Microsoft Technology Licensing, LLC

Facebook, Inc.

Thomas Alan Bouldin

Ilya Sukhar

Kevin David Lacker

David Eitan Poll

Bryan Jay Klimt, Jr

Michael Brian Jacokes

Eric J Horvitz

Dattatraya B Rajpure

Tahsin Erdogan

David Tepper

Objects stored in a zip archive may be extracted in random-access fashion (without involving other objects stored in the zip archive) using the addresses of the objects stored in the central directory of the zip archive. However, zip archives often provide insufficient information to enable random access to the data within an object. This capability may be provided by segmenting the object into sections of a section size, and including in the zip archive a block table specifying, for respective sections, the block size of the corresponding block. A zip archive extractor may achieve random access to the object by using the block table to computing the addresses of blocks comprising the selected portion and extracting only those blocks. Backwards compatibility of the zip archive with other zip archive extractors may be preserved by including the block table within a zip extension of the central directory of the zip archive.

Enabling random access within objects in zip archives

Techniques to generate mass push notifications are described. In one embodiment, for example, an apparatus may comprise a submission component, a query component, a delivery component, and a record update component. The submission component may be operative to receive a message bundle, the message bundle comprising a message and a query. The query component may be operative to compare the query to a plurality of recipient records to determine a plurality of recipient records matching the query, each of the plurality of recipient records corresponding to a particular installation of a particular application onto a particular device. The delivery component may be operative to broadcast the message to a plurality of installed applications corresponding to the plurality of recipients records matching the query. Other embodiments are described and claimed.

Techniques to generate mass push notifications

A software streaming platform may be implemented that predictively chooses units of a program to download based on the value of downloading the unit. In one example, a program is divided into blocks. The sequence in which blocks of the program historically have been requested is analyzed in order to determine, for a given history, what block is the next most likely to be requested. Blocks then may be combined into chunks, where each chunk represents a chain of blocks that have a high likelihood of occurring in a sequence. A table is then constructed indicating, for a given chunk, the chunks that are most likely to follow the given chunk. Based on the likelihood table and various other considerations, the value of downloading particular chunks is determined, and the chunk with the highest expected value is downloaded.

Predictive software streaming

Files, or other data, may be stored in a package, and the contents of the package may be retrieved incrementally and/or on-demand. In one example, files are packaged into a ZIP file or similar type of package. Additionally, metadata is added to the package that describes the contents of the package at the sub-file level, thereby allowing portions of files to be retrieved by appropriately-configured software. When the package is to be used on a local machine, placeholder files may be created on that machine, which are to be populated by the package's contents at a later time. When a request for data in the package is made, if the data does not reside locally, then a request for the specific data (possibly at the sub-file level) is made, and the placeholder files are populated with the actual package data.

On-demand or incremental remote data copy

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San Francisco, CA, United States of America

Thomas Alan Bouldin