Abstract: A system, method, and machine-readable storage medium for resolving a candidate community are provided. In some embodiments, a method includes obtaining a candidate community and a neighbor set for the candidate community, the neighbor set including zero or more stable communities. The method also includes resolving the candidate community as being a new stable community if the neighbor set is empty. The method further includes resolving the candidate community as being part of a matching stable community if a hash value of the candidate community matches a hash value of one or more stable communities included in the neighbor set. The method also includes resolving the candidate community as being a new stable community if an entropy value is greater than a threshold, the entropy value being based on the candidate community and the neighbor set.

Abstract: A system, method, and machine-readable storage medium for detecting an anomaly are provided. In some embodiments, the method includes computing an access rate of a set of entities for each user of a plurality of users. The access rate may refer to data operations for the set of entities stored by a storage system. The method also includes normalizing the access rates for a subset of the plurality of users, the subset belonging to a community. The method further includes determining whether a normalized access rate from among the access rates satisfies a threshold. The method also includes detecting an anomaly in response to a determination that the normalized access rate satisfies the threshold.

Abstract: A system, method, and machine-readable storage medium for forming a community based on a common set of attributes are provided. In some embodiments, the method includes creating a list of entities associated with a plurality of users, each entity included in the list of entities being accessed by a user of the plurality of users. The method also includes identifying a first entity accessed by a group of users of the plurality of users. The method further includes determining a first set of entities accessed by each user of the group of users, the first set of entities being included in the list of entities. The method also includes removing the first entity and the first set of entities from the list of entities. The method further includes forming a first community including the group of users, the first entity, and the first set of entities.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced here. Techniques are provided for determining a probability of deduplication for a data object based on a characteristic of the data object and performing a deduplication operation on the data object in the storage system prior to the data object being stored in persistent storage of the storage system if the probability of deduplication for the data object has a specified relationship to a specified threshold.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced herein. Techniques are provided for determining a first deduplication priority for a first data object based upon a first projected likelihood that deduplication of the first data object will provide a storage space benefit to reduce storage consumption of a storage device. Inline deduplication is performed for the first data object based upon the first deduplication priority exceeding a deduplication probability threshold that is indicative of inline deduplication of the first data object having a threshold likelihood of achieving the storage space benefit from inline deduplication.

Abstract: An embodiment of the invention provides an apparatus and method for classifying a workload of a computing entity. In an embodiment, the computing entity samples a plurality of values for a plurality of parameters of the workload. Based on the plurality of values of each parameter, the computing entity determines a parameter from the plurality of parameters that the computing entity's response time is dependent on. Here, the computing entity's response time is indicative of a time required by the computing entity to respond to a service request from the workload. Further, based on the identified significant parameter, the computing entity classifies the workload of the computing entity by selecting a workload classification from a plurality of predefined workload classifications.

Abstract: Methods and systems for a networked storage system is provided. One method includes transforming by a processor, performance parameters associated with storage volumes of a storage system for representing each storage volume as a data point in a parametric space; generating by the processor, a plurality of bins in the parametric space using the transformed performance parameters; adjusting by the processor, bin boundaries for the plurality of bins for defining a plurality of service levels for the storage system based on the performance parameters; and using the defined plurality of service levels for operating the storage system.

Abstract: Methods and systems for document classification are provided. One method includes generating by a processor, a plurality of topics using content of a plurality of electronic documents, where each topic includes a plurality of words associated with the plurality of electronic documents; reducing by the processor, the plurality of topics to a subset of topics to represent the plurality of electronic documents based on a parameter indicating a property of each subset topic and separation between the subset topics; automatically generating by the processor, a tag for each subset topic, based on the tag's position within the subset topic; wherein each tag is an attribute of each subset topic; storing by the processor, the subset of topics with corresponding tags in a model data structure; and updating the model data structure by the processor based on one of a new topic and a new tag associated with an electronic document.

Abstract: The use of a just-in-time market for EV's (electric vehicles) to buy and sell energy from each other directly. Such a market enables the following: sellers to advertise the amount of energy they are willing to sell and the minimum selling price; buyers to advertise the amount of energy they are interested in buying and the maximum buying price. The market works at any location and at any time as long as there is a buyer and seller. The communications are directly between buyers and sellers without the involvement of any third parties.

Abstract: An embodiment of the invention provides an apparatus and method for classifying a workload of a computing entity. In an embodiment, the computing entity samples a plurality of values for a plurality of parameters of the workload. Based on the plurality of values of each parameter, the computing entity determines a parameter from the plurality of parameters that the computing entity's response time is dependent on. Here, the computing entity's response time is indicative of a time required by the computing entity to respond to a service request from the workload. Further, based on the identified significant parameter, the computing entity classifies the workload of the computing entity by selecting a workload classification from a plurality of predefined workload classifications.

Abstract: A method, non-transitory computer readable medium, and provisioning advisor device that obtains an intensity and characteristics for each of a plurality of training workloads from storage device volumes. For each of the training workloads, at least first and second training workload parameters are generated, based on the training workload intensity, and an associated training workload signature is generated, based on the training workload characteristics. The first and second training workload parameters and associated training workload signatures are stored in a mapping table. A signature and an intensity for a query workload are obtained. First and second query workload parameters are determined based on a correlation of the query workload signature with the training workload signatures of the mapping table. An estimated latency for the query workload is determined, based on the first and second query workload parameters and the query workload intensity, and the estimated query workload latency is output.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced here. Techniques are provided for determining a probability of deduplication for a data object based on a characteristic of the data object and performing a deduplication operation on the data object in the storage system prior to the data object being stored in persistent storage of the storage system if the probability of deduplication for the data object has a specified relationship to a specified threshold.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced herein. Techniques are provided for determining deduplication priorities of data objects based upon projected likelihoods that deduplication of such data objects will provide a storage space benefit. Inline deduplication and/or post processing deduplication is selectively provided on an individual data object basis based upon deduplication priorities assigned to respective data objects.

Abstract: A method and system for a provisioning advisor are described which estimates the input/output operation performance of a workload on a storage system. A regression module in a provisioning advisor estimates a maximum IOPS on the storage system for buckets, or combinations of values, for various characteristics of the workloads running on the system by modeling a relationship between the workload characteristics and performance metrics gathered from the storage system. A performance module can use the estimated maximum IOPS for each bucket to update a set of working tables for the provisioning advisor, which can then be used to predict the input/output performance of a new workload to be provisioned on the storage system.

Abstract: Systems and methods disclosed herein provide intelligent filtering of system log messages having low utility value. In providing the filtering, the systems and methods determine the utility value of a system log message and delete the message from the system log if the message is determined to be of low utility value. As such, embodiments herein provide an system log filter, which reduces the amount of data stored in the system log based on the utility value of the message.

Abstract: A system and method for creating an accurate black-box model of a live storage system and for predicting performance of the storage system under a given workload is disclosed. An analytics engine determines a subset of counters that are relevant to performance of the storage system with respect to a particular output (e.g., throughput or latency) from performance data in counters of the storage system. Using the subset of counters, the analytics engine creates a workload signature for the storage system by using a recursive partitioning technique, such as a classification and regression tree. The analytics engine then creates the black-box model of the storage system performance by applying uncertainty measurement techniques, such as a Gaussian process, to the workload signature.

Abstract: A method and system for a provisioning advisor are described which estimates the input/output operation performance of a workload on a storage system. A regression module in a provisioning advisor estimates a maximum IOPS on the storage system for buckets, or combinations of values, for various characteristics of the workloads running on the system by modeling a relationship between the workload characteristics and performance metrics gathered from the storage system. A performance module can use the estimated maximum IOPS for each bucket to update a set of working tables for the provisioning advisor, which can then be used to predict the input/output performance of a new workload to be provisioned on the storage system.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced here. Techniques are provided for determining a probability of deduplication for a data object based on a characteristic of the data object and performing a deduplication operation on the data object in the storage system prior to the data object being stored in persistent storage of the storage system if the probability of deduplication for the data object has a specified relationship to a specified threshold.

Abstract: Methods and apparatuses for performing selective deduplication in a storage system are introduced here. Techniques are provided for determining a probability of deduplication for a data object based on a characteristic of the data object and performing a deduplication operation on the data object in the storage system prior to the data object being stored in persistent storage of the storage system if the probability of deduplication for the data object has a specified relationship to a specified threshold.

Abstract: Technology is disclosed for graphically representing classification of workloads in a storage system. Workload classification is graphically represented to the user by mapping workload signatures of the workloads to a grid. When the workload signatures are mapped to the grid, a number of clusters are formed in the grid. Each of the clusters represents workloads of a particular category. Mapping the workload signature to the grid includes mapping a high-dimensionality workload signature vector to a low-dimensionality grid.