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公开(公告)号:US12026167B2
公开(公告)日:2024-07-02
申请号:US16096498
申请日:2017-04-25
Applicant: CONVIDA WIRELESS, LLC
Inventor: Xu Li , Qing Li , Sneha Aman Singh , Rocco Di Girolamo , Catalina Mihaela Mladin , Hongkun Li , Chonggang Wang
IPC: G06F16/2458 , G06F9/54 , G06F16/84 , G06F16/955 , G06F16/958 , G06Q30/0201 , H04L67/63
CPC classification number: G06F16/2465 , G06F9/541 , G06F9/547 , G06F16/86 , G06F16/955 , G06F16/958 , G06Q30/0201 , H04L67/63 , G06F2216/03
Abstract: A common Data Analytics Service (DAS) at service layer is designed to use underlying existing/future data analytics technologies or tools and provide them to service layer entities that need those data analytics operations with uniform access approach. A general operation framework/interface design is used for enabling DAS and the operation details within DAS. Related procedures for interacting with DAS, including the new parameters in service layer request/response messages can be used.
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公开(公告)号:US10956423B2
公开(公告)日:2021-03-23
申请号:US16096510
申请日:2017-04-25
Applicant: CONVIDA WIRELESS, LLC
Inventor: Sneha Aman Singh , Xu Li , Quang Ly , Gregory S. Sternberg , Shamim Akbar Rahman , Chonggang Wang
Abstract: A modular and distributed architecture for data stream processing and analysis is described to incorporate data stream analytics capabilities, called Data Stream Analytics Service (DSAS) in the IoT/M2M service layer. Each service layer node hosting DSAS can be split into two independent modules, Stream Forwarder and Stream Analytics Engine. Stream Forwarder is a light weight processing modules that can be responsible for data preprocessing and routing. Stream Analytics Engine is responsible for performing actual analytics on the data stream. Separating the two functionalities enables the service layer nodes to efficiently distribute stream analytics tasks across multiple nodes.
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公开(公告)号:US11727012B2
公开(公告)日:2023-08-15
申请号:US17175100
申请日:2021-02-12
Applicant: CONVIDA WIRELESS, LLC
Inventor: Sneha Aman Singh , Xu Li , Quang Ly , Gregory S. Sternberg , Shamim Akbar Rahman , Chonggang Wang
IPC: G06F16/2455 , H04L12/28 , H04W4/70 , H04L43/04 , H04W12/08 , H04L43/18 , G06F16/00 , H04L67/12 , H04L9/40
CPC classification number: G06F16/24568 , G06F16/00 , H04L12/28 , H04L12/2823 , H04L43/04 , H04L43/18 , H04L67/12 , H04W4/70 , H04W12/08 , H04L63/10 , H04L63/1425
Abstract: A modular and distributed architecture for data stream processing and analysis is described to incorporate data stream analytics capabilities, called Data Stream Analytics Service (DSAS) in the IoT/M2M service layer. Each service layer node hosting DSAS can be split into two independent modules, Stream Forwarder and Stream Analytics Engine. Stream Forwarder is a light weight processing modules that can be responsible for data preprocessing and routing. Stream Analytics Engine is responsible for performing actual analytics on the data stream. Separating the two functionalities enables the service layer nodes to efficiently distribute stream analytics tasks across multiple nodes.
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