Apparatus and associated methods relate to selection of an operating baud rate for a building automation system that communicates over a Master-Slave Token-Passing (MS/TP) BACnet. A server (or router or gateway) connected to the MS/TP BACnet is programmed to iteratively select operating baud rates from a series of available operating baud rates. Each iteration, the server broadcasts a frame indicating baud rate selection to a plurality of building automation devices connected to a MS/TP BACnet. Each of the plurality of building automation devices connected to the MS/TP BACnet then iteratively sets its baud rate so as to match the baud rate selected by the server. The server monitors communications conducted over the MS/TP BACnet so as to determine reliability or unreliability of the communications conducted over the MS/TP BACnet using the baud rates iteratively selected. A highest reliable baud rate is then used by the building automation system.

A priority control apparatus includes: load information acquisition part which acquires communication load information per priority at relay apparatus that controls allocation of communication resources relative to individual communication depending on a priority that is set for the individual communication between two or more communication apparatuses; communication quality acquisition part which acquires communication quality as to control target communication; and priority control part which calculates a first priority, with which communication quality as to the control target communication can satisfy a predetermined condition, by using a mathematical model that indicates a relationship between a piece of communication load information before a priority as to the control target communication is set as the first priority and a communication quality when the priority as to the control target communication concerned is set as the first priority, and which sets the calculated first priority as the priority of the control target communication concerned.

Methods, systems, and computer program products for service-to-service scheduling in container orchestrators are provided herein. A computer-implemented method includes reserving, by a network orchestrator, network resources requested between a plurality of services, wherein each of the services is implemented as one or more replicas running on a set of nodes of a cluster, managed by the network orchestrator, that use the network resources to serve incoming requests to the plurality services; monitoring utilization of the network resources; and scheduling, by the network orchestrator based on the monitoring, one or more new replicas of the plurality of services and the incoming requests to the plurality of services in a collaborative manner to increase at least one network performance characteristic.

Device group partitions and a settlement platform are provided. In some embodiments, device group partitions (e.g., partitions of devices based on associated device groups) are provided. In some embodiments, a settlement platform service is provided. In some embodiments, a settlement platform service is provided for partitioned devices. In some embodiments, collecting device generated service usage information for one or more devices in wireless communication on a wireless network; and aggregating the device generated service usage information for a settlement platform for the one or more devices in wireless communication on the wireless network is provided. In some embodiments, a settlement platform implements a service billing allocation and/or a service/transactional revenue share among one or more partners. In some embodiments, service usage information includes micro-CDRs, which are used for CDR mediation or reconciliation that provides for service usage accounting on any device activity that is desired. In some embodiments, each device activity that is desired to be associated with a billing event is assigned a micro-CDR transaction code, and a service processor of the device is programmed to account for that activity associated with that transaction code. In some embodiments, a service processor executing on a wireless communications device periodically reports (e.g., during each heartbeat or based on any other periodic, push, and/or pull communication technique(s)) micro-CDR usage measures to, for example, a service controller or some other network element for CDR mediation or reconciliation.

A method for dynamically allocating server resources includes receiving a request from a client system, wherein the request comprises a request for a first set of streaming data, providing from the server to the client system a first portion of streaming data from the first set of streaming data, wherein the first portion is associated with a first quality of service level, receiving user activity data from the client system for the first portion of the streaming data, determining a second quality of service level for a second portion of the streaming data from the first set of streaming data, providing from the server to the client system the second portion of streaming data from the first set of streaming data, wherein the second portion provided with the second quality of service level, and wherein the first quality of service level is different from the second quality of service level.

Systems are methods are described for predicting and forecasting a resource utilization on network device, particularly for handling multicast flows, by monitoring past resource consumption patterns. A system can include a plurality of multicast clients coupled to a network; and a network device coupled to the network. The network device may be a switch or a router that directs multicast traffic to the plurality of multicast clients. The network device can include a flow prediction controller that determines one or more real-time predictions relating to a demand of the network based on an analysis of an artificial intelligence (AI) forecasting model, such as an Autoregressive Integrated Moving Average (ARIMA) model. Also, the network device can include a resource optimizer that performs a resource management action that optimizes the resources of the network device based on the one or more real-time predictions of the demand of the network and a policy.

Apparatuses, methods, and systems are disclosed for modifying a data connection. One apparatus (500) includes a processor (505), a first interface supporting (705) a first data connection with a 5G core network over a first access and a second interface that communicates with a UE over a second access. The processor (505) receives (710) a request to establish a second data connection with the UE and determines (715) whether the second data connection can be mapped into one of a plurality of QoS flows established over the first data connection. The processor (505) sends (720) a request to establish a new QoS flow over the first data connection upon determining that the second data connection cannot be mapped into an existing QoS flow of the first data connection and relays (725) traffic between the second data connection and the new QoS flow over the first data connection.

Some embodiments provide a method that assigns, at a VPN client, a QoS class to each path of multiple paths based on performance metrics for paths. The paths are available for use by a VPN client to reach a VPN server. The method identifies a QoS class for a packet. The method selects a path based on the identified QoS class of the packet and the QoS class assigned to each path. The method transmits the packet using the selected path.

Cloud-based computing systems, although claimed to have virtually unlimited resources, could get oversubscribed due to budget constraints of cloud users. The disclosed invention proposes a mechanism to identify various types of “mergeable” tasks. The system also determines when it is appropriate to aggregate tasks and how to allocate them so that the QoS of other tasks is not affected. Experimental results under real-world workload settings show that the disclosed system can improve robustness of the system in the face of oversubscription and also saves the overall time of using cloud services by more than 14%.

Various embodiments are directed to techniques for dynamically adjusting a maximum rate of throughput for accessing data stored within a volume of storage space of a storage cluster system based on the amount of that data that is stored within that volume. An apparatus includes an access component to monitor an amount of client data stored within a volume defined within a storage device coupled to a first node, and to perform a data access command received from a client device via a network to alter the client data stored within the volume; and a policy component to limit a rate of throughput at which at least the client data within the volume is exchanged as part of performance of the data access command to a maximum rate of throughput, and to calculate the maximum rate of throughput based on the stored amount.