Abstract: An electro-optical (EO) modulator that includes (i) a substrate. (ii) a modulation unit that includes an EO modulation layer and a modulation zone waveguide that is optically coupled to the EO modulation layer and is partially surrounded by one or more gaps. (iii) radio-frequency electrodes that are electromagnetically coupled to the EO modulation layer. (iv) an input waveguide that is configured to guide light towards the modulation unit; and (v) an output waveguide that is configured to receive modulated light from the modulation unit.

Abstract: There may be provided a silicon photonics unit that may include an input waveguide that is configured to convey an input optical signal; a distribution unit (DU) that comprises a DU input port, a first DU output port, a second DU output port and a distribution core; wherein the distribution core is configured to receive the input optical signal, split the input optical signal to a first optical signal and a second optical signal, provide the first optical signal to the first DU output port and provide the second optical signal to the second DU output port; a photodetector (PD) that comprises a PD's first optical input port, a PD's second optical input port, and a PD's electrical output port; wherein the PD is configured to output, via the PD output port, a PD output signal indicative of the first optical signal and the second optical signal; a first optical path that comprises a first waveguide and is configured to convey the first optical signal to the PD's first optical input port; and a second optical path

Abstract: A millimeter scale weak grating coupler comprising a silicon waveguide having bars of overlay material of length (a) disposed periodically at a period (?) adjacent the silicon waveguide whereby a uniform grating output is achieved.

Abstract: A method of forming an emitting array of waveguides, comprising providing a plurality of waveguides that exhibit different propagation constants so as to ensure that nearby waveguides do not couple evenly over parallel propagation lengths by varying a length in one or more dimensions of respective waveguides, whereby the respective waveguides are phase mismatched with at least their nearest neighbor.

Abstract: A method of forming an emitting array of waveguides, comprising providing a plurality of waveguides that exhibit different propagation constants so as to ensure that nearby waveguides do not couple evenly over parallel propagation lengths by varying a length in one or more dimensions of respective waveguides, whereby the respective waveguides are phasemismatched with at least their nearest neighbor.

Abstract: A millimeter scale weak grating coupler comprising a silicon waveguide having bars of overlay material of length (a) disposed periodically at a period (?) adjacent the silicon waveguide whereby a uniform grating output is achieved.

Abstract: The disclosure is related to balancing resources between pools of servers, e.g., by moving servers from a first pool of servers to a second pool of servers. The first pool executes a first version of an application, e.g., a desktop version, and the second pool executes a second version of the application, e.g., a mobile version. The technology moves a number of servers from an “OK” pool to a “not OK” pool. A “not OK” pool is a pool whose performance metric, e.g., response latency of a server, does not satisfy a criterion, and an “OK” pool is a pool whose performance metric satisfies the criterion even if the number of servers are removed from the pool. The number of servers to be moved is determined as a function of the increase in load which the pool can withstand by remaining in OK state even after the servers are removed.

Abstract: Embodiments provide a system including a plurality of objects and a monitoring module coupled to the objects. The monitoring module is configured to determine a health value of each object. The system also includes an optimization module coupled to the monitoring module. The optimization module is configured to receive a user input indicating a utility to be increased within the system, wherein the utility is based on the health value of each object. The optimization module is also configured to identify a plurality of available actions to be performed on each object. Each available action is associated with at least one expected consequence. The optimization module is also configured to calculate an expected utility of each action based on an effect of each expected consequence on the health value of each object and select, from the available actions, an action based on the expected utility for the system.

Abstract: In a computer-implemented method for scheduling a plan of operations in a datacenter selection of a target from a plurality of targets in the datacenter is enabled for scheduling operations on the selected target. Selection of one or more bundles is enabled, wherein the plan of operations on the selected target are based on the one or more bundles. Dependency relationships between the selected target and other targets in the plurality of targets are determined based on the selection of one or more bundles. The plan of operations on the selected target is scheduled.

Abstract: The disclosure is related to balancing resources between pools of servers, e.g., by moving servers from a first pool of servers to a second pool of servers. The first pool executes a first version of an application, e.g., a desktop version, and the second pool executes a second version of the application, e.g., a mobile version. The technology moves a number of servers from an “OK” pool to a “not OK” pool. A “not OK” pool is a pool whose performance metric, e.g., response latency of a server, does not satisfy a criterion, and an “OK” pool is a pool whose performance metric satisfies the criterion even if the number of servers are removed from the pool. The number of servers to be moved is determined as a function of the increase in load which the pool can withstand by remaining in OK state even after the servers are removed.

Abstract: Combining profiles based on priorities associated therewith to create an effective profile are provided. A plurality of profiles defining one or more rules that are applicable to a functional computing object are identified. A priority corresponding to each applicable profile is determined. The applicable profiles are combined by the computing device based on the corresponding priorities to create an effective profile that includes no conflicting rules.

Abstract: In a computer-implemented method for scheduling a plan of operations in a datacenter selection of a target from a plurality of targets in the datacenter is enabled for scheduling operations on the selected target. Selection of one or more bundles is enabled, wherein the plan of operations on the selected target are based on the one or more bundles. Dependency relationships between the selected target and other targets in the plurality of targets are determined based on the selection of one or more bundles. The plan of operations on the selected target is scheduled.

Abstract: In a computer-implemented method for a unified graphical user interface for displaying a plan of operations in a datacenter metadata is accessed from a plurality of disparate software bundles for updating targets in a datacenter. A unified visualization of a plan of operations on the targets is displayed via a unified graphical user interface based on the accessed metadata, wherein the unified graphical user interface displays the plan of operations with a common look and feel.

Abstract: In a computer-implemented method for a unified graphical user interface for displaying a plan of operations in a datacenter metadata is accessed from a plurality of disparate software bundles for updating targets in a datacenter. A unified visualization of a plan of operations on the targets is displayed via a unified graphical user interface based on the accessed metadata, wherein the unified graphical user interface displays the plan of operations with a common look and feel.

Abstract: The current document discloses an automated method and system for inferring the logical rules underlying the configuration and versioning state of the components and subcomponents of a complex system, including data centers and other complex computational environments. The methods and systems employ a database of configuration information and construct an initial set of logical rules, or hypotheses, regarding system configuration. Then, using simulated annealing and a variant of genetic programming, the methods and systems disclosed in the current document carry out a search through the hypothesis state space for the system under several constrains in order to find one or more hypotheses that best explain the configuration and, when available, configuration history. The constraints include minimization of the complexity of the hypotheses and maximizing the accuracy by which the hypotheses predict observed configuration and configuration history.

Abstract: A method and program product are provided for implementing object state changes in a data network system that includes at least one application having a plurality of objects. Each object is capable of being in of a plurality of different object states. The method comprises utilizing a network monitor to identify potential object state anomaly candidates from among the plurality of objects and utilizing object measurements taken during a predetermined time segment to determine if the current object state of a potential object state anomaly candidate should change from the current object state to an updated object state.

Abstract: The current document discloses an automated method and system for inferring the logical rules underlying the configuration and versioning state of the components and subcomponents of a complex system, including data centers and other complex computational environments. The methods and systems employ a database of configuration information and construct an initial set of logical rules, or hypotheses, regarding system configuration. Then, using simulated annealing and a variant of genetic programming, the methods and systems disclosed in the current document carry out a search through the hypothesis state space for the system under several constrains in order to find one or more hypotheses that best explain the configuration and, when available, configuration history. The constraints include minimization of the complexity of the hypotheses and maximizing the accuracy by which the hypotheses predict observed configuration and configuration history.

Abstract: Combining profiles based on priorities associated therewith to create an effective profile are provided. A plurality of profiles defining one or more rules that are applicable to a functional computing object are identified. A priority corresponding to each applicable profile is determined. The applicable profiles are combined by the computing device based on the corresponding priorities to create an effective profile that includes no conflicting rules.

Abstract: Combining profiles based on priorities associated therewith to create an effective profile are provided. A plurality of profiles defining one or more rules that are applicable to a functional computing object are identified. A priority corresponding to each applicable profile is determined. The applicable profiles are combined by the computing device based on the corresponding priorities to create an effective profile that includes no conflicting rules.

Abstract: Embodiments provide a system including a plurality of objects and a monitoring module coupled to the objects. The monitoring module is configured to determine a health value of each object. The system also includes an optimization module coupled to the monitoring module. The optimization module is configured to receive a user input indicating a utility to be increased within the system, wherein the utility is based on the health value of each object. The optimization module is also configured to identify a plurality of available actions to be performed on each object. Each available action is associated with at least one expected consequence. The optimization module is also configured to calculate an expected utility of each action based on an effect of each expected consequence on the health value of each object and select, from the available actions, an action based on the expected utility for the system.