Convida Wireless, LLC

Sneha Aman Singh

Chonggang Wang

Xu Li

Quang Ly

Shamim Akbar Rahman

Gregory S Sternberg

Qing Li

Rocco Di Girolamo

Catalina Mihaela Mladin

Hongkun Li

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.

Methods for enabling data analytics service at service layer

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.

Data stream analytics at service layer

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Redmond, WA, United States of America

Sneha Aman Singh