203 results about "Service optimization" patented technology

Systems and methods are described for a power aggregation system. In one implementation, a service establishes individual Internet connections to numerous electric resources intermittently connected to the power grid, such as electric vehicles. The Internet connection may be made over the same wire that connects the resource to the power grid. The service optimizes power flows to suit the needs of each resource and each resource owner, while aggregating flows across numerous resources to suit the needs of the power grid. The service can bring vast numbers of electric vehicle batteries online as a new, dynamically aggregated power resource for the power grid. Electric vehicle owners can participate in an electricity trading economy regardless of where they plug into the power grid.

Applications of CI processing to ad-hoc and peer-to-peer networking significantly improve throughput, network capacity, range, power efficiency, and spectral efficiency. CI-based subscriber units perform network-control functions to optimize network performance relative to channel conditions, network loads, and subscriber services. CI codes are used to identify and address network transmissions. Channel characteristics of communication links are employed to encode, address, and authenticate network transmissions. CI transceivers used as relays and routers employ unique characteristics of transmission paths to code and decode network transmissions. A central processor is adapted to perform array processing with signals received from, and transmitted by, a plurality of subscriber units in a wireless network.

The invention provides a method for dynamically configurating TDD (Time Division Duplex) base station uplink and downlink subframe scale. Through measurement and feedback of TDD base station interference environment and service type, the method can realize different uplink and downlink subframe scale configurations in different cells so as to avoid the strong interference and simultaneously realize flexible and dynamic self-configuration of TDD uplink and downlink subframe scale, thus improving the service efficiency of wireless communication resource, enhancing TDD cell service optimization and improving the energy efficiency of the access network. The invention can be applied to the cell environment of the next generation wireless communication system in TTD mode, including Femtocell in homogeneous or heterogeneous network and indoor relay and the like.

A method and system for determining quality and capacity of a transport monitoring connection between radio service nodes to facilitate local management of subscriber connections are disclosed. One method includes sending first test packets from a first radio service node to a second radio service node via the transport monitoring connection. Second test packets are received from the second radio service node. The second test packets have information added to the first test packets by the second radio service node. The second test packets are analyzed to determine a quality and a bandwidth of the transport monitoring connection. Control and user plane functions are informed when transport monitoring performance is one of degraded and improved based on the quality and bandwidth. The method includes making radio service provisioning decisions based on the quality and bandwidth of the transport monitoring connection.

A shopping system may receive, from a user, a request to add information about an item to a watch list associated with the user; may receive, from the user, a price associated with the item; and may receive, from the user, a schedule associated with the item. The shopping system may identify a vendor offer associated with the item and associated with a particular vendor, where the vendor offer includes a price that is less than or equal to the received price, the identifying being based on the schedule associated with the item; and may provide a notification to the user, where the notification includes information about the identified vendor offer.

The invention discloses a self-adaptive composite service optimization method based on multi-agent reinforced learning. The method combines conceptions of the reinforced learning and agents, and defines the state set of reinforced learning to be the precondition and postcondition of the service, and the action set to be the Web service; parameters for Q learning including the learning rate, discount factors and Q value in reinforced learning are initialized; each agent is used for performing one composite optimizing task, and can perceive the current state, and select the optimal action under the current state as per the action selection strategy; the Q value is calculated and updated as per the Q learning algorithm; before the Q value is converged, the next round learning is performed after one learning round is finished, and finally the optimal strategy is obtained. According to the method, the corresponding self-adaptive action strategy is worked out on line as per the environment change at the time, so that higher flexibility, self-adaptability and practical value are realized.

Systems and methods can provide for customer value optimization. The customer value optimization can include analyzing certain transaction and / or non-transaction data of customers with one or more predictive models to determine predictive modeling scores, values, or indicators. These one or more predictive modeling scores, values, or indicators can be used with other transaction or non-transaction data of customers, either alone or with other derived values / calculations, to provide certain optimizations relating to product / service optimization.

An online certificate status checking protocol (OCSP) system is provided for use with a first device, an end device and a certificate authority. The first device can provide a certificate. The end device can provide an OCSP request based on the certificate and process an OCSP response. The certificate authority can provide a CRL update. The certificate has a validity period. The OCSP system includes an OCSP responder, and OCSP proxy and a cache. The OCSP responder can provide the OCSP response. The OCSP proxy can receive the OCSP request from the end device, can send the OCSP request to the OCSP responder, can receive the OCSP response from the OCSP responder and can send the OCSP response to the end device. The cache can store information based on the OCSP response. The OCSP proxy can further store, in the cache, information based on the OCSP response and can send a proactive OCSP request to the OCSP responder based on a predetermined policy. The OCSP responder can further send a proactive OCSP response to the OCSP proxy in response to the proactive OCSP request. The OCSP proxy can further update the information in the cache based on the proactive OCSP response. The OCSP proxy can additionally provide, using the updated information in the cache, a second OCSP response to the end device in response to a subsequent request from the end device related to information of the certificate.

Various examples are provided for power quality of service optimization for microgrids. In one example, among others, a microgrid includes a smart meter configured to control supply of electric power to loads based at least in part upon energy consumption scheduling of the loads, which is based at least in part upon an effective electric generation capacity associated with the microgrid. The energy consumption scheduling can be based at least in part upon estimated power output of a sustainable energy resource of the microgrid and a load demand characterization of the loads. In another example, a system comprises a plurality of microgrids and an advanced metering infrastructure (AMI) configured to monitor operations of the microgrids and to control supply of electric power from sustainable energy resources and energy storage systems to loads of the microgrids via smart meters based at least in part upon energy consumption scheduling of the loads.

The embodiment of the invention provides a data processing method and device, a functional entity and a storage medium. In the data processing method of the network, on one hand, the NWDAF can exchange application layer information or application layer service optimization information with the AF directly or through the NEF; and on the other hand, the NWDAF can issue an analysis result to the SMF,the AMF, the UDM, the UDR or the PCF directly or through the PCF.

The invention provides a cloud manufacturing resource service optimization scheduling method based on fuzzy multi-objective optimization. The cloud manufacturing resource service optimization scheduling method comprises the steps that step 1, a service demander proposes project requirements; step 2, project task decomposition is performed; step 3, candidate resources are determined; step 4, cloudresource scheduling is performed; step 5, service selections are made based on a scheduling result.: corresponding services are selected according to a production scheduling scheme and operation is performed; step 6, user evaluations are made: the service demander evaluates the scheme after the task solution is executed; step 7, scheduling information is sorted into a database by storing the scheduling information and the user information into the database for next use. A fuzzification mechanism is added in the multi-objective optimization process to carry out fuzzification processing on service reliability evaluation. Therefore, the whole scheduling process finds the optimal scheduling combination scheme faster, and the technical problem that enough good service support cannot be providedfor the service demander due to narrow resource acquisition surface and opaque resources in the traditional manufacturing scheduling process is solved.

The invention discloses composite service optimizing method and device based on a protocol composition mechanism. The method comprises the steps of: acquiring access information of different users to composite service and interaction and dependency among services in the process of composite service execution; generating a service process model through a process mining algorithm based on the acquired access information of users to the composite service, the interaction and dependency among the services and a process optimizing strategy; and carrying out adjustment and optimization on the composite service according to the requirements on the users and the service process model to acquire the composite service meeting the requirements on the users. The technical scheme of the invention can carry out dynamic adjustment on the composite service through the interaction and the dependency among services so as to ensure that the adjusted and optimized composite service can better meet the actual requirements on the users and improve the user satisfaction index.

The invention provides a low-data volume service optimization method for a long term evolution (LTE) network and network side equipment. The method comprises the following steps of: when the network side equipment receives a service establishment request from a mobile terminal, identifying the type of a service to be established by the mobile terminal; when the type of the service is a low-data volume service, querying the type of an operating system used by the mobile terminal according to the international mobile equipment identity (IMEI) of the mobile terminal; querying corresponding connection strategy information from a preset terminal information table according to the type of the operating system and the type of the service; establishing service connection for the mobile terminal according to the connection strategy information, and residing the mobile terminal in a radio resource control (RRC) state; and configuring a discontinuous receiving (DRX) parameter in the connection strategy information for the mobile terminal. A signaling load is alleviated, and problems caused by the introduction of a DRX technology about time delay and energy consumption are solved, so that a good experience is provided for a user.

The invention provides a dynamic domain name service optimizing system, and relates to the field of network communication. A conventional DNS mainly has the problem of address resolution suboptimum; as a BGP service is forwarded through a destination address, BGP service access quality is relatively more greatly influenced by different addresses obtained for an identical domain name; and as the conventional domain names all provide a plurality of sets of addresses for the access of users, the satisfaction of the users in access experiences is greatly improved if an optimal resolved address can be obtained. The dynamic domain name service optimizing system comprises a DNS optimization controller, adopts an active working principle, queries all DNS results for www.abc.com according to a request of a client for the www.abc.com, puts the DNS results into a comparison list, performs connectivity checking on records in the list, determines a fastest IP address record through calculation and comparison and returns optimal IP address information to the client.

A wireless communication system optimizes media services over a wireless network. The wireless communication system is HARQ enabled. The wireless communication system receives the number of HARQ retransmissions, communication status data, configuration data, and flow identifications (IDs) for media flows that use FEC packets. The wireless communication system determines if the communication status data exceeds a system status threshold. If the communication status data exceeds the system status threshold, then the wireless communication system adjusts the number of HARQ retransmissions.

An integrated, pervasive service management system of a service organization for a mobile workforce and vehicle that includes an application server to coordinate communications between the system and field service entities that include service technician communication devices. The system also includes an integration hub server to communicate between the service optimization suite and back office systems of the service organization and a universal service model to automatically coordinate the details of a service contract concerning service to be provided to customers of the organization. A optional service optimization suite to provide integrated, optimized service can also be provided.

An API optimizer generates an API (application program interface) customized to a particular process. The resulting optimized API includes API services that minimize network access. The API optimizer applies heuristic rules from a rules database to generate, on the basis of the application logic flow for that application and the set of objects, those services that minimize network access.

An apparatus in one example has: a first communication network optimized for high-speed packet data services; a first database operatively coupled to the first communication network; a second communication network for providing both voice and slow data-rate data services; a second database operatively coupled to the second communication network; and an operations platform operatively coupled to the first and second databases. The first communication network optimized for high speed packet data will generate in the first database a record which will have at least: mobile ID type, mobile ID, connection ending time, cell, sector, carrier information; and last signal strength value. The second communication network providing both voice and low speed packet data will generate, in the second data base, a record that will have at least mobile ID type, call start time, call length, mobile ID (ESN / MEID), call type (data or voice), cell, sector, carrier information; and call disposition. The operations platform will link the records on the two databases based on mobile ID, call ending time, and the call start time. The linking of the two records with matching mobile ID and time stamps will give information about mobile tuneaway and the reason for the tune away.

The invention relates to a ship navigation data high-efficiency visual analysis method in a cloud environment. The method includes the following steps: 1, designing an HBase-oriented cloud storage mode; 2, establishing a ship transportation visual analysis body, and designing an HBase-based OWL body storage mode; 3, designing a cloud service description model for ship navigation visual analysis features; 4, describing user visual analysis function requirements and QoS requirements; 5, selecting visual analysis cloud services according with the user function requirements and the QoS requirements, designing mapping functions within the cloud services and among the cloud services, and dynamically constructing a visual analysis cloud service optimized combination model; 6, establishing a ship navigation visual analysis global process model and a local process model to realize static optimized division of processes; and 7, constructing a multi-target optimizing model, completing dynamic adjustments of local processes, and realizing visual analysis of ship navigation data. The visual analysis process implementation efficiency for ship navigation data is improved effectively.

The invention discloses a source network load interaction mode based intelligent power distribution network dispatching service optimization method. The source network load interaction mode based intelligent power distribution network dispatching service optimization method comprises the steps of 1 determining an optimization objective for a system weak link so as to perform initiative optimization according to current network architecture operation state analysis and index assessment of a power distribution network, 2 performing dispatching service optimization, namely optimizing process flows of long-term, medium-and-long-term, short-term, ultra-short-term and real-time all-time-scale dispatching service, 3 performing progressive dispatching service optimization, namely conducting progressive dispatching service optimization on the dispatching service at all time scales from the perspective of the dispatching service. The dispatching service optimization is performed through the process flows of the long-term, medium-and-long-term, short-term, ultra-short-term and real-time all-time-scale dispatching service, the incidence relation of multiple time periods and the optimization objective are firstly determined, and then the planning compilation optimization and optimization scheme arrangement of the dispatching service are performed. The source network load interaction mode based intelligent power distribution network dispatching service optimization method utilizes a source network load interaction mode and operation efficiency optimization and improvement of the power distribution network to achieve overall efficient operation of the power distribution network.

The invention discloses a cloud manufacturing service optimization method. The method includes the following steps: first, according to a structure of a manufacturing task, optional manufacturing services and manufacturing service combinations, randomly generating an initial population as a current population for subsequent iteration, and representing each manufacturing service combination schemein the current population with a two-dimensional code; then executing transfer operator operation and mutation operator operation on the current population and applying variable neighborhood search tothe current population to perform transformation; and then judging whether an end condition is satisfied, if the condition is satisfied, stopping the iteration, and outputting the optimal manufacturing service composition scheme, otherwise returning to continue the iteration. The method provided by the invention has superior performance in solving the service combination problem.

The invention discloses a hadoop-based panoramic big data distributed storage method, can provide a novel big data distributed storage method for big data of intelligent grids, and can effectively solve the problems of storage redundancy, low access efficiency, poor disaster recovery robustness and the like of the traditional relational database. The hadoop-based panoramic big data distributed storage method comprises the steps of firstly, optimizing the design of an Hbase table based on distributed data storage and access to minimize and fixedly set the row key length, then performing load balance, JVM (Java Virtual Machine) optimization and split-and-merge service optimization on Hbase system performance, and finally, optimizing large-scale small files of an HDFS (Hadoop Distributed File System) by adopting a labeling method. The method obviously improves the power big data distributed storage technology on storage redundancy optimization, fast access, high efficiency and high reliability and disaster recovery security.

The invention discloses service assembly system and method based on service quality optimization and semantic information integration, which are designed mainly for improving the reliability and stability of service assembly and service quality. The service assembly system comprises a Web service network, an ontology concept network database, an index generating server, a service assembly engine server and a service assembly result executing server, wherein the Web service network provides service and a corresponding input / output data type; the ontology concept network database provides an ontology concept; the index generating server is used for establishing a service-data type-ontology index between the input / output type of the service and the ontology concept and storing the index in the index generating server; and the service assembly engine server is used for receiving the input / output data type demanded by the client end, inquiring the data type matched with the input / output data type from the service-data type-ontology index and carrying out service assembly according to a service assembly algorithm to obtain a service assembly result. The invention integrates semantic information, has optimal service quality and can efficiently process large-scale service assembly.

The invention discloses a method for selecting to-be-increased components based on an improved multi-target particle swam optimization algorithm, and belongs to the technical field of cloud service optimization. The method comprises the following steps of analyzing concurrent quantity of history application users, and utilizing an autocorrelation coefficient analysis method to divide the concurrent quantity into a stationary type and a non-stationary type according to the data distribution trend of the concurrent quantity; and predicating the concurrent quantity of application users for different characteristics by utilizing different time sequence prediction methods. According to the method, the prediction efficiency is not only improved, but the flexibility of the prediction method is improved; furthermore, the component call relationship and the component call frequency are utilized to decompose the concurrent quantity of the application users, the concurrent quantity of each component is computed, two factors capable of directly reflecting the working performance of each component, namely the concurrent quantity of each component and the component response time, are comprehensively considered and are taken as the basis of selection of the to-be-increased components, so that the accuracy of the method for selecting the component is improved; the method aims at the problem of low precision of the constraint condition of the conventional particle swam optimization algorithm, and provides a semi-feasible region, so that the precision of the constraint condition is effectively improved.

The invention provides a method and device for processing service wireless side behavioral analysis. The method comprises the steps that a control plane message generated by an RNC and an SGSN in an interactive mode through an Iu-PS interface is identified, user plane data packages sent by the RNC and the SGSN through the Iu-PS interface are analyzed, a control plane data package and the user plane data packages are related according to a preset rule, and service wireless side behavioral analysis is conducted according to the recorded number of sending times, the sending time of each message and the service type. According to the technical scheme, service wireless side behavioral analysis can be conducted in a time-saving, labor-saving and low-cost mode, so that the service optimization efficiency is greatly improved.

The invention discloses a service optimization method based on quality of service (QoS) historical recording and clustering. The service optimization method comprises the following steps: step 1, obtaining a data set; step 2, performing layering clustering on the QoS historical recording of each service by utilizing an H2D-SC fuzzy layering clustering method, performing service combination based on the QoS historical recording by utilizing the clustering center of each service in each layer, and calculating the scores of each service combination based on the QoS historical recording according to a utility value formula; and step 3, enabling each service to correspond to a cluster in each layer, acculumating the utility value scores of the service combination based on the QoS historical recording participated by each clustering center, generating the next layer of the service according to the cluster with the highest score, and simultaneously accumulating the utility value scores of the service combination based on the QoS historical recording into the corresponding utility value scores of the service combination. Finally the service combination with the highest score is the optimum service combination scheme.

The invention relates to an implement system for resource service optimization allocation (RSOA) fault-tolerant management. In the implement system, corresponding fault-tolerant management implement mechanisms are designed according to causes and types to generate faults in a process of RSOA so as to implement corresponding fault detection and elimination. The implement system comprises an information service module, an RSOA module, a fault detection module and a fault recovery module, and has the advantages of good modularity, maintainability and expansibility, can effectively detect and eliminate various faults in the process of the RSOA, and improves stability of the whole service manufacturing system and reliability of the RSOA. The implement system can effectively detect common faults caused by virtual connect, resources, tasks, applications and the like in the process of the RSOA of the service manufacturing system and provides corresponding good elimination strategies for the common faults, as well as effectively improves reliability and service quality of the RSOA of the service manufacturing system.

The embodiment of the invention provides a business optimization method based on big data positioning and artificial intelligence, and a cloud computing center, and the method comprises the steps: extracting the target user intention features of a business service link and the user portrait feature information of the business service link through a business relation; rich business relationship feature information of the business service link being extracted by integrating the business flow label information of the business service link and the user portrait feature information of the businessservice link, and data support being provided for accurate information pushing based on big data positioning; and besides, through the target user intention characteristics of the business service link, business push configuration updating is performed on the business service link, and business push configuration optimization information of the business service link is obtained, so that an accurate information push process based on big data positioning is realized.