Abstract: The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components for determining and presenting a health profile for the RAN components. Systems described herein involve implementing event tracking agents on the RAN components, compiling instances of detected events via event streams from the respective RAN components, and determining a health profile that reflects a current or predicted health state for components that make up a RAN. The systems described herein may further generate and present a health profile presentation including interactive icons and features that enable an individual to view health profile data for specific RAN sites, RAN components, and even user devices associated with the tracked events. Systems described herein may perform various mitigation actions to overcome poor health conditions as they are observed or predicted over time.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components. For example, the systems described herein can identify data signals that are tracked by one or more RAN components. Based on these data signals, the systems can define any number of network events that may be tracked by event tracking agents that are deployed on each of the RAN component(s). The RAN components may then provide a stream of event instances to the systems for collecting, analyzing, and otherwise utilizing the network event data that is locally tracked by the respective RAN components.

Abstract: A plurality of computing devices are provisioned configured to communicate on a mobile communications network operated, in part, by an edge computing network. The edge computing network is associated with a customer of a computing service provider. The edge computing network comprises computing and storage devices configured to extend computing resources of the computing service provider to the customer of the computing service provider. A selection is received of a SIM provider and a quantity of SIM profiles for enabling the plurality of computing devices to access the mobile communications network. SIM data corresponding to the quantity of SIM profiles is received. The SIM data is encrypted and received over an encrypted channel.

Abstract: A plurality of computing devices are provisioned configured to communicate on a mobile communications network operated, in part, by an edge computing network. The edge computing network is associated with a customer of a computing service provider. The edge computing network comprises computing and storage devices configured to extend computing resources of the computing service provider to the customer of the computing service provider. A selection is received of a SIM provider and a quantity of SIM profiles for enabling the plurality of computing devices to access the mobile communications network. SIM data corresponding to the quantity of SIM profiles is received. The SIM data is encrypted and received over an encrypted channel.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components. For example, the systems described herein can identify data signals that are tracked by one or more RAN components. Based on these data signals, the systems can define any number of network events that may be tracked by event tracking agents that are deployed on each of the RAN component(s). The RAN components may then provide a stream of event instances to the systems for collecting, analyzing, and otherwise utilizing the network event data that is locally tracked by the respective RAN components.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components for determining and presenting a health profile for the RAN components. Systems described herein involve implementing event tracking agents on the RAN components, compiling instances of detected events via event streams from the respective RAN components, and determining a health profile that reflects a current or predicted health state for components that make up a RAN. The systems described herein may further generate and present a health profile presentation including interactive icons and features that enable an individual to view health profile data for specific RAN sites, RAN components, and even user devices associated with the tracked events. Systems described herein may perform various mitigation actions to overcome poor health conditions as they are observed or predicted over time.

Abstract: A plurality of computing devices are provisioned configured to communicate on a mobile communications network operated, in part, by an edge computing network. The edge computing network is associated with a customer of a computing service provider. The edge computing network comprises computing and storage devices configured to extend computing resources of the computing service provider to the customer of the computing service provider. A selection is received of a SIM provider and a quantity of SIM profiles for enabling the plurality of computing devices to access the mobile communications network. SIM data corresponding to the quantity of SIM profiles is received. The SIM data is encrypted and received over an encrypted channel.

Abstract: According to various embodiments, a system for vehicular application development is disclosed. The system includes a programmable on-board diagnostics (OBD)-connected dongle for providing computational and storage resources to a vehicle and hosting one or more applications in the vehicle. The dongle is configured to utilize one or more external devices, cloud servers, and add-on modules to provide additional resources for the applications and enable control of the applications. The dongle is implemented with a middleware that enables intended operations of the dongle.

Abstract: According to various embodiments, a method for locating the user of a mobile device without accessing global position system (GPS) data is disclosed. The method includes determining the last location that the user was connected to a wireless network. The method further includes compiling publicly-available auxiliary information related to the last location. The method additionally includes classifying an activity of the user to driving, traveling on a plane, traveling on a train, or walking. The method also includes estimating the location of the user based on sensory and non-sensory data of the mobile device particular to the activity classification of the user.

Abstract: According to various embodiments, a method for locating the user of a mobile device without accessing global position system (GPS) data is disclosed. The method includes determining the last location that the user was connected to a wireless network. The method further includes compiling publicly-available auxiliary information related to the last location. The method additionally includes classifying an activity of the user to driving, traveling on a plane, traveling on a train, or walking. The method also includes estimating the location of the user based on sensory and non-sensory data of the mobile device particular to the activity classification of the user.

Abstract: According to various embodiments, a system for vehicular application development is disclosed. The system includes a programmable on-board diagnostics (OBD)-connected dongle for providing computational and storage resources to a vehicle and hosting one or more applications in the vehicle. The dongle is configured to utilize one or more external devices, cloud servers, and add-on modules to provide additional resources for the applications and enable control of the applications. The dongle is implemented with a middleware that enables intended operations of the dongle.

Abstract: An approach to implementing or configuring an Oblivious RAM (ORAM), which in addition to behaving as a RAM, provides a way to meet a specified degree of privacy in a manner that avoids applying unnecessary computation resources (computation time and/or storages space and/or data transfer) to achieve the specified degree of privacy. In this way, a tradeoff between privacy and computation resources may be tuned to address requirements of a particular application. This ability to tune this tradeoff is not found in other ORAM implementations, which in general aim to achieve complete privacy. In some implementations, the ORAM provides a constant bandwidth overhead compared to conventional RAMs, while achieving a statistical privacy as desired by the user.

Abstract: An approach to implementing or configuring an Oblivious RAM (ORAM), which in addition to behaving as a RAM, provides a way to meet a specified degree of privacy in a manner that avoids applying unnecessary computation resources (computation time and/or storages space and/or data transfer) to achieve the specified degree of privacy. In this way, a tradeoff between privacy and computation resources may be tuned to address requirements of a particular application. This ability to tune this tradeoff is not found in other ORAM implementations, which in general aim to achieve complete privacy. In some implementations, the ORAM provides a constant bandwidth overhead compared to conventional RAMs, while achieving a statistical privacy as desired by the user.

Abstract: The present invention relates to a method for stratifying a patient into a clinically relevant group comprising the identification of the probability of an alteration within one or more sets of molecular data from a patient sample in comparison to a database of molecular data of known phenotypes, the inference of the activity of a biological network on the basis of the probabilities, the identification of a network information flow probability for the patient via the probability of interactions in the network, the creation of multiple instances of network information flow for the patient sample and the calculation of the distance of the patient from other subjects in a patient database using multiple instances of the network information flow.