Abstract:
A method in a graph storage and processing system is provided. The method includes storing, in a scalable, distributed, fault-tolerant, in-memory graph storage device, base graph data representative of graphs, and storing, in a real-time, in memory graph storage device, update graph data representative of graph updates for the graphs with respect to a time threshold. The method further includes sampling the base graph data to generate sampled portions of the graphs and storing the sampled portions, by an in-memory graph sampler. The method additionally includes providing, by a query manager, a query interface between applications and the system. The method also includes forming, by the query manager, graph data representative of a complete graph from at least the base graph data and the update graph data, if any. The method includes processing, by a graph computer, the sampled portions using batch-type computations to generate approximate results for graph-based queries.
Abstract:
Systems and methods for swapping out and in pinned memory regions between main memory and a separate storage location in a system, including establishing an offload buffer in an interposing library; swapping out pinned memory regions by transferring offload buffer data from a coprocessor memory to a host processor memory, unregistering and unmapping a memory region employed by the offload buffer from the interposing library, wherein the interposing library is pre-loaded on the coprocessor, and collects and stores information employed during the swapping out. The pinned memory regions are swapped in by mapping and re-registering the files to the memory region employed by the offload buffer, and transferring data of the offload buffer data from the host memory back to the re-registered memory region.
Abstract:
A runtime method is disclosed that dynamically sets up core containers and thread-to-core affinity for processes running on manycore coprocessors. The method is completely transparent to user applications and incurs low runtime overhead. The method is implemented within a user-space middleware that also performs scheduling and resource management for both offload and native applications using the manycore coprocessors.
Abstract:
Systems and methods are provided for deploying applications within a wireless network infrastructure, including initiating, by a centralized control module in a pre-configured hardware unit having a 5G wireless communication module, edge computing device, centralized control module, and data processing module with access to cloud resources, a setup procedure upon receiving a deployment command, the setup procedure including activating the 5G wireless communication module to establish a network connection. User equipment for communication with sensors and cameras is deployed using an edge device through the network connection. Application deployment is managed using a centralized control module including an edge cloud optimizer for allocating resources between an edge computing device and the cloud resources based on real-time analysis of network conditions and application requirements. Computing resource allocation between the edge computing device and cloud resources is dynamically adjusted for application requirements and network conditions during automated application deployment and optimization.
Abstract:
A method for real-time cross-spectral object association and depth estimation is presented. The method includes synthesizing, by a cross-spectral generative adversarial network (CS-GAN), visual images from different data streams obtained from a plurality of different types of sensors, applying a feature-preserving loss function resulting in real-time pairing of corresponding cross-spectral objects, and applying dual bottleneck residual layers with skip connections to accelerate real-time inference and to accelerate convergence during model training.
Abstract:
A pull-based communication method for microservices-based real-time streaming video analytics pipelines is provided. The method includes receiving a plurality of frames from a plurality of cameras, each camera including a camera sidecar, arranging a plurality of detectors in layers such that a first detector layer includes detectors with detector sidecars and detector business logic, and the second detector layer includes detectors with only sidecars, arranging a plurality of extractors in layers such that a first extractor layer includes extractors with extractor sidecars and extractor business logic, and the second extractor layer includes extractors with only sidecars, and enabling a mesh controller, during registration, to selectively assign inputs to one or more of the detector sidecars of the first detector layer and one or more of the extractor sidecars of the first extractor layer to pull data items for processing.
Abstract:
A method for implementing application self-optimization in serverless edge computing environments is presented. The method includes requesting deployment of an application pipeline on data received from a plurality of sensors, the application pipeline including a plurality of microservices, enabling communication between a plurality of pods and a plurality of analytics units (AUs), each pod of the plurality of pods including a sidecar, determining whether each of the plurality of AUs maintains any state to differentiate between stateful AUs and stateless AUs, scaling the stateful AUs and the stateless AUs, enabling communication directly between the sidecars of the plurality of pods, and reusing and resharing common AUs of the plurality of AUs across different applications.
Abstract:
A method for automatically adjusting camera parameters to improve video analytics accuracy during continuously changing environmental conditions is presented. The method includes capturing a video stream from a plurality of cameras, performing video analytics tasks on the video stream, the video analytics tasks defined as analytics units (AUs), applying image processing to the video stream to obtain processed frames, filtering the processed frames through a filter to discard low-quality frames and dynamically fine-tuning parameters of the plurality of cameras. The fine-tuning includes passing the filtered frames to an AU-specific proxy quality evaluator, employing State-Action-Reward-State-Action (SARSA) reinforcement learning (RL) computations to automatically fine-tune the parameters of the plurality of cameras, and based on the reinforcement computations, applying a new policy for an agent to take actions and learn to maximize a reward.
Abstract:
Methods and systems for managing communications include identifying a system condition in a distributed computing system comprising a first microservice in communication with a second microservice. A communications method is identified responsive to the identified system condition using a reinforcement learning model that associates communication methods with system conditions. The identified communications method is implemented for communications between the first microservice and the second microservice, such that the first microservice and the second microservice use the identified communications method to transmit data.
Abstract:
A method for tracing individuals through physical spaces that includes registering cameras in groupings relating a physical space. The method further includes performing local video monitoring including a video sensor input that outputs frames from inputs from recording with the cameras in the groupings, a face detection application for extracting faces from the output frames, and a face matching application for matching faces extracted from the output frames to a watchlist, and a local movement monitor that assigns tracks to the matched faces. The method further includes performing a global monitor including a biometrics monitor for preparing the watchlist of faces, the watchlist of faces being updated when a new face is detected by the cameras in the groupings, and a global movement monitor that combines the outputs from the assigned tracks to the matched faces to launch a report regarding individual population traveling to the physical spaces.