Abstract: A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.

Abstract: A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.

Abstract: A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.

Abstract: A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.

Abstract: A method and apparatus in a distributed data processing system for selecting configuration information for a client in the distributed data processing system. A request is received at a server from the client for configuration information. A subnet for the client is identified using the configuration information. A set of identification tokens is identified from the request. A plurality of containers in a hierarchical structure is traversed using the subnet and identification tokens to identify selected containers within the plurality of containers matching the subnet and the identification tokens. The identified containers are selected in an order the preserves preference as determined by their arrangement in the hierarchical structure and by the data that each contains. Configuration information is obtained from selected containers within the plurality of containers to form selected configuration information. The selected configuration information is sent to the client.

Abstract: Network input processing is distributed to multiple CPUs on multiprocessor systems to improve network throughput and take advantage of MP scalability. Packets are received by the network adapter and are distributed to N receive buffer pools set up by the device driver, based on N CPUs being available for input processing of packets. Each receive buffer pool has an associated CPU. Packets are direct memory accessed to one of the N receive buffer pools by using a hashing function, which is based on the source MAC address, source IP address, or the packet's source and destination TCP port numbers, or all or a combination of the foregoing. The hashing mechanism ensures that the sequence of packets within a given communication session will be preserved. Distribution is effected by the network adapter, which sends an interrupt to the CPU corresponding to the receive buffer pool, subsequent to the packet being DMAed into the buffer pool.