as cloud infrastructure encounter with several issues such as power management for the sake of economic viewpoint. Researches show that high rate of power wastage in large scale datacenters is related to sprawl resource usage making low utilization. More recently, server consolidation techniques have been developed to maximize resource utilization in at least used number of physical servers. This technique is applied in virtualization environment which allows physical servers to host several operating systems and related applications. Server consolidation approach abstracts system under study into NP-hard bin-packing problem. Several works have been done in literature to solve server consolidation problem. This paper analyses the papers and compare them with parameters derived from research context. Commonalities and differences are argued. Then, open issues and challenges are concluded to work in future.

Sercon: Server Consolidation Algorithm using Live Migration of Virtual Machines for Green Computing

Virtualization technologies changed the way data centers of enterprises utilize their server resources. Instead of using dedicated servers for each type of application, virtualization allows viewing resources as a pool of unified resources, thereby reducing complexity and easing manageability. Server consolidation technique, which deals with reducing the number of servers used by consolidating applications, is one of the main applications of virtualization in data centers. The latter technique helps to use computing resources more effectively and has many benefits, such as reducing costs of power, cooling and, hence, contributes to the Green IT initiative. In a dynamic data center environment, where applications encapsulated as virtual machines are mapped to and released from the nodes frequently, reducing the number of server nodes used can be achieved by migrating applications without stopping their services, the technology known as live migration. However, live migration is a costly operation; hence, how to perform periodic server consolidation operation in a migration-aware way is a challenging task. We propose server consolidation algorithm - Sercon, which not only minimizes the overall number of used servers, but also minimizes the number of migrations. We verify the feasibility of our algorithm along with showing its scalability by conducting experiments with eight different test cases.