Abstract: Examples may include container index persistent item tags. Examples may store chunk signatures in at least one container index and, for each chunk signature, store at least one persistent item tag identifying a respective backup item that references or formerly referenced the chunk signature. Examples may determine that all chunks formerly referenced by a backup item have been erased based on the persistent item tags in the at least one container index and output an indication that the backup item has been erased.

Abstract: Examples described herein relate to deletion of data entities in a deduplication system. Examples may maintain entries in a housekeeping queue, each entry including a priority value and a total unshared chunk size of a data entity to be deleted from the deduplication system. Examples may delete the data entities corresponding to the entries including a low priority value from the deduplication system. Examples may determine whether an available storage capacity of the deduplication system is sufficient after deleting the data entities corresponding to the entries including the low priority value. Examples may delete a data entity corresponding to an entry including a high priority value and a largest total unshared chunk size if the available storage capacity is insufficient.

Abstract: Examples may include a deduplication system threshold based on an amount of wear of a storage device. Examples may obtain an indication of an amount of wear experienced by at least one storage device storing a plurality of container indexes of a deduplication system, and may adjust a threshold of the deduplication system based on the amount of wear.

Abstract: Examples described herein relate to deletion of data entities in a deduplication system. Examples may maintain entries in a housekeeping queue, each entry including a priority value and a total unshared chunk size of a data entity to be deleted from the deduplication system. Examples may delete the data entities corresponding to the entries including a low priority value from the deduplication system. Examples may determine whether an available storage capacity of the deduplication system is sufficient after deleting the data entities corresponding to the entries including the low priority value. Examples may delete a data entity corresponding to an entry including a high priority value and a largest total unshared chunk size if the available storage capacity is insufficient.

Abstract: Examples may include a deduplication system threshold based on an amount of wear of a storage device. Examples may obtain an indication of an amount of wear experienced by at least one storage device storing a plurality of container indexes of a deduplication system, and may adjust a threshold of the deduplication system based on the amount of wear.

Abstract: Examples may include a deduplication system threshold based on an amount of wear of a storage device. Examples may obtain an indication of an amount of wear experienced by at least one storage device storing a plurality of container indexes of a deduplication system, and may adjust a threshold of the deduplication system based on the amount of wear.

Abstract: Examples may include a deduplication system threshold based on an amount of wear of a storage device. Examples may obtain an indication of an amount of wear experienced by at least one storage device storing a plurality of container indexes of a deduplication system, and may adjust a threshold of the deduplication system based on the amount of wear.

Abstract: Examples may include container index persistent item tags. Examples may store chunk signatures in at least one container index and, for each chunk signature, store at least one persistent item tag identifying a respective backup item that references or formerly referenced the chunk signature. Examples may determine that all chunks formerly referenced by a backup item have been erased based on the persistent item tags in the at least one container index and output an indication that the backup item has been erased.

Abstract: According to an example, to allocate disk storage space, a request to store a new data chunk in a container is received. For a list of available containers, an exposure count for the container is fetched in the event that a container comprises a data chunk from a same source as the new data chunk. An optimal container to store the new data chunk is determined, and in the event that an exposure count of the optimal container is less than an exposure count limit, the new data chunk in the optimal container is stored.

Abstract: A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations.

Abstract: According to an example, to allocate disk storage space, a request to store a new data chunk in a container is received. For a list of available containers, an exposure count for the container is fetched in the event that a container comprises a data chunk from a same source as the new data chunk. An optimal container to store the new data chunk is determined, and in the event that an exposure count of the optimal container is less than an exposure count limit, the new data chunk in the optimal container is stored.

Abstract: Store data chunks associated with data objects to data store files. Determine for each of the data store files reference counts for each of the data chunks indicating number of data objects associated with respective data chunks. Move data chunks to one of the data store files based on whether respective reference counts of respective data chunks exceeds a threshold.

Abstract: Read data blocks based on a read-amount multiplied by an increment-amount from data storage and write the data blocks to the read-ahead buffer. If the total number of data blocks written to the read-ahead buffer is greater than or equal to the request-amount, then returning to the host the total number of data blocks written to the read-ahead buffer. If the total the number of data blocks written to the read-ahead buffer is less than the request-amount, repeating incrementing the increment-amount and reading data blocks equal to the read-amount multiplied by the increment-amount from the data storage, and writing the read data blocks to the read-ahead buffer until the total number of data blocks written to the read-ahead buffer is greater than or equal to the request-amount.

Abstract: Determination may be made, for a first backup file comprising deduplication data in a first backup storage device, whether the first backup file comprises a number of tags ready for deletion higher than a threshold amount. Responsive to determining that the number of tags ready for deletion is higher than the threshold amount, each corresponding set of data associated with a tag ready for deletion in the first backup file may be deleted.

Abstract: Disclosed herein are a system, non-transitory computer readable medium and method of file verification. A request to verify a file in storage is read. A hierarchy of objects associated with metadata of at least the file is analyzed.

Abstract: A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations.

Abstract: A terminal computer is used to send instructions to a host computer through a public network to open and close application programs and to transmit data between the application programs and the terminal computer through the public network. In order to open application programs, the terminal computer establishes an initial connection between the two computers and instructions are sent over this initial connection to open application programs. The host computer establishes an additional connection for each application program. In the terminal computer, a respective terminal emulator window is created for each additional connection. For each application program, data is transmitted over the respective additional connection using a character-based protocol. In the terminal computer, the data is converted from the character-based format to a bit-mapped graphical format and then displayed in the respective terminal emulator window.

Abstract: A network manager for a telecommunications network having a client-server architecture is provided. The components of the network manager include a set of clients which form part of the application programs of the network manager, a user interface, a database containing details of the network and a communications stack for communicating with exchanges managed by the network manager. The clients generate requests to run jobs on the servers. The jobs which are run on certain servers are eventually destined for a resource in the form of a database, while the jobs which are run on other servers are eventually destined for resources in the form of exchanges. The requests are initially passed to a module JBM. This module checks if the resource for which the job is destined is free and, if not, puts the job on a holding queue. If the resource is free, it checks whether the job is scheduled for immediate execution or execution at a future time.