Abstract: Remote provisioning of an IT network and/or associated services is provided. Hardware, software, service and/or expertise can be moved from on-premise to a remote location (e.g., central, distributed . . . ). Accordingly, at least a large degree computation can be moved to the center to exploit economies of scale, among other things. In such an architecture, computational resources (e.g., data storage, computation power, cache . . . ) can be pooled, and entities can subscribe to a particular level of resources related to a private entity IT network.

Abstract: A user-centric or identity-centric resource licensing system that manages access to ‘cloud-based’ resources (e.g., applications and services) is provided. A ‘cloud’ refers to a collection of resources (e.g., hardware and/or software) provided and maintained by an off-site or off-premise party (e.g., third party), wherein the collection of resources can be accessed by an identified user via a network. In accordance with the user-centric licensing model, the resource license (and subscription) rights can migrate with a user without regard to physical location, device used, or other contextual factors (e.g., activity engaged). Effectively, the rights are mapped (and tracked) as a function of a user identity, which can be a core identity or an identity based upon activity engaged, role, capacity, etc.

Abstract: Personal data mining mechanisms and methods are employed to identify relevant information that otherwise would likely remain undiscovered. Users supply personal data that can be analyzed in conjunction with data associated with a plurality of other users to provide useful information that can improve business operations and/or quality of life. Personal data can be mined alone or in conjunction with third party data to identify correlations amongst the data and associated users. Applications or services can interact with such data and present it to users in a myriad of manners, for instance as notifications of opportunities.

Abstract: The claimed subject matter provides systems and/or methods that facilitate replicating a state associated with a client, user, service, application, and the like. A third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. A replication component can generate replicas of states associated with requested services. Further, the replicas can facilitate seamlessly interacting with the third party service provider (e.g., while transitioning between client devices). Additionally, by providing replicas of the state related information, differing third party service providers can effectuate services based upon a request from a client without regenerating the state.

Abstract: The claimed subject matter provides systems and/or methods that facilitate dynamically allocating resources (e.g., hardware, software, . . . ) supported by a third party service provider. The third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. An interface component can receive a request from a client device. Further, a dynamic allocation component can apportion resources (e.g., hardware resources) supported by the third party service provider to process and respond to the request based at least in part upon subscription data. Moreover, a user state evaluator can determine a state associated with a user and/or the client device; the state can be utilized by the dynamic allocation component to tailor resource allocation.

Abstract: The claimed subject matter provides systems and/or methods that facilitate replicating a state associated with a client, user, service, application, and the like. A third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. A replication component can generate replicas of states associated with requested services. Further, the replicas can facilitate seamlessly interacting with the third party service provider (e.g., while transitioning between client devices). Additionally, by providing replicas of the state related information, differing third party service providers can effectuate services based upon a request from a client without regenerating the state.

Abstract: Remote provisioning of an IT network and/or associated services is provided. Hardware, software, service and/or expertise can be moved from on-premise to a remote location (e.g., central, distributed . . . ). Accordingly, at least a large degree computation can be moved to the center to exploit economies of scale, among other things. In such an architecture, computational resources (e.g., data storage, computation power, cache . . . ) can be pooled, and entities can subscribe to a particular level of resources related to a private entity IT network.

Abstract: A user-centric or identity-centric resource licensing system that manages access to ‘cloud-based’ resources (e.g., applications and services) is provided. A ‘cloud’ refers to a collection of resources (e.g., hardware and/or software) provided and maintained by an off-site or off-premise party (e.g., third party), wherein the collection of resources can be accessed by an identified user via a network. In accordance with the user-centric licensing model, the resource license (and subscription) rights can migrate with a user without regard to physical location, device used, or other contextual factors (e.g., activity engaged). Effectively, the rights are mapped (and tracked) as a function of a user identity, which can be a core identity or an identity based upon activity engaged, role, capacity, etc.

Abstract: A method for determining a load distribution for a plurality of servers is disclosed. A total user count during a predetermined interval of time is received from each server of a plurality of servers for all channel resources associated with each respective server of the plurality of servers. A present load distribution is determined for the predetermined interval of time for each respective server of the plurality of servers based on the total user count received from each server. A load gradient is determined for the predetermined interval of time from each server of the plurality of servers. A future load distribution is determined for each respective server based on the total user count for each server and each respective load gradient. Lastly, a load distribution for each respective channel resource is distributed among the plurality of servers based on the determined future load distribution for each respective channel resource.

Abstract: A method for determining a load distribution for a plurality of servers is disclosed. A total user count during a predetermined interval of time is received from each server of a plurality of servers for all channel resources associated with each respective server of the plurality of servers. A present load distribution is determined for the predetermined interval of time for each respective server of the plurality of servers based on the total user count received from each server. A load gradient is determined for the predetermined interval of time from each server of the plurality of servers. A future load distribution is determined for each respective server based on the total user count for each server and each respective load gradient. Lastly, a load distribution for each respective channel resource is distributed among the plurality of servers based on the determined future load distribution for each respective channel resource.

Abstract: A method for determining a load distribution for a plurality of servers is disclosed. A total user count during a predetermined interval of time is received from each server of a plurality of servers for all channel resources associated with each respective server of the plurality of servers. A present load distribution is determined for the predetermined interval of time for each respective server of the plurality of servers based on the total user count received from each server. A load gradient is determined for the predetermined interval of time from each server of the plurality of servers. A future load distribution is determined for each respective server based on the total user count for each server and each respective load gradient. Lastly, a load distribution for each respective channel resource is distributed among the plurality of servers based on the determined future load distribution for each respective channel resource.

Abstract: A technique for maintaining server cluster consistency is disclosed. When a front-end server of a plurality of servers detects that the front-end server has reconnected to a backend server or in the situation of a backend server failover, the front-end server sends resource ownership information to a backend server. The resource ownership information relates to ownership information for each respective resource owned by the front-end server. The back-end server verifies the ownership information for contention with static resources and dynamic resources owned by other servers and sends back verification information to the server. The backend maintains resource ownership information for all the servers in the cluster than sent resources for verification. Based on the received verification information, the server maintains ownership information at the server for each respective resource indicated in the verification information to be owned by the server.

Abstract: A failover algorithm implemented in software, without any failover-specific hardware, that allows servers in a cluster to determine whether a primary or secondary controller is active without requiring communication between the primary and secondary controllers. A server cluster includes several servers coupled to two servers, which are designated as a primary controller and a secondary controller. While the server cluster is operational, either the primary controller or the secondary controller will be actively controlling the cluster. Software running on the servers of the cluster, on the primary controller, and on the secondary controller, cooperates to ensure that each server will properly identify which controller is active at any particular time, including, but not limited to, upon starting up the server cluster, upon adding one or more servers to a cluster that is already operation, and upon failure of an active controller, a server, or a link between an active controller and a server.