The Experts below are selected from a list of 116820 Experts worldwide ranked by ideXlab platform

Andrzej Kochut - One of the best experts on this subject based on the ideXlab platform.

  • application performance management in Virtualized Server Environments
    2006 IEEE IFIP Network Operations and Management Symposium NOMS 2006, 2006
    Co-Authors: G. Khanna, G. Kar, Kirk Beaty, Andrzej Kochut
    Abstract:

    As businesses have grown, so has the need to deploy I/T applications rapidly to support the expanding business processes. Often, this growth was achieved in an unplanned way: each time a new application was needed a new server along with the application software was deployed and new storage elements were purchased. In many cases this has led to what is often referred to as "server sprawl", resulting in low server utilization and high system management costs. An architectural approach that is becoming increasingly popular to address this problem is known as server virtualization. In this paper we introduce the concept of server consolidation using virtualization and point out associated issues that arise in the area of application performance. We show how some of these problems can be solved by monitoring key performance metrics and using the data to trigger migration of virtual machines within physical servers. The algorithms we present attempt to minimize the cost of migration and maintain acceptable application performance levels

  • NOMS - application performance management in Virtualized Server Environments
    2006 IEEE IFIP Network Operations and Management Symposium NOMS 2006, 2006
    Co-Authors: G. Khanna, G. Kar, Kirk Beaty, Andrzej Kochut
    Abstract:

    As businesses have grown, so has the need to deploy I/T applications rapidly to support the expanding business processes. Often, this growth was achieved in an unplanned way: each time a new application was needed a new server along with the application software was deployed and new storage elements were purchased. In many cases this has led to what is often referred to as "server sprawl", resulting in low server utilization and high system management costs. An architectural approach that is becoming increasingly popular to address this problem is known as server virtualization. In this paper we introduce the concept of server consolidation using virtualization and point out associated issues that arise in the area of application performance. We show how some of these problems can be solved by monitoring key performance metrics and using the data to trigger migration of Virtual Machines within physical servers. The algorithms we present attempt to minimize the cost of migration and maintain acceptable application performance levels.

G. Khanna - One of the best experts on this subject based on the ideXlab platform.

  • application performance management in Virtualized Server Environments
    2006 IEEE IFIP Network Operations and Management Symposium NOMS 2006, 2006
    Co-Authors: G. Khanna, G. Kar, Kirk Beaty, Andrzej Kochut
    Abstract:

    As businesses have grown, so has the need to deploy I/T applications rapidly to support the expanding business processes. Often, this growth was achieved in an unplanned way: each time a new application was needed a new server along with the application software was deployed and new storage elements were purchased. In many cases this has led to what is often referred to as "server sprawl", resulting in low server utilization and high system management costs. An architectural approach that is becoming increasingly popular to address this problem is known as server virtualization. In this paper we introduce the concept of server consolidation using virtualization and point out associated issues that arise in the area of application performance. We show how some of these problems can be solved by monitoring key performance metrics and using the data to trigger migration of virtual machines within physical servers. The algorithms we present attempt to minimize the cost of migration and maintain acceptable application performance levels

  • NOMS - application performance management in Virtualized Server Environments
    2006 IEEE IFIP Network Operations and Management Symposium NOMS 2006, 2006
    Co-Authors: G. Khanna, G. Kar, Kirk Beaty, Andrzej Kochut
    Abstract:

    As businesses have grown, so has the need to deploy I/T applications rapidly to support the expanding business processes. Often, this growth was achieved in an unplanned way: each time a new application was needed a new server along with the application software was deployed and new storage elements were purchased. In many cases this has led to what is often referred to as "server sprawl", resulting in low server utilization and high system management costs. An architectural approach that is becoming increasingly popular to address this problem is known as server virtualization. In this paper we introduce the concept of server consolidation using virtualization and point out associated issues that arise in the area of application performance. We show how some of these problems can be solved by monitoring key performance metrics and using the data to trigger migration of Virtual Machines within physical servers. The algorithms we present attempt to minimize the cost of migration and maintain acceptable application performance levels.

Alexandru Iosup - One of the best experts on this subject based on the ideXlab platform.

  • statistical characterization of business critical workloads hosted in cloud datacenters
    IEEE ACM International Symposium Cluster Cloud and Grid Computing, 2015
    Co-Authors: Siqi Shen, Vincent Van Beek, Alexandru Iosup
    Abstract:

    Business-critical workloads -- web servers, mail servers, app servers, etc. -- are increasingly hosted in virtualized data enters acting as Infrastructure-as-a-Service clouds (cloud data enters). Understanding how business-critical workloads demand and use resources is key in capacity sizing, in infrastructure operation and testing, and in application performance management. However, relatively little is currently known about these workloads, because the information is complex -- larges-scale, heterogeneous, shared-clusters -- and because datacenter operators remain reluctant to share such information. Moreover, the few operators that have shared data (e.g., Google and several supercomputing centers) have enabled studies in business intelligence (MapReduce), search, and scientific computing (HPC), but not in business-critical workloads. To alleviate this situation, in this work we conduct a comprehensive study of business-critical workloads hosted in cloud data enters. We collect two large-scale and long-term workload traces corresponding to requested and actually used resources in a distributed datacenter servicing business-critical workloads. We perform an in-depth analysis about workload traces. Our study sheds light into the workload of cloud data enters hosting business-critical workloads. The results of this work can be used as a basis to develop efficient resource management mechanisms for data enters. Moreover, the traces we released in this work can be used for workload verification, modelling and for evaluating resource scheduling policies, etc.

  • CCGRID - Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters
    2015 15th IEEE ACM International Symposium on Cluster Cloud and Grid Computing, 2015
    Co-Authors: Siqi Shen, Vincent Van Beek, Alexandru Iosup
    Abstract:

    Business-critical workloads -- web servers, mail servers, app servers, etc. -- are increasingly hosted in virtualized data enters acting as Infrastructure-as-a-Service clouds (cloud data enters). Understanding how business-critical workloads demand and use resources is key in capacity sizing, in infrastructure operation and testing, and in application performance management. However, relatively little is currently known about these workloads, because the information is complex -- larges-scale, heterogeneous, shared-clusters -- and because datacenter operators remain reluctant to share such information. Moreover, the few operators that have shared data (e.g., Google and several supercomputing centers) have enabled studies in business intelligence (MapReduce), search, and scientific computing (HPC), but not in business-critical workloads. To alleviate this situation, in this work we conduct a comprehensive study of business-critical workloads hosted in cloud data enters. We collect two large-scale and long-term workload traces corresponding to requested and actually used resources in a distributed datacenter servicing business-critical workloads. We perform an in-depth analysis about workload traces. Our study sheds light into the workload of cloud data enters hosting business-critical workloads. The results of this work can be used as a basis to develop efficient resource management mechanisms for data enters. Moreover, the traces we released in this work can be used for workload verification, modelling and for evaluating resource scheduling policies, etc.

Qiben Yan - One of the best experts on this subject based on the ideXlab platform.

  • Demystifying application performance management Libraries for Android
    2019 34th IEEE ACM International Conference on Automated Software Engineering (ASE), 2019
    Co-Authors: Yutian Tang, Xian Zhan, Xiapu Luo, Yajin Zhou, Zhou Xu, Hao Zhou, Qiben Yan
    Abstract:

    Since the performance issues of apps can influence users' experience, developers leverage application performance management (APM) tools to locate the potential performance bottleneck of their apps. Unfortunately, most developers do not understand how APMs monitor their apps during the runtime and whether these APMs have any limitations. In this paper, we demystify APMs by inspecting 25 widely-used APMs that target on Android apps. We first report how these APMs implement 8 key functions as well as their limitations. Then, we conduct a large-scale empirical study on 500,000 Android apps from Google Play to explore the usage of APMs. This study has some interesting observations about existing APMs for Android, including 1) some APMs still use deprecated permissions and approaches so that they may not always work properly; 2) some app developers use APMs to collect users' privacy information.

  • ASE - Demystifying application performance management Libraries for Android
    2019 34th IEEE ACM International Conference on Automated Software Engineering (ASE), 2019
    Co-Authors: Yutian Tang, Xian Zhan, Xiapu Luo, Yajin Zhou, Hao Zhou, Qiben Yan
    Abstract:

    Since the performance issues of apps can influence users' experience, developers leverage application performance management (APM) tools to locate the potential performance bottleneck of their apps. Unfortunately, most developers do not understand how APMs monitor their apps during the runtime and whether these APMs have any limitations. In this paper, we demystify APMs by inspecting 25 widely-used APMs that target on Android apps. We first report how these APMs implement 8 key functions as well as their limitations. Then, we conduct a large-scale empirical study on 500,000 Android apps from Google Play to explore the usage of APMs. This study has some interesting observations about existing APMs for Android, including 1) some APMs still use deprecated permissions and approaches so that they may not always work properly; 2) some app developers use APMs to collect users' privacy information.

Kang Jianchu - One of the best experts on this subject based on the ideXlab platform.

  • Standards and Technologies on application performance management
    Computer Engineering, 2004
    Co-Authors: Kang Jianchu
    Abstract:

    This paper summarizes the research in the application performance management field. After summing up the history and actuality of the application performance management, this paper systematically presents the standards about the application performance management, such as common information model and Java management extension and analyzes the respective advantages and limitations of familiar technologies by overall comparison.