Patent application number | Description | Published |
20110283099 | Private Aggregation of Distributed Time-Series Data - Techniques are described herein for privately aggregating distributed time-series data. A requestor provides a query sequence to users. Each user evaluates the query sequence on the user's time-series data to determine an answer sequence. Each user transforms its answer sequence to another domain, adds noise, and encrypts it for further processing by the requestor. The requestor combines these encrypted sequences in accordance with a homomorphic encryption technique to provide an encrypted summation sequence. The requestor provides the encrypted summation sequence to at least some of the users, who may in turn provide respective decryption shares to the requestor. The requestor combines the decryption shares in an effort to decrypt the encrypted summation sequence. Decrypting the encrypted summation sequence provides a summation of the encrypted sequences from the users, which may be transformed back to the original domain to estimate a summation of the answer sequences of the users. | 11-17-2011 |
20120280035 | MAGNETIC STRIPE-BASED TRANSACTIONS USING MOBILE COMMUNICATION DEVICES - Magnetic stripe-based transaction enabled mobile communication device embodiments are presented which generally involve a mobile communication device which has been configured to perform transactions that heretofore were completed using a magnetic stripe found on magnetic-stripe cards. In one general embodiment, a mobile communication device generates magnetic stripe data which is used to perform a magnetic stripe-based transaction. To this end, the mobile communication device includes a magnetic stripe device and a computing device. The computing device stores the magnetic stripe data, and the magnetic stripe device is employed to transfer the stored magnetic stripe information so that it can be used to conduct transactions as if a traditional magnetic stripe card were being used. | 11-08-2012 |
20120284194 | SECURE CARD-BASED TRANSACTIONS USING MOBILE PHONES OR OTHER MOBILE DEVICES - A “Portable Card Generator” is implemented within a portable device, such as a mobile phone, and provides various techniques for writing secure account information from user selected accounts to a “wildcard” having rewritable magnetic stripes, rewritable RFID tags, and/or rewritable smartcard circuitry. The account information is retrieved by the portable device from local or remote stores of user accounts. Once that account information is written, the wildcard is then available for immediate use for credit card or debit-type payments, loyalty card use, etc. Consequently, by providing a credit card sized object having a rewriteable magnetic stripe, RFID tag, and/or smartcard circuitry, in combination with account information for various credit cards, debit cards, consumer loyalty cards, insurance cards, ID cards or badges, etc., the user is no longer required to physically carry those cards in order to use the corresponding accounts within existing card-based infrastructures. | 11-08-2012 |
20130159237 | METHOD FOR RULE-BASED CONTEXT ACQUISITION - Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules. If the inferred value of the target context cannot be determined, the method further includes executing a first step of a sensing plan for acquiring an inferred value of the target context using a rule-based acquisition planner, as well as executing any of a number of subsequent steps of the sensing plan until the inferred value of the target context is obtained. | 06-20-2013 |
20140189086 | COMPARING NODE STATES TO DETECT ANOMALIES - Methods, systems, and computer storage media for detecting anomalies within nodes of a data center are provided. A self-learning system is employed to proactively and automatically detect the anomalies using one or more locally hosted agents for pulling information that describes states of a plurality of nodes (e.g., computing devices of a cloud-computing infrastructure), respectively, and using at least one early-warning mechanism for implementing a comparison technique. The comparison technique involves individually comparing the state information of the plurality of the nodes against one another and, based upon the comparison, grouping one or more nodes of the plurality of nodes into clusters that exhibit substantially similar state information. Upon identifying the clusters that include low number of nodes grouped therein, with respect to a remainder of the clusters of nodes, the members of the identified clusters are designated as anomalous machines. | 07-03-2014 |
20140236919 | EXECUTING A FAST CRAWL OVER A COMPUTER-EXECUTABLE APPLICATION - Technologies related to crawling computer-executable applications are described. A full crawl is executed over an application, where executing the full crawl includes causing the application to output a plurality of pages. The application retrieves content from the World Wide Web when generating the pages for output. Thereafter, a fast crawl is executed over the application, where executing the fast crawl takes less time when compared to the time needed to execute the full crawl. | 08-21-2014 |
20140335920 | METHOD FOR RULE-BASED CONTEXT ACQUISITION - Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules without initializing sensor procedures as a result of the request. | 11-13-2014 |
Patent application number | Description | Published |
20080247313 | Slot-Cache for Caching Aggregates of Data with Different Expiry Times - Techniques for collecting and displaying sensor data captured by a spatially and temporally representative sample of sensors requested in a search query are described. The sensors are represented in an index structure (e.g., a data tree) having a plurality of leaf nodes and internal nodes. The leaf nodes are associated with sensors and the internal nodes are allotted with caches having cache slots for storing sensor data with various expiry times. In response to a query, the index structure is leveraged to identify a set of nodes associated with sensors of a user selected spatial region. Sensor data having an expiry time greater than a user specified expiry time is then collected from one or more cache slots of the set of nodes. In this manner, the number of sensors to be probed to collect the sensor data is reduced. | 10-09-2008 |
20080259875 | Sleep Scheduling for Geographically Distributed Network Nodes - Techniques for implementing sleep scheduling in a distributed network environment are described. The sleep scheduling attempts to optimize routing of communication among nodes of the distributed network, while still conserving energy by allowing nodes to occasionally transition to sleep mode. The sleep scheduling is performed as a function of the number of awake neighboring nodes. | 10-23-2008 |
20080263061 | Self-Tuning Index for Flash-Based Databases - Techniques for self-tuning indices for databases, including flash-based databases, are described. Using a data tree structure wherein the nodes of the data tree may operate in two modes (e.g. disk mode or log mode), a self-tuning index determines whether it is more economical to perform a requested operation on a node in its current mode or in an alternate mode. The operation is then performed on the node using the more economical mode. | 10-23-2008 |
20080263114 | EFFICIENT ACCESS OF FLASH DATABASES - Techniques for efficient access to flash databases are described. In one implementation, a method includes performing an operation on a flash database, supplementing at least one portion of a node translation table corresponding to at least one node involved in the operation, and semantically compressing at least one portion of the node translation table. The semantic compression includes discarding at least one log entry that is rendered obsolete by at least one subsequent log entry, and incrementing a version number of the log entries corresponding to the at least one portion of the node translation table. In further embodiments, discarding at least one log entry includes discarding at least one log entry that is at least one of opposed by or overruled by at least one subsequent log entry. | 10-23-2008 |
20100290617 | SECURE OUTSOURCED AGGREGATION WITH ONE-WAY CHAINS - Secure outsourced aggregation of data using one-way chains is discussed in this application. Each input data source such as a sensor generates a Verifiable Synopsis (“VS”) which includes sensor data, an Inflation Free Proof (“IFP”) generated using a cryptographic function and a Self-Authenticating Value (“SEAL”) chain generated using a one-way function. An aggregator takes a plurality VSs from multiple data sources and aggregates them together into one. Maximum value, top-k, count, count distinct, sum, average, and other aggregate functions may be used. Folded VS provides a concise proof that no value greater than the maximum value was reported by a sensor, thus providing a check against deflation of sensor data. Similarly, the cryptographic function of the IFP provides a mechanism to prevent inflation of the sensor data. Thus it becomes possible at a portal to verify that aggregated data has not been inflated or deflated by the aggregator. | 11-18-2010 |
20120316956 | Client-Server Joint Personalization for Private Mobile Advertising - The subject disclosure is directed towards personalizing content (e.g., advertisement) delivery to a mobile device such as a smartphone, without violating user privacy. A user decides how much context information (from the device's sensor readings and/or other data) to share with an advertisement server. Based on this limited, partial context information, the server selects a subset of advertisements from those available and sends them to the client. The client then picks the most relevant one based on richer, more granular context data, e.g., more (or even all) of the device's sensor readings and possibly other non-revealed information such as user preference data. The optimization of selecting the most relevant advertisement to display is done jointly by the user and the server, with the server selecting a subset of advertisements based upon partial context, and the client selecting from the subset based upon full context. | 12-13-2012 |
20120323926 | Efficient Optimization over Uncertain Data - The subject disclosure is directed towards using fingerprints, comprising lists of simulation results corresponding to partial (random sampled) simulation results, to determine whether a full simulation may be avoided by reusing simulation results from a previous full simulation. Before running a full simulation, a current fingerprint is obtained via a partial simulation. If a previous fingerprint matches (is identical or similar to) the current fingerprint, the associated previous results are reused. Also described is indexing fingerprint data to facilitate efficient lookup-based fingerprint matching. | 12-20-2012 |
20130166712 | CLOUD-EDGE TOPOLOGIES - The description relates to cloud-edge topologies. Some aspects relate to cloud-edge applications and resource usage in various cloud-edge topologies. Another aspect of the present cloud-edge topologies can relate to the specification of cloud-edge applications using a temporal language. A further aspect can involve an architecture that runs data stream management systems (DSMSs) engines on the cloud and cloud-edge computers to run query parts. | 06-27-2013 |
20140372160 | CONTEXT-AWARE MOBILE CROWDSOURCING - The subject disclosure is directed towards a context-aware mobile crowd sourcing service/system. Context information is automatically collected for a mobile device via mobile-device sensors. When a task is received that specifies context-related criteria, a worker is selected for that task based at least in part upon the context information associated with that worker's mobile device. Sensors on the device may be leveraged to capture information related to performing the task. Also described is a cross-platform task configuration that allows a task to be written once and run on different mobile device platforms. | 12-18-2014 |
20140372216 | CONTEXTUAL MOBILE APPLICATION ADVERTISEMENTS - Aspects of the subject disclosure are directed towards retrieving advertisements relevant to application content based upon keywords extracted from the application content. In one aspect, a client-side component scrapes application page content to obtain keywords and feature-based weights for those keywords. The keywords are sent to an advertisement server, which returns an advertisement based upon one or more of the keywords. Also described is the hashing of keywords before sending to the advertisement server to protect client privacy, and the use of a Bloom filter to avoid sending keywords to the advertisement server that do not correspond to (e.g., popular) advertisement keywords. | 12-18-2014 |
Patent application number | Description | Published |
20090125918 | SHARED SENSING SYSTEM INTERFACES - Various interfaces such as application programming interfaces (APIs) are employed to allow developers to construct applications that use multiple shared sensors. In one instance, a coordinator can be utilized to facilitate coordination of sensor data contributors and applications desirous of utilizing such data. Standardized interfaces can be employed to aid interaction between all entities including contributors, applications and a coordinator, amongst others. | 05-14-2009 |
20090144011 | ONE-PASS SAMPLING OF HIERARCHICALLY ORGANIZED SENSORS - One-pass sampling is employed within a hierarchically organized structure to efficiently and expeditiously respond to sensor inquires. Identification of relevant sensors and sampling of those sensors is combined and performed in a single pass. Oversampling can also be employed to ensure a target sample size is met where some sensors fail or are otherwise unavailable. Further yet, sensor data can be cached and utilized to hasten processing as well as compensate for occasional sensor unavailability. | 06-04-2009 |
20090222544 | FRAMEWORK FOR JOINT ANALYSIS AND DESIGN OF SERVER PROVISIONING AND LOAD DISPATCHING FOR CONNECTION-INTENSIVE SERVER - The claimed subject matter provides a system and/or a method that facilitates managing a number of active servers in a cluster. A forecast component can predict at least one of login rate or number of connections in the cluster at a future time. A dynamic load analysis component can evaluate dynamic behaviors in login rate and number of connections in the cluster as a result of load dispatching. Moreover, a provisioning component can determine a number of servers in the cluster needed based at least in part on the prediction and dynamic behavior analysis. In addition, the provisioning component can include an additional margin in the number of servers needed in accordance with multiplicative factors. | 09-03-2009 |
20090222562 | LOAD SKEWING FOR POWER-AWARE SERVER PROVISIONING - The claimed subject matter provides a system and/or a method facilitates energy-aware connection distribution among a plurality of servers in a cluster. A set of busy servers in the cluster can be provided that each handle a high number of connections. In addition, a set of tail servers in the cluster can be managed that each maintain a low number of connections. A load skewing component gives priority to at least a subset of the set of busy servers when dispatching new connection requests from a plurality of users. In addition, the load skewing component controls the number of tail servers to maintain a sufficient number for energy-aware operation. | 09-03-2009 |
20090327376 | B-FILE ABSTRACTION FOR EFFICIENTLY ARCHIVING SELF-EXPIRING DATA - Systems and methods are provided for data processing and storage management. In an illustrative implementation an exemplary computing environment comprises at least one data store, a data processing and storage management engine (B-File engine) and at least one instruction set to instruct the B-File engine to process and/or store data according to a selected data processing and storage management paradigm. In an illustrative operation, the illustrative B-File engine can generate a B-File comprising multiple buckets and store sample items in a random bucket according to a selected distribution. When the size of the B -FILE grows to reach a selected threshold (e.g., maximum available space), the B-File engine can shrink the B-File by discarding the largest bucket. Additionally, the B-File engine can append data to existing buckets and explicitly cluster data when erasing data such that data can be deleted together into the same flash block. | 12-31-2009 |
20100030809 | MAINTAINING LARGE RANDOM SAMPLE WITH SEMI-RANDOM APPEND-ONLY OPERATIONS - Systems and methods are provided for online maintenance, processing, and querying of large random samples of data from a large/infinite data stream. In an illustrative implementation an exemplary computing environment comprises at least one data store, a data storage and management engine operable to process and/or store data according to a selected data processing and storage management paradigm on a cooperating data store (e.g., flash media). The exemplary data storage and management engine can deploy the exemplary sampling algorithm to perform and/or provide one or more of the following operations/features comprising the algorithm is operable for streaming data (or a single pass through the dataset), allows for the semi-random data write operations, the algorithm avoids operations (e.g., in-place updates) that are expensive on flash storage media, and the algorithm is tunable to both the amount of flash storage and the amount of standard memory (DRAM) available to the algorithm. | 02-04-2010 |
20100325132 | QUERYING COMPRESSED TIME-SERIES SIGNALS - A system described herein includes a receiver component that receives a query that pertains to a raw time-series signal. A query executor component selectively executes the query over at least one of multiple available compressed representations of the raw time-series signal, wherein the query pertains to at least one of one of determining a trend pertaining to the raw time-series signal, generating a histogram pertaining to the raw time-series signal, or determining a correlation pertaining to the raw time-series signal. | 12-23-2010 |
20120110015 | SEARCH CACHE FOR DOCUMENT SEARCH - A method is described herein that includes receiving a query from a user at a computing device. The method also includes performing a search for one or more documents based at least in part upon the received query, wherein performing the search comprises causing a processor to perform the search through utilization of a search cache retained on the computing device, wherein the search cache comprises a results cache, an index cache, and a Boolean cache. | 05-03-2012 |
20120131009 | ENHANCING PERSONAL DATA SEARCH WITH INFORMATION FROM SOCIAL NETWORKS - The personal data search technique uses data input by users for a given user's personal data on a social networking site to enrich the given user's personal data. The technique annotates personal data stored on a personal computing device or in a computing cloud with data obtained from social networking sites (for example, tags, comments, likes/dislikes and so forth) provided by friends/other users in the given user's social network or networks. Such annotations can later are used by search engine to enhance the search functionality and/or to improve the ranking of search results. Since the data is entered by actual human users it is very accurate and since the data is already readily available on social networks the cost to obtain it is very inexpensive. | 05-24-2012 |
20120246169 | QUERYING COMPRESSED TIME-SERIES SIGNALS - Technologies pertaining to compressing time-series signals are described herein. Groups of time-series signals are generated based upon similarities between time-series signals. Each group of time-series signals includes a respective base time-series signal. Ratio signals that are representative of time-series signals are computed, wherein the ratio signals are based upon the base time-series signal and other respective time-series signals in a group of time-series signals. | 09-27-2012 |
20130332442 | DEEP APPLICATION CRAWLING - The deep application crawling technique described herein crawls one or more applications, commonly referred to as “apps”, in order to extract information inside of them. This can involve crawling and extracting static data that are embedded within apps or resource files that are associated with the apps. The technique can also crawl and extract dynamic data that apps download from the Internet or display to the user on demand, in order to extract data. This extracted static and/or data can then be used by another application or an engine to perform various functions. For example, the technique can use the extracted data to provide search results in response to a user query entered into a search engine. Alternately, the extracted static and/or dynamic data can be used by an advertisement engine to select application-specific advertisements. Or the data can be used by a recommendation engine to make recommendations for goods/services. | 12-12-2013 |
20140279026 | ENERGY-EFFICIENT MOBILE ADVERTISING - Various technologies described herein pertain to prefetching advertisements for mobile advertising. A prediction model for estimating a number of advertisements that a mobile client is likely to request during an upcoming prediction time period can be employed. An estimated total amount of time of likely interaction with application(s) executed by the mobile client can be predicted; based upon such prediction, a number of advertisement slots likely to be available and a probability of each of the advertisement slots being available can be computed. Moreover, an ad server can allocate advertisements in a pending advertisement queue and/or disparate advertisements collected from an ad exchange to the mobile client based upon the number of advertisement slots likely to be available, the probability of each of the advertisements slots being available, and aggregated probabilities of the pending advertisements in the pending advertisement queue being displayed prior to corresponding deadlines for expiration. | 09-18-2014 |