A cloud management server and method for performing automatic placement of clients in a distributed computer system uses a list of compatible clusters to select an affinity cluster to place the clients associated with an affinity constraint. As part of the placement method, a cluster that cannot satisfy any anti-affinity constraint associated with the clients and the affinity constrain is removed from the list of compatible clusters. After the affinity cluster has been selected, at least one cluster in the distributed computer system is also selected to place clients associated with an anti-affinity constraint.

A cloud management server and method for performing automatic placement of clients in a distributed computer system uses a list of compatible clusters to select an affinity cluster to place the clients associated with an affinity constraint. As part of the placement method, a cluster that cannot satisfy any anti-affinity constraint associated with the clients and the affinity constrain is removed from the list of compatible clusters. After the affinity cluster has been selected, at least one cluster in the distributed computer system is also selected to place clients associated with an anti-affinity constraint.

The disclosed embodiments provide a method and system for processing network data. During operation, the system obtains, at a remote capture agent, configuration information for the remote capture agent from a configuration server over a network. Next, the system uses the configuration information to configure the generation of event data from network data obtained from network packets at the remote capture agent. The system then uses the configuration information to configure transformation of the event data or the network data into transformed event data at the remote capture agent.

Methods for balancing storage data traffic in a system in which at least one computing device (server) coupled to a converged network accesses at least one storage device coupled (by at least one adapter) to the network, systems configured to perform such methods, and devices configured to implement such methods or for use in such systems. Typically, the system includes servers and adapters, and server agents implemented on the servers and adapter agents implemented on the adapters are configured to detect and respond to imbalances in storage and data traffic in the network, and to redirect the storage data traffic to reduce the imbalances and, thereby to improve the overall network performance (for both data communications and storage traffic). Typically, each agent operates autonomously (except in that an adapter agent may respond to a request or notification from a server agent), and no central computer or manager directs operation of the agents.

The present disclosure relates to an apparatus and method of altruistic scheduling based on reinforcement learning. An altruistic scheduling apparatus according to an embodiment of the present disclosure includes: an external scheduling agent for determining a basic resource share for each process based on information of a resource management system; an internal scheduling agent for determining a basic resource allocation schedule for each process based on information including the basic resource share and a resource leftover based on the basic resource allocation schedule; and a leftover scheduling agent for determining a leftover resource allocation schedule based on information including the resource leftover. According to an embodiment of the present disclosure, it may be expected that reinforcement learning will not only mitigate the diminution of fairness of an altruistic scheduler but also further improve other performance indicators such as completion time and efficiency.

The present disclosure, relating to the technical field of communications, provides a management method for a home network device and a network management system. The method includes that: a home gateway acquires home terminal device information in a home network; the home gateway sends the home terminal device information to a home sub-cloud which corresponds to the home network and is independent from other home sub-clouds on a cloud management platform to store.

Methods, systems, and devices are described for orchestrating server management in a modern IT network. The described techniques may be implemented to manage any number of networked severs, whether local, remote, or both. Server orchestration may leverage a central, cloud-based management system and/or one or more autonomous agents installed on servers with the network. The autonomous agents may each be registered with the supervisory server and may have awareness of one another.

Methods, systems, and devices are described for orchestrating server management in a modern IT network. The described techniques may be implemented to manage any number of networked severs, whether local, remote, or both. Server orchestration may leverage a central, cloud-based management system and/or one or more autonomous agents installed on servers with the network. The autonomous agents may each be registered with the supervisory server and may have awareness of one another.

Various embodiments are generally directed to techniques for network strengthening, such as by detecting issues with one or more network components and reconfiguring one or more upstream or downstream network components to preempt issues with the one or more upstream or downstream network components, for instance. Some embodiments are particularly directed to a tool (e.g., strengthening agent) that implements pre-scripted or dynamic hardening of up and downstream dependencies of a network component in response to an issue identified with the network component. In many embodiments, up and downstream components of a network component may be reconfigured while the issue with the network component is being addressed to preempt issues with the up and downstream components.

Various embodiments are generally directed to techniques for network strengthening, such as by detecting issues with one or more network components and reconfiguring one or more upstream or downstream network components to preempt issues with the one or more upstream or downstream network components, for instance. Some embodiments are particularly directed to a tool (e.g., strengthening agent) that implements pre-scripted or dynamic hardening of up and downstream dependencies of a network component in response to an issue identified with the network component. In many embodiments, up and downstream components of a network component may be reconfigured while the issue with the network component is being addressed to preempt issues with the up and downstream components.