Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: A method includes receiving user data packets from customer premises equipment (CPE) in communication with a network terminal over a communication link and enabling a network terminal-side loopback mode to establish a closed traffic test loop across the communication link between the network terminal and the CPE. The received user data packets indicate that a CPE-side loopback mode is enabled. The method also includes injecting a number of data bits into the closed traffic test loop until a saturation threshold of the communication link is satisfied, and when the number of data bits injected into the closed traffic test loop satisfies the saturation threshold, determining a packet error-rate of the number of data bits circulating in the closed traffic test loop. After determining the packet error-rate, the method also includes removing the closed traffic test loop across the communication link between the network terminal and the CPE.

Abstract: A method includes receiving user data packets from customer premises equipment (CPE) in communication with a network terminal over a communication link and enabling a network terminal-side loopback mode to establish a closed traffic test loop across the communication link between the network terminal and the CPE. The received user data packets indicate that a CPE-side loopback mode is enabled. The method also includes injecting a number of data bits into the closed traffic test loop until a saturation threshold of the communication link is satisfied, and when the number of data bits injected into the closed traffic test loop satisfies the saturation threshold, determining a packet error-rate of the number of data bits circulating in the closed traffic test loop. After determining the packet error-rate, the method also includes removing the closed traffic test loop across the communication link between the network terminal and the CPE.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified rules to events in an action log framework (ALF) stream is disclosed. More specifically, collaboration environments can include features or mechanisms that allow end-users or collaborators to perform a variety of actions such as, for example, file uploads and previews, or collaboration operations such as, for example, task assignment and comments. These actions can be captured or logged by an action log framework and, as described herein, automatically translated into one or more jobs by applying customizable user-specified rules.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified metadata rules to metadata events. More specifically, the scalable architecture described herein uses metadata to drive automations and/or polices in a cloud-based environment. In one embodiment, the architecture integrates a metadata service with an event-based automation engine to automatically trigger polices and/or automations based on metadata and/or changes in metadata changes. The metadata service can include customizable and/or pre-build metadata templates which can be used to automatically apply a metadata framework (e.g., particular fields) to files based on, for example, the upload or placement of a particular file in a particular folder. The architecture also provides for advanced metadata searching and data classification.

Abstract: Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified rules to events in an action log framework (ALF) stream is disclosed. More specifically, collaboration environments can include features or mechanisms that allow end-users or collaborators to perform a variety of actions such as, for example, file uploads and previews, or collaboration operations such as, for example, task assignment and comments. These actions can be captured or logged by an action log framework and, as described herein, automatically translated into one or more jobs by applying customizable user-specified rules.

Abstract: A storage of nodes of hierarchically structured data uses logical node identifiers to reference the nodes stored within and across record data structures. A node identifier index is used to map each logical node identifier to a record identifier for the record that contains the node. When a sub-tree is stored in a separate record, a proxy node is used to represent the sub-tree in the parent record. The mapping in the node identifier index reflects the storage of the sub-tree nodes in the separate record. Since the references between the records are through logical node identifiers, there is no limitation to the moving of records across pages, as long as the indices are updated or rebuilt to maintain synchronization with the resulting data pages. This approach is highly scalable and has a much smaller storage consumption than approaches that use explicit references between nodes.

Abstract: A micro-electro-mechanical device including a first substrate; a first contact disposed on a first surface of the substrate; a piezoelectric actuator disposed over the first surface of the substrate; a second contact coupled to the actuator and disposed in proximity to the first contact; a gap control mechanism disposed between the substrate and the actuator for limiting movement of the first contact relative to the second contact. In the exemplary embodiment, the gap control mechanism is a gap control stop constructed of dielectric material. In practice, plural stops are used. In the exemplary embodiment, plural thermosonic bonds are used to connect the actuator to the first substrate. A second substrate is disposed over the piezo-electric actuator. The second substrate has wells over the bonds to facilitate application of a bonding tool to the bonds. The gap control mechanism provides consistent height control between a flipped chip and its base substrate without exposing the assembly to high temperatures.

Abstract: A variable-length binary string is utilized to encode node identifiers in a tree for an XML document object model. A general prefix encoding scheme is followed; a node identifier is generated by the concatenation of encodings at each level of a tree along a path from a root node to another particular node. Arbitrary insertions are supported without change to existing node identifier encodings. In addition, the method provides for document order when unsigned binary string comparison is used to compare encoded node identifiers. In support of sub-document concurrency control, prefix encoding provides a way to derive ancestor-descendant relationships among nodes in a tree. Lastly, the encoding method provides a natural pre-order clustering sequence, also known as depth-first clustering. If a prefix is applied to an encoding with a level number, starting with zero at the root, width-first clustering will result. A mixed clustering can also be supported.