Abstract: Systems and methods are described for allocating resources in a cloud computing environment. The method includes receiving a computing request, the request for use of at least one virtual machine and a portion of memory. In response to the request, a plurality of hosts is identified and a cost function is formulated using at least a portion of those hosts. Based on the cost function, at least one host that is capable of hosting the virtual machine and memory is selected.

Abstract: A method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchically arranged data center, clustering nodes based on groups of capabilities information, generating a histogram that represents individual node clusters, and sending the histogram to a next higher level in the hierarchically arranged data center. Relative rankings of capabilities may be used to order a sequence of clustering operations.

Abstract: An example method for leveraging hardware accelerators for scalable distributed stream processing in a network environment is provided and includes allocating a plurality of hardware accelerators to a corresponding plurality of bolts of a distributed stream in a network, facilitating a handshake between the hardware accelerators and the corresponding bolts to allow the hardware accelerators to execute respective processing logic according to the corresponding bolts, and performing elastic allocation of hardware accelerators and load balancing of stream processing in the network. The distributed stream comprises a topology of at least one spout and the plurality of bolts. In specific embodiments, the allocating includes receiving capability information from the bolts and the hardware accelerators, and mapping the hardware accelerators to the bolts based on the capability information.

Abstract: Techniques are provided to generate and store a network graph database comprising information that indicates a service node topology, and virtual or physical network services available at each node in a network. A service request is received for services to be performed on packets traversing the network between at least first and second endpoints. A subset of the network graph database is determined that can provide the services requested in the service request. A service chain and service chain identifier is generated for the service based on the network graph database subset. A flow path is established through the service chain by flow programming network paths between the first and second endpoints using the service chain identifier.

Abstract: In one embodiment, a processor can receive data representing a view reflected by a mirror of a plurality of mirrors. The plurality of mirrors may be configured in a space to reflect a plurality of views of structures in the space. The mirror of the plurality of mirrors may include a uniquely identifiable feature distinguishable from other objects in the space. The processor can identify the mirror of the plurality of mirrors according to the uniquely identifiable feature. The processor can also determine an attribute of the structures according to the identified mirror and the data representing the view reflected by the mirror.

Abstract: In one embodiment, an n-dimensional resource vector for each of a plurality of resources in a computer network is determined, each n-dimensional resource vector having n property values for a corresponding resource of the plurality of resources. Upon receiving a request for one or more resources of the plurality of resources, where the request indicates one or more desired property values, the techniques convert the desired property values of the request into an n-dimensional request vector, determine a distance between each resource vector and the request vector, and provide a response to the request, the response indicating one or more closest match resources for the request based on the distances.

Abstract: Data representing capabilities of devices in a data is aggregated on a cluster-basis. Information representing capability attributes of devices in the data center is received. The information representing the capability attributes is analyzed to generate data that groups devices based on similarity of at least one capability attribute. Aggregation data is stored that represents the grouping of the devices based on similarity of the at least one capability attribute and identifies the devices in corresponding groups.

Abstract: Techniques are provided herein for defragmenting resources within a cloud computing system. The cloud computing system includes a plurality of servers deployed in a plurality of respective racks, wherein the respective racks are deployed in a pod of a data center. An element of the cloud computing system determines for each server in a given rack of servers a number of free resource slots available thereon and a number of resource slots in an idle state, and then further determines whether the number of free resource slots on a first server in the plurality of servers is greater than a predetermined threshold. When the number of free resource slots in the first server is greater than the predetermined threshold, a second server in the plurality of servers is identified with sufficient resource slots thereon to accommodate the number of resource slots in the idle state on the first server, and the resource slots in the idle state on the first server are caused to be migrated to the second server.

Abstract: In one embodiment, a method comprises retrieving a request graph specifying request nodes identifying respective requested cloud computing service operations, and at least one request edge specifying a requested path requirements connecting the request nodes; identifying a placement pivot among feasible cloud elements identified in a physical graph representing a data network having a physical topology, each feasible cloud element an available solution for one of the request nodes, the placement pivot having a maximum depth in the physical topology relative to the feasible cloud elements; ordering the feasible cloud elements, according to increasing distance from the placement pivot to form an ordered list of candidate sets of feasible cloud elements; and determining an optimum candidate set, from at least a portion of the ordered list, based on the optimum candidate set having an optimized fitness function in the physical graph among the other candidate sets in the ordered list.

Abstract: A method, apparatus, computer readable medium, and system that includes receiving an indication identifying a tunnel between a first virtual machine, associated with a first protocol, and a second virtual machine, associated with a second protocol, determining that the first protocol is different than the second protocol, determining at least one translation directive that specifies for translation between the first protocol and the second protocol for the tunnel, and causing establishment of a translator based, at least in part, on the translation directive is disclosed.

Abstract: Techniques are described for selecting an optimal data center for instantiating a first cloud service. Embodiments of the invention receive a request specifying a topology of a first cloud service to be hosted by one of a plurality of data centers which provide computing resources to host a plurality of cloud services. A suitability value is then determined for each of the data centers which measures a fitness of the data center for instantiating the first cloud service. In one embodiment, the suitability value is determined by calculating a plurality of metric values for the data center, normalizing the metric values and calculating a weighted average of the normalized values. One of the data centers is then selected for instantiating the first cloud service, based at least in part on the determined suitability values.

Abstract: In one embodiment, a method comprises retrieving a request graph specifying request nodes identifying respective requested cloud computing service operations, and at least one request edge specifying a requested path requirements connecting the request nodes; identifying a placement pivot among feasible cloud elements identified in a physical graph representing a data network having a physical topology, each feasible cloud element an available solution for one of the request nodes, the placement pivot having a maximum depth in the physical topology relative to the feasible cloud elements; ordering the feasible cloud elements, according to increasing distance from the placement pivot to form an ordered list of candidate sets of feasible cloud elements; and determining an optimum candidate set, from at least a portion of the ordered list, based on the optimum candidate set having an optimized fitness function in the physical graph among the other candidate sets in the ordered list.

Abstract: In one embodiment, a method includes receiving a summary of statistics concerning a sensor node in a sensor network that comprises a plurality of sensor nodes, the statistics having been generated based on one or more of sensor data from a sensor at the sensor node, communication to the sensor node from one or more other sensor nodes in the sensor network, or communication from the sensor node; analyzing the summary; and applying based on the analysis one or more predetermined polices to one or more of the sensor nodes or the sensor network.

Abstract: In one embodiment, a method includes generating a set of statistics concerning a sensor node in a sensor network based on one or more of sensor data from a sensor at the sensor node, communication to the sensor node from one or more other sensor nodes in the sensor network, or communication from the sensor node; determining based on a subset of the set of statistics whether a predetermined anomalous event correlated with the subset has occurred; and, if the predetermined anomalous event has occurred, generating a summary of the subset and communicating it to a police node in the sensor network.

Abstract: Mining information from network data traffic to determine interests of online network users is provided herein. A data packet received at a network interface device can be accessed and inspected at line rate speeds. Source or addressing information in the data packet can be extracted to identify an initiating and/or receiving device. The packet can be inspected to identify occurrences of keywords or data features related with one or more subject matters. A vector can be defined for a network device that indicates a relative rank of interest in various subject matters. Furthermore, statistical analysis can be implemented on data stored in one or more interest vectors to determine information pertinent to network user interests. The information can facilitate providing value-added products or services to network users.

Abstract: Techniques are provided for monitoring the state or status of virtual data centers. In one embodiment, a method includes receiving state information representing the state of hardware devices supporting instantiations of virtual data centers operating within a physical data center. The state information is mapped to hardware devices supporting a selected instantiation of a virtual data center to identify state information for the selected instantiation of a virtual data center. An assessment is then made, based on the state information for the selected instantiation of a virtual data center, regarding a degree to which the selected instantiation of a virtual data center is operating in accordance with predetermined policy. A user is then notified of the assessment via, e.g., a color-coded dashboard representation of the selected instantiation of a virtual data center or a color-coded aspect of the selected instantiation of a virtual data center.

Abstract: In one embodiment, a method includes accessing first information identifying a sensor-data set that includes sensor-data from multiple sensor-data streams from multiple sensors over a period of time, with the sensor data from the sensor-data streams having been combined with each other based on a relationship of the sensor data to a sensor subject; accessing second information identifying one or more offers to purchase the sensor-data set; and matching one of the offers with the sensor-data set to facilitate a purchase of the sensor-data set based at least on the one of the offers matched to the sensor-data set.

Abstract: In one embodiment, an n-dimensional resource vector for each of a plurality of resources in a computer network is determined, each n-dimensional resource vector having n property values for a corresponding resource of the plurality of resources. Upon receiving a request for one or more resources of the plurality of resources, where the request indicates one or more desired property values, the techniques convert the desired property values of the request into an n-dimensional request vector, determine a distance between each resource vector and the request vector, and provide a response to the request, the response indicating one or more closest match resources for the request based on the distances.

Abstract: A first network device determines capabilities of resources in a section of a network that is accessible using the first network device. The first network device groups the resources into a resource cluster. The first network device advertises the resource cluster in the network, wherein each of a plurality of network devices advertise a resource cluster associated with sections of the network. A second network device receives a request for providing a service. The second network device groups the request into a plurality of request clusters. The second network device selects at least one resource cluster for providing the service based on information associated with the request clusters and the advertised resource clusters. The second network device allocates resources included in the at least one resource cluster for providing the service based on selecting the at least one resource cluster.

Abstract: Mining information from network data traffic to determine interests of online network users is provided herein. A data packet received at a network interface device can be accessed and inspected at line rate speeds. Source or addressing information in the data packet can be extracted to identify an initiating and/or receiving device. The packet can be inspected to identify occurrences of keywords or data features related with one or more subject matters. A vector can be defined for a network device that indicates a relative rank of interest in various subject matters. Furthermore, statistical analysis can be implemented on data stored in one or more interest vectors to determine information pertinent to network user interests. The information can facilitate providing value-added products or services to network users.