Abstract: An identity provider (200) communicates (101) with a first logged-in user who seeks to receive particular streaming content at a first corresponding first user platform and who has also identified at least one other user with whom this user wishes to share the receiving of this content. The identity provider invites (102) the other user to share in the receiving of this content. Upon receiving (103) an acceptance of the invitation from the other user, the identity provider can treat this other user as a logged-in participating second user (i.e., a user who is now both logged-in (even if this user was not previously logged-in) and who wishes to accept the invitation and participate in viewing the streaming content selected by the first user) and automatically direct (104) these users to a content provide to facilitate the substantially simultaneous receipt of the streaming content at all of the corresponding user platforms.

Abstract: A method and system for evaluating performance of a policy rule (101) includes a memory (406) and processor (404) adapted for accessing at least one policy rule (101) having associated with it at least one policy event (102), at least one policy action (104), and at least one policy condition (103). Next, the policy rule (101) is associated with at least one policy evaluation event (105), at least one policy evaluation condition (106), and at least one policy evaluation action (107), wherein the policy evaluation event (105) is independent of the policy event (102) which triggers the policy rule (101). Performance of the policy rule (101) is then assessed by utilizing the policy evaluation condition (106) and the policy evaluation action (107).

Abstract: A method and system for managing a policy includes a memory adapted to store at least one policy, residing at a first abstraction level, where each policy includes a plurality of language elements in a first vocabulary set and a processor communicatively coupled to the memory and adapted to perform semantic resolution using a set of ontologies by mapping at least one of the language elements in the first vocabulary set to at least one of a plurality of language elements in a second vocabulary set, the second vocabulary set having at least one of a different grammar and a different vocabulary from the first vocabulary set create a second policy, in response to the semantic resolution.

Abstract: A method (1300) for manipulation of two sets of policies is described, wherein each set includes at least two related policies, and wherein each policy comprises a set of policy rules. The method includes identifying (1325) a possible conflict between a pair of policies comprising one policy in each of two sets of policies, marking (1330) the one policy in each of the two sets of policies to identify the possible conflict, and marking (1330) at least one other policy in one of the two sets of policies that is related to one of the marked policies in the two policy rules to identify at least one other possible conflict.

Abstract: A system [100] is provided that includes a Model-Based Translation Layer [200] to accept an input event being formed in any of a pre-determined set of languages and protocols, and output an output message having a common language and protocol. The system [100] also includes a State Processing Layer [300] to (a) parse the output message to determine an event, an externally perceived state of the event, and an internally perceived state of the event; (b) determine a type of the event; (c) determine whether the externally perceived state of the event is substantially equivalent to the internally perceived state of the event; and (d) invoke policy control to lookup action functions to address the event in response to determining that a combination of the type of the event and the externally perceived state of the event is determined to be valid.

Abstract: A system includes vendor specific converters [210, 215, 220, 225] to gather vendor-specific data from sensors [235, 240] and convert to normalized data. The vendor-specific data comprises at least a first input and a second input. The first input corresponds to a first language and the second input corresponds to a second language, where the first language is different from the second language. The vendor specific converters [210, 215, 220, 225] receive normalized commands and issue vendor-specific commands to a managed resource [165]. A converter module [230] receives the normalized data and converts to an output corresponding to a common language. The converter module [230] also receives and outputs normalized commands corresponding to the common language. Semantic processing logic [255] receives the normalized data and matches the normalized data against a predetermined set of knowledge bases and generates a new object to send to an autonomic manager [160].

Abstract: A system includes object construction logic [700] and semantic augmentation logic [705]. The object construction logic receives events and data. It also identifies whether managed objects exist in a predefined set of at least one information model [205] and at least one ontology [240] corresponding to the events and data. The object construction logic [700] further deduces, based on the events and data, whether any previously unknown managed objects exist corresponding to the events and data. The semantic augmentation logic [705] augments at least one of the managed objects and the previously unknown managed objects with semantic information based on knowledge-based reasoning and state awareness, according to at least one installed policy to generate at least one new object and provide the at least one new object to an autonomic processing engine.

Abstract: An autonomic computational processor can be provided with both at least one substantially closed loop problem solving mechanism (such as, but not necessarily limited to, an abductive algorithm-based problem solving mechanism (101)) and at least one substantially open loop problem solving mechanism (such as, but not necessarily limited to, a machine learning algorithm-based problem solving mechanism (102)). Upon receiving (103) information regarding a problem as relates to a given corresponding process, then, these teachings can provide for automatically determining (104) which of the closed loop and open loop problem solving mechanisms to use to attempt to resolve the problem.

Abstract: The disparate data and commands from are received from a managed resource (102) and have potentially different semantics. The disparate data and commands are processed according to rules received from an autonomic manager (112) to produce a single normalized view of this information. The actual state of the managed resource is determined from the normalized view of disparate data. The actual state of the managed resource (102) is compared to a desired state of the managed resource (102). When a match does not exist between the actual state and the desired state, a configuration adjustment to the managed resource (102) and/or another resource is determined to allow the actual state to be the same as the desired state. Then, the configuration adjustment is applied to the managed resource (102). When a match exists between the actual state and the desired state, maintenance functions associated with the managed resource (102) are performed.