One example method occurs at a test system implemented using at least one processor, the method comprising: sending, via an application programming interface (API) and to a first traffic generator, a first instruction for setting a rate of background test packets sent to or via a system under test (SUT) for a test session; sending the background test packets to or via the SUT during the test session; receiving, from at least one feedback entity, feedback indicating at least one traffic metric associated with the background test packets sent to or via the SUT during the test session; generating, using the feedback, a second instruction for adjusting the rate of background test packets sent during the test session; and providing, via the API and to the first traffic generator, the second instruction for adjusting the rate of background test packets sent to or via the SUT during the test session.

One example method occurs at a test system implemented using at least one processor, the method comprising: sending, via an application programming interface (API) and to a first traffic generator, a first instruction for setting a rate of background test packets sent to or via a system under test (SUT) for a test session; sending the background test packets to or via the SUT during the test session; receiving, from at least one feedback entity, feedback indicating at least one traffic metric associated with the background test packets sent to or via the SUT during the test session; generating, using the feedback, a second instruction for adjusting the rate of background test packets sent during the test session; and providing, via the API and to the first traffic generator, the second instruction for adjusting the rate of background test packets sent to or via the SUT during the test session.

A system comprises a seed node, one or more compute servers and a controller server. The seed node generates initial conditions for a computational process representing an environment having one or more layers with agents. Each compute server executes tasks to generate a portion of the environment. The controller server receives initial conditions of the environment from the seed node; determines a distribution of tasks for the computational process among the compute servers; and sends instructions to each compute server for execution of tasks determined for the respective compute server. The controller server measures an execution time period for the computational process in units of discrete time frames, and sends an update or synchronization instructions, or both, to one or more compute servers in each time frame.

The present application relates generally to Volt-VAR optimization for power distribution systems having advanced metering infrastructure (AMI). Distributed energy resources (DER) such as photovoltaic arrays are becoming prevalent in distribution systems. These DER systems inject power into the distribution system which can cause unfavorable changes, such as a rise in voltage across the feeder lines of the distribution system. Existing control proposals suffer from a number of shortcomings, drawbacks and disadvantages. In some instances, traditional controllers for distribution systems with DER systems may require information related to the arrangement of the distribution system which is unknown and cannot be provided by the advanced metering infrastructure. There remains a significant need for the apparatuses, methods, systems and techniques disclosed herein.

The present application relates generally to Volt-VAR optimization for power distribution systems having advanced metering infrastructure (AMI). Distributed energy resources (DER) such as photovoltaic arrays are becoming prevalent in distribution systems. These DER systems inject power into the distribution system which can cause unfavorable changes, such as a rise in voltage across the feeder lines of the distribution system. Existing control proposals stiffer from a number of shortcomings, drawbacks and disadvantages. In some instances, traditional controllers for distribution systems with DER systems may require information related to the arrangement of the distribution system which is unknown and cannot be provided by the advanced metering infrastructure. There remains a significant need for the apparatuses, methods, systems and techniques disclosed herein.