Emc IP Holding Company LLC

Simon Tao

Yu Cao

Kenneth Durazzo

Xiaoyan Guo

Sanping Li

Zhe Dong

Stephen J Todd

John T Cardente

Accela Yilong Zhao

A first set of values for a set of metrics is obtained. A given metric of the set of metrics monitors a given component of a set of components of a computing system. The first set of values is obtained during a period of expected behavior of the computing system. One or more correlations are determined between values of the first set of values to establish one or more expected correlations between values of two or more metrics. A second set of values for the set of metrics is obtained. A determination is made as to whether values of the second set of values maintain the one or more expected correlations determined based on the first set of values.

System monitoring with metrics correlation for data center

A method for processing data includes receiving an adjustment request for adjusting a number of consumer instances from a first number to a second number, and determining a migration overhead for adjusting a first distribution of states associated with the first number of consumer instances to a second distribution of the states associated with the second number of consumer instances, wherein the states are intermediate results of processing the data and the migration overhead includes a latency and a bandwidth shortage incurred for migrating the states. Based on the determined migration overhead, the states are migrated between the first number of consumer instances and the second number of consumer instances, and thereafter the data is processed based on the second distribution of the states at the second number of consumer instances.

Method and system for processing data

A scheduler module receives a first allocation request for a given amount of a resource in a cloud computing platform that an application program currently needs. The scheduler module allocates the given amount of the resource to the application program for a first time slot. The given amount of allocated resource is received back at the scheduler module upon expiration of the first time slot for subsequent allocation. The scheduler module receives a second allocation request for a given amount of a resource that an application program currently needs. The scheduler module allocates the given amount of the resource to the application program for a second time slot. The given amount of allocated resource is received back at the scheduler module upon expiration of the second time slot for subsequent allocation.

Spatial-temporal cloud resource scheduling

Embodiments of the present invention relates to a method and system for processing data. Specifically, there is provided a method for processing data, comprising: in response to receiving an adjustment request for adjusting the number of consumer instances from a first number to a second number, determining an adjustment policy on adjusting a first distribution of states associated with the first number of consumer instances to a second distribution of the states associated with the second number of consumer instances, the states being intermediate results of processing the data; migrating the states between the first number of the consumer instances and the second number of the consumer instances according to the adjustment policy; and processing the data based on the second distribution of the states at the second number of the consumer instances. In other embodiments, there are further provided a device and system for processing data.

A computing system is monitored by collecting monitoring information from two or more different monitoring tools associated with respective portions of the computing system, where the monitoring tools having different information collection capabilities associated therewith. The monitoring information received from the different monitoring tools is consolidated in a unified data store. The unified data store is utilized to perform analytics relating to inter-dependencies of storage, compute and networking components of the computing system managed by different ones of the monitoring tools. The analytics results are presented utilizing a monitoring dashboard.

Monitoring and analytics system

A specification of visualization requirements for a customized visualization associated with one or more storage, compute and networking resources of a data center is generated. Resource data is obtained from one or more data sources, the resource data being associated with one or more of the storage, compute and networking resources of the data center. One or more data views are created utilizing the resource data, each data view comprising a dynamic mapping of the resource data based on the visualization requirements. One or more visuals are rendered utilizing the one or more data views. The customized visualization is generated by organizing the visuals into one or more dashboards of a graphical user interface.

Customized visualizations for data centers

Processing nodes in a distributed ad-hoc computing environment are discovered, wherein each processing node is configured to discover other processing nodes. A set of candidate processing nodes is selected from the discovered processing nodes. Selection is based on each discovered processing node advertising its own capabilities to other processing nodes, and processing nodes are selected as candidates based on their advertised capabilities. A subset of processing nodes is formed from the set of candidate processing nodes. The subset of processing nodes forms a self-organized task coordination ensemble wherein each processing node in the task coordination ensemble executes the same consensus protocol. By way of example, the distributed ad-hoc computing environment comprises an IoT network and the processing nodes are IoT devices.

Self-organizing distributed task coordination for ad-hoc computing environment

A data movement method includes enabling a given data center operatively coupled to one or more other data centers via a communication network to move data between itself and the one or more other data centers in accordance with a peer-to-peer protocol. The given data center and the one or more other data centers thereby form a peer-to-peer network. At least a portion of the given data center and the one or more other data centers are implemented on a cloud computing platform.

Global data movement in cloud computing environment

A computing platform comprises one or more virtual compute elements, virtual storage elements, and virtual networking elements, wherein one or more application programs of one or more tenants execute on the computing platform. An application program monitoring service layer comprises a set of monitoring service modules selectable by the one or more tenants. The monitoring service modules are configured to provide different application-level monitoring functions, for a given tenant, to monitor the execution of at least one installed application program of the given tenant. A selected monitoring service module executes in at least one virtual compute element that is part of a set of one or more virtual compute elements currently executing the at least one installed application program of the given tenant being monitored. The application program monitoring service layer further comprises a data collecting service module configured to receive application data from the monitoring service module.

Application-level monitoring and profiling services in computing environments

One or more resource identifiers are obtained, wherein the one or more resource identifiers are extracted from a content page obtained over a computer network. One or more irrelevant resource identifiers are filtered out from the one or more extracted resource identifiers. One or more resource identifiers remaining after the filtering step are classified into one or more classifications from a given set of classifications, wherein each of the given set of classifications has a dedicated network search component associated therewith. In response to the classifying step, the one or more classified resource identifiers are inserted into a seed set of resource identifiers associated with a dedicated network search component corresponding to the classification of the one or more classified resource identifiers.

High-performance network data capture and storage

A specification of resource requirements is received. One or more resource configurations for a computing environment that satisfy the specification of resource requirements are generated utilizing a description of available resources in the computing environment. A model is utilized to estimate a level of service for each of the resource configurations, wherein the model predicts behavioral dependencies between attributes of the resources in the computing environment. A given one of the resource configurations is selected based at least in part on the estimated levels of service, and resources in the computing environment are assigned according to the selected configuration of resources.

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Shanghai, China

Simon Tao