Abstract: The proposed system defines a predictive real-time Service Level Agreements (SLAs) monitoring system by (a) a detailed analysis of traffic flows with reduced monitor-data flow across network; and (b) a suitable combination of offline and real-time processing of historical and current traffic data. In order to be able to undertake a detailed analysis without significantly impacting the network throughput, the system analyzes the historical traffic patterns of a typical Provider's network to determine a set of critical SLAs. An in-depth analysis of traffic is performed by creating a unique network parent probe for every critical SLA and the parent probe spawns an optimal number of intelligent master and slave probes based on a regionalization procedure. The online overload monitoring system analyzes the gathered data from the master and slave probes to (a) forecast future violations of the SLA under consideration based on multiple forecast models and (b) generate operator SLA violation alarms.

Abstract: A fault identification system analyzes alarm information and the associated contextual information to identify the occurred faults. The contextual information is based on usecases, transactions, and functions associated with the electronic system under consideration. Multiple detectors that form part of knowledge repositories are used in the process of fault identification.

Abstract: The proposed system defines a comprehensive video license distribution system to achieve the zero-reject of requests from subscribers, maximizing the usage of licenses and minimizing the churn rate by (a) using symbolic and numeric features of movies; (b) planning video license distribution of different license kinds to a predictable group of subscribers based on the analysis of subscriber video viewing patterns; (c) exclusive handling of unpredictable behavior of subscribers; (d) the effective trading of favor points; (e) intelligent timing and selection of subscriber specific previews; and (f) the detailed analysis of subscriber complaints.

Abstract: A fault identification system consisting of multiple reasoning engines and the blackboard analyzes alarm information and the associated contextual information to identify faults. The contextual information associated with an alarm is derived by analyzing the alarm along four spaces, namely, transaction-space, function-space, execution-space, and signal-space. The reasoning engines associated with these spaces infer and/or validate the occurrences of faults. Transaction reasoning engine, using the associated knowledge repository, processes the generated alarms to infer and validate faults. Monitor reasoning engine, using the associated knowledge repository, processes domain specific monitor variables to infer faults. Execution reasoning engine, using the associated knowledge repository, processes execution specific monitor variables to infer and validate faults. Function reasoning engine, using the associated knowledge repository, reasons to infer and validate faults.

Abstract: The proposed system defines an automated safe reprogramming of software radios. The essence of software radios is to enhance or alter the functionality of a mobile terminal by using software. This means that the required software is downloaded onto a mobile terminal on the fly to meet the critical and necessary needs of the user. Lot of caution needs to be exercised while downloading the necessary software components on the fly. The proposed invention automates the validation and verification of the downloaded component by suggesting (a) a means for the computation of signatures; (b) a means for defining multiple zones and verification of zone-specific signatures; (c) a means for periodic online verification of the downloaded components; and (d) a means for collecting the usage statistics of the downloaded components. The objective is to define the safeness of the downloaded component based on multiple signatures to be validated in different zones.

Abstract: The proposed system defines a predictive real-time Service Level Agreements (SLAs) monitoring system by (a) a detailed analysis of traffic flows with reduced monitor-data flow across network; and (b) a suitable combination of offline and real-time processing of historical and current traffic data. In order to be able to undertake a detailed analysis without significantly impacting the network throughput, the system analyzes the historical traffic patterns of a typical Provider's network to determine a set of critical SLAs. An in-depth analysis of traffic is performed by creating a unique network parent probe for every critical SLA and the parent probe spawns an optimal number of intelligent master and slave probes based on a regionalization procedure. The online overload monitoring system analyzes the gathered data from the master and slave probes to (a) forecast future violations of the SLA under consideration based on multiple forecast models and (b) generate operator SLA violation alarms.

Abstract: An advertisement system that provides subscribers with the most relevant advertisements based on their individual purchase prediction of the various products and contextual information such as location, ongoing public events, festivals and personal events. The system customizes the advertisements to suit the audiovisual, language, and textual caption preferences of the subscribers. System provides for tracking of various promotional offers made to the subscribers from the time the offer is made to the time it is redeemed by the subscriber. System consists of methods to learn (a) purchase predictions (b) preferred streaming schedule and (c) the subscriber's preferences in terms of audiovisual aspects of the advertisements. Purchase prediction for individual subscriber is derived from historical purchase data by time series analysis and the influence of events such as co-purchases of other products and organized events such as sales exhibitions and festivals is derived based on Bayesian network models.