Abstract: Methods, systems, and apparatuses provide support for allowing thread forward progress in a processing system and that improves quality of service. One system includes a processor; a bus coupled to the processor; a memory coupled to the processor via the bus; and a floating point unit coupled to the processor via the bus, wherein floating point unit comprises hardware control logic operative to: store for each thread, by a scheduler of the floating point unit, a counter; increase, by the scheduler, a value of the counter for each thread corresponding to a thread when at least one source ready operation exist for the thread; compare, by the scheduler, the value of the counter to a predetermined threshold; and make other threads ineligible to be picked by the scheduler when the counter is greater than or equal to the predetermined threshold.

Abstract: An apparatus comprises a processing device configured to obtain information associated with an application and to determine, based at least in part on the obtained information, values associated with metrics characterizing suitability of hosting the application at edge computing sites of an information technology infrastructure. The processing device is also configured to generate, based at least in part on the determined values, a score for the application, and to analyze workload status of the edge computing sites. The at least one processing device is further configured to select, based at least in part on the score for the application and the workload status of the edge computing sites, whether to host the application at a core computing site of the information technology infrastructure or the edge computing sites, and to host the application at the selected one of the core computing site and the edge computing sites.

Abstract: A dangerous scene prediction device 80 for predicting a dangerous scene occurring during driving of a vehicle includes a learning model selection/synthesis unit 81 and a dangerous scene prediction unit 82. The learning model selection/synthesis unit 81 selects, from two or more learning models, a learning model used for predicting the dangerous scene, depending on a scene determined based on information obtained during the driving of the vehicle. The dangerous scene prediction unit 82 predicts the dangerous scene occurring during the driving of the vehicle, using the selected learning model.

Abstract: A computer hardware system includes a machine learning engine and a hardware processor configured to perform the following executable operations. A stake in a software product is converted into feature development tokens to be stored in the digital wallet. A description of a plurality of proposed product features for the software product and previously-stored within a blockchain are forwarded to a usage user via a usage user portal. A plurality of the feature development tokens are allocated, using the usage user portal, to a selected one of the proposed product features. The digital wallet and the blockchain are updated based upon the allocating. An objective analysis is performed on the plurality of proposed product features using the machine learning engine. The blockchain is updated based upon a delivered one of the plurality of the proposed product features.

Abstract: Collaborative environments can allow multiple users access to view and modify objects. In order to avoid conflicting requests from different users to modify objects in the environment, virtual semaphore objects can be made available to users in a collaborative environment. A virtual semaphore can confer an ability to edit or modify objects in the environment, upon being assigned to a user. Users can request changes to user-semaphore assignments, including summoning a semaphore to be self-assigned, surrendering a self-assigned semaphore, transferring a semaphore from one user to another, and scheduling a semaphore assignment to a particular user at a future time. Upon assignment to a particular user, a virtual semaphore can be moved to a location close to a virtual representation of the particular user. Users can request changes to user-semaphore assignments using input devices by making selections in a graphical user interface, or by performing gestures associated with virtual semaphores.

Abstract: A computer implemented method comprises a server processing work requests of a work requester. The work requester can communicate to the server a processing dependency of one work request on a second work request. The server can associate the dependency with the work requests and/or a queue of work requests. The dependency include a condition to be met in association with processing the work requests, and the condition can include an action for the server to take in association with processing a work request. A computing system can comprise a work requester, a server, and a set of dependency-aware queues for processing a set of work requests. A queue and/or work requests on the queues can be associated with a processing dependency and the server can process work requests enqueued to the queues in an order based on the dependencies. A work requester/server interface can comprise a dependency framework.

Abstract: A method for scheduling a computational operation based on graph data, which includes: dividing graph data into multiple partitions; scheduling the partitions to be allocated to multiple processors; successively assigning the partitions to corresponding threads of the processors for computation according to a respective degree of criticality of each partition; determining whether an idle processor exists, a processor being the idle processor when the processor includes one or more idle threads; communicating the idle processor with other processor(s) to find partition(s) to be computed and corresponding to the other processor(s); selecting and determining a partition to be computed; and migrating and binding the determined partition to be computed to thread(s) of the idle processor for processing. The present disclosure further relates to a system, a computer readable medium, and a device for scheduling a computational operation based on graph data.

Abstract: Systems and methods are disclosed for secure transmission of high-priority computer server event notifications. One method comprises obtaining a new computer server event to report; generating a first notification message pertaining to the computer server event; generating a second notification message pertaining to the computer server event and to the delivery of the first notification message; storing the first notification message; storing the second notification message; and transmitting the first notification message to a partner over a computer network.

Abstract: A system includes a computing infrastructure and an application prioritization system. The computing infrastructure includes a plurality of computing devices configured to implement computing applications. The application prioritization system receives application data associated with the computing applications. A request is received for a priority of a first computing application of the computing applications compared to a second computing application of the computing applications. The application prioritization system determines, using a feedback-based machine learning model, a first priority of the first computing application and a second priority of the second computing application and an explanation of the first and second priorities. A response is provided with an indication of the larger of the first priority and second priority and the explanation.

Abstract: A secondary pool of VMs is used to run secondary services or jobs, which may be evicted upon failure of a corresponding primary VM. Upon detection of a failure of a primary resource, the secondary services or jobs are evicted from secondary pool resources, and the secondary pool resources can be automatically allocated to the jobs of the failed primary resource. In this regard, a secondary job may be thought of as a preemptible job and comprises services or jobs that are lower priority than the service or job on the primary resource. By using computing resources in the secondary pool to run secondary or preemptible jobs, this technology makes use of what would be otherwise idle resources. This beneficially avoids having to allocate additional and separate computing resources for secondary jobs, leads to more efficient use of network resources, and reduces costs.

Abstract: A method of optimizing execution of a control function on a control system including a plurality of hardware components includes: determining a processing capability and a communication capability of each of the plurality of hardware components; generating a plurality of solutions for executing the control function using the plurality of hardware components based on a processing capability and a communication capability of each of the plurality of hardware components; scoring the plurality of generated solutions based on a desirability of each solution; selecting a solution having a highest desirability score; and controlling the control system to execute the control function based on the selected solution.

Abstract: A mainframe workflow method manages workflow tasks in a mainframe workflow management system. The method includes selecting, by a user terminal, a target mainframe computing system from a plurality of target mainframe computing systems for execution of a mainframe workflow process having a plurality of workflow tasks, and transmitting the plurality of workflow tasks to the selected target mainframe computing system over a communication network. The method also includes storing the plurality of workflow tasks, in a workflow file repository at the target mainframe computing system, and checking the plurality of workflow tasks for inter-task dependencies.

Abstract: Mechanisms are provided for intelligently identifying an execution environment to execute a computing job. An execution time of the computing job in each execution environment of a plurality of execution environments is predicted by applying a set of existing machine learning models matching execution context information and key parameters of the computing job and execution environment information of the execution environment. The predicted execution time of the machine learning models is aggregated. The aggregated predicted execution times of the computing job are summarized for the plurality of execution environments. Responsive to a selection of an execution environment from the plurality of execution environments based on the summary of the aggregated predicted execution times of the computing job, the computing job is executed in the selected execution environment. Related data during the execution of the computing job in the selected execution environment is collected.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scheduling jobs for a data backup service using backup process history and backup target entity profiles.

Abstract: The present disclosure relates to a manycore system which includes a device memory configured to store data associated with a job requested to be offloaded from a host device, and a plurality of clusters. Each of the plurality of clusters includes a program memory configured to store a program associated with the job requested to be offloaded, a plurality of cores configured to execute one or more threads associated with the job, and a management module configured to allocate one or more tasks associated with the job to the plurality of cores based on job loads of the plurality of cores, and control thread execution corresponding to the one or more allocated tasks. Each core includes thread areas configured to independently store and track an execution state of each thread executed on the core, and each thread executed on the core is independently executed using a separate thread area.

Abstract: Disclosed herein are system, method, and computer program product embodiments for a dynamic symbol-based system for objects-of-interest (OOI) video analytics detection. Some embodiments include instantiating one or more symbolic objects associated with one or more real world rules, defining an area of interest, associating one or more CV functions with the one or more symbolic objects, and identifying one or more video sources for which to apply the one or more CV functions. Some embodiments further include executing the one or more CV functions associated with the one or more symbolic objects to process the one or more video sources.

Abstract: In some examples, a system includes a kernel scheduler to schedule, for execution, threads to run in an address space of an operating system (OS) kernel according to respective priorities associated with the threads, where each thread of the threads has a user persona and a kernel persona. The kernel scheduler switches each respective thread of the threads to the kernel persona of the respective thread in response to scheduling the respective thread for execution responsive to a kernel call from the respective thread. The kernel scheduler preempts a thread in the kernel persona of the thread that is actively executing in response to an event.

Abstract: The present disclosure provides a resource configuration method, a resource obtaining method, a network device and a terminal. The resource configuration method for the network device includes: obtaining a control information about a GCL; and configuring a preconfigured resource for an air interface for a terminal in accordance with the control information.

Abstract: A processor core is configured to execute a parent task that is described by a data structure stored in a memory. A coprocessor is configured to dispatch a child task to the at least one processor core in response to the coprocessor receiving a request from the parent task concurrently with the parent task executing on the at least one processor core. In some cases, the parent task registers the child task in a task pool and the child task is a future task that is configured to monitor a completion object and enqueue another task associated with the future task in response to detecting the completion object. The future task is configured to self-enqueue by adding a continuation future task to a continuation queue for subsequent execution in response to the future task failing to detect the completion object.

Abstract: The present disclosure discloses a medical ETL task dispatching method, system and apparatus based on multiple centers. The method includes following steps: step S1: testing and verifying ETL tasks; step S2: deploying the ETL tasks to a hospital center, and dispatching the ETL tasks to a plurality of executors for execution; step S3: screening an executor set meeting resource demands of ETL tasks to be dispatched; step S4: calculating a current task load of each executor in the executor set; step S5: selecting the executor with a minimum current task load to execute the ETL tasks; and step S6: selecting, by the dispatching machine, the ETL tasks from executor active queues according to a priority for execution. The present disclosure selects the most suitable executor by analyzing a serving index as a task to be dispatched on a current dispatching machine.

Abstract: A pipeline in a controller may be configured to interface between sensors and actuators. The pipeline may elements such as drivers, filters, a combine, estimators, controllers, a mixer, and actuator controllers. The drivers may receive sensor data and pre-process the received sensor data. The filters may filter the pre-processed sensor data to generate filtered sensor data. The combine may package the filtered sensor data to generate packaged sensor data. The estimators may determine estimates of a position of a vehicle based on the packaged sensor data. The controllers may generate control signals based on the determined estimates. The mixer may modify the generated control signals based on limitations of the vehicle. The actuator controllers may generate actuator control signals based on the modified control signals to drive the actuators.

Abstract: A control device manages multiple applications by acquiring and comparing messages they transmit and receive. It includes a storage unit that prioritizes message processing across these applications and an arbitration unit that determines the sequence for encrypting these messages based on the stored priorities.

Abstract: A system prioritizes workflows based on priority levels and calculates an amount of resource consumption associated with the workflows. Each client starts a predefined time period with a certain amount of credits that indicate a degree of resource consumption. Workflows may be run with high priorities using credits. Workflows that are run with higher priorities are scheduled to run before workflows with lower priorities. A degree of resource consumption for running a workflow may be calculated based on resources consumed by the system, such as central processing unit (CPU), memory storage, network usage and elapsed time. The degree of resource consumption for running a workflow may be calculated and converted to an amount of credits and the respective amount of credits may be deducted from a credit balance associated with the client's account. The degree of resource consumption associated with a workflow may be estimated before the workflow starts running.

Abstract: Systems and methods of deploying a program to a distributed network are provided. In one exemplary embodiment, a method is performed by a node (101, 200, 300) that is associated with a set of distributed nodes (113-115, 500, 600) in a distributed system (111). Further, functions (133-135) of a program (131) are distributable among the set for execution of the program. The method includes obtaining (401a) an execution pattern (117) of the program and a sleep requirement (119-121) of at least one distributed node. The method also includes dynamically deploying (403a) the functions of the program to all or a portion of the set for execution of the program by the set based on the execution pattern of the program and the sleep requirement of the at least one distributed node.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for job management in a distributed network include a prioritizer that determines a priority level for a job and inserts the job into a priority queue based on the priority level, a scheduler that, for each element in the distributed network, requests the priorities of one or more jobs scheduled for execution, evaluates, based on the priorities of the one or more jobs scheduled for execution, the priority of a particular job with respect to the element, determines, based on the priorities, that the network element is free to perform job processes, and upon determining that a network element is free, scheduling a particular job for execution, and an executor that determines that all local and remote resources required for the scheduled job are available and executes the job according to processes defined within the distributed network.

Abstract: A computing device includes a plurality of nodes, where a first node operates in accordance with a computing device operation system (OS) and remaining nodes operate in accordance with a custom OS. The remaining nodes include a plurality of sets of processing core resources that process a plurality of sets of threads of an application. The computing device also includes a main memory divided into a computing device memory section and a custom memory section that includes portions logically allocated as a plurality of buffers. The computing device also includes a memory access control module operable to coordinate access to the plurality of buffers by at least some of the plurality of sets of threads in accordance with the custom OS. The computing device also includes disk memory and a disk memory access control module operable to coordinate access to the disk memory in accordance with the computing device OS.

Abstract: A method for determining a progress of an execution of a task, the method may include accessing only a portion of a shared task status data structure that (a) is associated with the task, wherein the task is executed by a first plurality of compute elements, and (b) comprises multiple hierarchical levels; wherein an entry of a certain hierarchical level represents an aggregate progress associated with multiple entries of the another hierarchical level; the certain hierarchical level is higher than the other hierarchical level; and determining the progress of the execution of the task based on a content of the portion.

Abstract: A pipeline in a controller may be configured to interface between sensors and actuators. The pipeline may elements such as drivers, filters, a combine, estimators, controllers, a mixer, and actuator controllers. The drivers may receive sensor data and pre-process the received sensor data. The filters may filter the pre-processed sensor data to generate filtered sensor data. The combine may package the filtered sensor data to generate packaged sensor data. The estimators may determine estimates of a position of a vehicle based on the packaged sensor data. The controllers may generate control signals based on the determined estimates. The mixer may modify the generated control signals based on limitations of the vehicle. The actuator controllers may generate actuator control signals based on the modified control signals to drive the actuators.

Abstract: Systems and methods for providing a guaranteed batch pool are described, including receiving a job request for execution on the pool of resources; determining an amount of time to be utilized for executing the job request based on available resources from the pool of resources and historical resource usage of the pool of resources; determining a resource allocation from the pool of resources, wherein the resource allocation spreads the job request over the amount of time; determining that the job request is capable of being executed for the amount of time; and executing the job request over the amount of time, according to the resource allocation.

Abstract: Apparatuses and methods can be related to placing memory in a computing system. The memory modules can be placed in memory slots to couple the memory modules to the computing system. The memory modules and/or the memory slots can have thermal qualities which can be utilized to determine which of the memory modules are placed on which of the memory slots.

Abstract: Disclosed is a method for managing a plurality of tasks of a one-off function implemented by a motor vehicle computer, the computer including a microcontroller, the microcontroller, termed a “multicore” microcontroller, including a plurality of cores, each of which is capable of processing regular functions and one-off functions, each one-off function including a plurality of tasks to be executed, each of which is identified by an identifier, the method including, during the processing of the tasks of a one-off function, each time a core of the plurality of cores is available to process a task, a step of the available core selecting, from a predetermined ordered list of identifiers of the tasks of the one-off function, the identifier of the first task which has not yet been processed by the other cores, and a step of the available core processing the task that corresponds to the selected identifier.

Abstract: Systems and methods are provided for improving autotuning procedures. For example, the system can implement a task launcher, a scheduler, and an agent to launch, schedule, and execute decomposed autotuning stages, respectively. The scheduling policy implemented by the scheduler may perform operations beyond a simple scheduling policy (e.g., a FIFO-based scheduling policy), which produces a high queuing delay. By leveraging autotuning specific domain knowledge, this may help reduce queuing delay and improve resource utilization that is otherwise found in traditional systems.

Abstract: An artificial intelligence (AI) model, using logistic regression and gradient boosting tree, may determine a priority score for a user. The priority score may be associated with a likelihood of redemption of investment funds of the user by the user. Based on the priority score for the user, a server may prioritize transmission of a communication message to the user via one of a plurality of communication channels. The communication message may describe why the user should continue with their investment funds without redemption.

Abstract: This application provides an IO request processing method, used in an external device. The external device includes a processor and a first hardware interface, and the first hardware interface is an interface that supports a PCIe protocol. The external device communicates with a physical host through the first hardware interface. The method includes: The processor synchronizes, through the first hardware interface, queue information in storage space of a virtual machine running on the physical host to storage space of the external device, where the queue information includes one or more input/output IO requests; and the processor sends the one or more IO requests to a storage server or a network server for processing. According to this application, all hardware resources of the physical host can be used to provide virtual machine services for users, thereby improving utilization of hardware resources of the physical host.

Abstract: A method comprises executing a workload acquiring algorithm at a first edge node of a plurality of edge nodes to pull at least one workload of a plurality of workloads from a workload queue corresponding to a second edge node of the plurality of edge nodes. In one example, the first edge node may be a component of a first edge location, and the method may further comprise providing the first edge node with access to one or more workloads from one or more workload queues corresponding to one or more edge nodes from a second edge location different from the first edge location.

Abstract: Embodiments relate to diagnosis and recovery of cloud based systems. From an incident ticket, a dynamic diagnostics graph is generated visualizing a hierarchy (ancestor, child) of diagnostic jobs investigating the functioning cloud system. By indicating and checking job statuses, child jobs dependent on a skipped or failed job can be skipped according to a dynamic pruning technique—thereby trimming an entire branch. And, by running separate groups of diagnostic jobs in parallel across different nodes, the diagnostic process can be finished rapidly and efficiently. A diagnostic report includes the dynamic diagnostics graph. For system recovery, the dynamic diagnostic graph is analyzed to automatically provide one or more appropriate Recommended Actions (RAs) resolving cloud system problem(s) revealed by diagnostic efforts. Those appropriate RAs may be provided by performing machine learning (e.g., referencing a neural network) with a model trained from historical cloud diagnostic and recovery activity.

Abstract: Systems and methods for split rendering of Network Based Media Processing (NBMP) are provided. A method includes deriving a media processing workflow; and obtaining connectivity information of at least one media processing entity (MPE) from among a plurality of MPEs, wherein the connectivity information describes a connection characteristic between at least two MPEs from among the plurality of MPEs; and assigning a plurality of workflow tasks of the media processing workflow among the plurality of MPEs based on the connectivity information.

Abstract: A module manages usage of a memory in a computer by scheduling data processing tasks. The module determines whether a memory associated with a computer is available for performing a data processing task. In response to determining that the memory is not available for performing the data processing task, the module generates a factory object for the data processing task. The factory object specifies instructions to produce the data processing task. After the factory object is generated, the module receives a request to perform the data processing task. The module produces the data processing task by using the factory object in response to the request and determine again whether the memory is available for performing the data processing task. In response to determining that the memory is now available for performing the data processing task, the module performs the data processing task by using the memory.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving a data process that includes a plurality of sub-processes. A unique subset of the sub-processes is assigned to each of: a managing thread, and at least one other thread. Moreover, performance characteristics of each of the threads is evaluated while the respective subsets of sub-processes are being performed, and a determination is made as to whether the performance characteristics of each of the threads are substantially equal to the performance characteristics of each of the other threads. In response to determining that performance characteristics of each of the threads are not substantially equal, the subsets of the sub-processes are dynamically adjusted such that the performance characteristics of each of the threads become more equal. Moreover, the adjusted subsets of the sub-processes are reassigned to each of the managing thread and at least one other thread.

Abstract: A method, performed by a network entity, of executing a software package in a wireless communication system, is provided.

Abstract: A memory controller circuit is disclosed which is coupleable to a first memory circuit, such as DRAM, and includes: a first memory control circuit to read from or write to the first memory circuit; a second memory circuit, such as SRAM; a second memory control circuit adapted to read from the second memory circuit in response to a read request when the requested data is stored in the second memory circuit, and otherwise to transfer the read request to the first memory control circuit; predetermined atomic operations circuitry; and programmable atomic operations circuitry adapted to perform at least one programmable atomic operation. The second memory control circuit also transfers a received programmable atomic operation request to the programmable atomic operations circuitry and sets a hazard bit for a cache line of the second memory circuit.

Abstract: A base station in a wireless communication system is provided. Each base station for wireless communication comprises: a communication module; and a processor. The processor is configured to determine the number of dynamic slot format information (SFI) bits based on a maximum value of a slot format combination index which can be indicated by dynamic SFI transmitted to a terminal, and monitor a physical downlink control channel (PDCCH) including the dynamic SFI based on the number of the dynamic SFI bits. The slot format combination index identifies a slot format combination configured for the terminal. The slot format combination indicates a type of a symbol included in one or more slots, and the type of the symbol is one among a downlink symbol, an uplink symbol, and a flexible symbol.

Abstract: In one set of embodiments, an operating system (OS) kernel of a computer system can receive an invocation of a system call by a user program running on the computer system. The OS kernel can further fetch a plurality of subsequent instructions that will be executed by the user program after the invocation of the system call and decode the plurality of subsequent instructions into a plurality of decoded instructions. The OS kernel can then analyze whether the plurality of decoded instructions include an additional system call invocation and whether other decoded instructions that appear between the invocation of the system call and the additional system call invocation are viable for emulation by the OS kernel.

Abstract: Methods and systems for generating common priority information for a plurality of requestors in a computing system that share a plurality of computing resources for use in a next cycle to arbitrate between the plurality of requestors, include generating, for each resource, priority information for the next cycle based on an arbitration scheme; generating, for each resource, relevant priority information for the next cycle based on the priority information for the next cycle for that resource, the relevant priority information for a resource being the priority information that relates to requestors that requested access to the resource in the current cycle and were not granted access to the resource in the current cycle; and combining the relevant priority information for the next cycle for each resource to generate the common priority information for the next cycle.

Abstract: A quantum-mechanics station (?-station) and a cloud-based server cooperate to provide quantum mechanics as a service (?aaS) including real-time, exclusive, interactive sessions. The ?-station serves as a system for implementing “recipes” for producing, manipulating, and/or using quantum-state carriers, e.g., rubidium 87 atoms. The cloud-based server acts as an interface between the station (or stations) and authorized users of account holders. To this end, the server hosts an account manager and a session manager. The account manager manages accounts and associated account-based and user-specific permissions that define what actions any given authorized user for an account may perform with respect to a ?-station. The session manager controls (e.g., in real-time) interactions between a user and a ?-station, some interactions allowing a user to select a recipe based on wavefunction characterizations returned earlier in the same session.

Abstract: Methods, systems, and devices for device reset alert mechanism are described. The memory system may identify a fault condition associated with resetting the memory system and set, in a register associated with event alerts of the memory system, a first indication for a reset of the memory system. In some cases, the memory system may transmit a message that includes a second indication that the register associated with event alerts of the memory system has been changed based on setting the register. The memory system may reset one or more components of the memory system based on the first indication and the second indication.

Abstract: Systems, computer program products, and methods are described herein for proactive network infrastructure component monitoring and replacement. The present invention is configured to transmitting instructions to display a manager input portal via a graphical display of a user device; receiving input via the graphical display of the user device for one or more network components or constraint variables; initiating a logic algorithm to determine the effects of the one or more network components or constraint variables on an assignment list; generating an updated assignment list and analyze the updated assignment list in comparison with one or more prior versions to determine one or more changes; generating a link between the one or more changes and the received input; and using a machine learning algorithm, forecasting one or more additional changes in order to generate an optimized recommendation for the updated assignment list.

Abstract: In one embodiment, an in-network compute resource assignment system includes a network device to receive a request to select resources to perform a processing job, wherein the request includes at least one resource requirement of the processing job, and end point devices assigned to perform the processing job, a memory to store a state of in-network compute-resources indicating resource usage of the in-network compute-resources by other processing jobs, and a processor to manage the stored state, and responsively to receiving the request, selecting ones of the in-network compute-resources to perform the processing job based on: (a) a network topology of a network including the in-network compute-resources; (b) the state of the in-network compute-resources; and (c) the at least one resource requirement of the processing job.

Abstract: Methods, devices and systems are disclosed for inter-app communications between software applications on a mobile communications device. In one aspect, a computer-readable medium on a mobile computing device comprising an inter-application communication data structure to facilitate transitioning and distributing data between software applications in a shared app group for an operating system of the mobile computing device includes a scheme field of the data structure providing a scheme id associated with a target software app to transition to from a source software app, wherein the scheme id is listed on a scheme list stored with the source software app; and a payload field of the data structure providing data and/or an identification where to access data in a shared file system accessible to the software applications in the shared app group, wherein the payload field is encrypted.

Abstract: According to various embodiments, a method for detecting security vulnerabilities in at least one of cyber-physical systems (CPSs) and Internet of Things (IoT) devices is disclosed. The method includes constructing an attack directed acyclic graph (DAG) from a plurality of regular expressions, where each regular expression corresponds to control-data flow for a known CPS/IoT attack. The method further includes performing a linear search on the attack DAG to determine unexploited CPS/IoT attack vectors, where a path in the attack DAG that does not represent a known CPS/IoT attack vector represents an unexploited CPS/IoT attack vector. The method also includes applying a trained machine learning module to the attack DAG to predict new CPS/IoT vulnerability exploits. The method further includes constructing a defense DAG configured to protect against the known CPS/IoT attacks, the unexploited CPS/IoT attacks, and the new CPS/IoT vulnerability exploits.