Convida Wireless, LLC

Interdigital Patent Holdings, Inc.

Lu Liu

Quang Ly

Dale N Seed

Chonggang Wang

Catalina Mihaela Mladin

Zhuo Chen

William Robert Flynn, Iv

Jiwan L Ninglekhu

Xu Li

Hongkun Li

Michael F Starsinic

Rocco Di Girolamo

William Robert Iv Flynn

William Robert Flynn Iv

Rocco Dl Girolamo

Systems and methods are described herein to automate managing of service layer operations comprised of multiple elementary operations and offloading the burden of performing such multi-step operations from a requesting entity to the service layer. A Request Abstraction Service (RAS) is described herein for the autonomous execution of such multi-step operations. Methods and apparatuses are also described herein for a service layer framework for integrating generic and functional user interfaces as services managed by the SL on behalf of requesting entities.

Mechanisms for an intelligent service layer request abstraction service

A distributed ledger interworking architecture is described wherein a distributed ledger proxy interfaces with IoT service layer systems and distributed ledger systems. Service layer nodes may interact with the distributed ledger proxy to leverage functions provided by distributed ledger systems, such as to request that the distributed ledger proxy insert some service layer information into the distributed ledgers. A distributed ledger proxy can support multiple service layer nodes and may interface to multiple different distributed ledger systems.

Interworking between IoT service layer systems and distributed ledger systems

The provision of fog services may be coordinated by a fog leader adapted to track capabilities and resources available at other fog nodes, and to receive and process requests and policies from entities seeking fog services. For example, the fog leader may divide tasks among several fog nodes according to the capabilities and resources available at various nodes, and do so in a way that is transparent to the requestor and the fog nodes providing the service. The fog leader may request the reservation of capabilities and resources, and confirm and cancel such reservations. Fog services policies may include, for example, periods of time during which capabilities and resources should be reserved.

Dynamic fog service deployment and management

A labeled data generation service provides an Internet-of-Things (IoT) system with a capability whereby users may configure how the system gathers, processes, and generates labeled data instances by: collecting and processing the data into a format required by supervised learning algorithms; generating expected outputs from data available in the IoT system; supporting the linking of collected inputs with generated expected outputs; forming labeled data instances; cleaning the labeled data set appropriately; sending the labeled data set to target nodes; and/or communicating with target nodes regarding improving the data processing and labeling processes, as required.

Automatic generation of labeled data in IoT systems

Systems and methods are described to automate managing of relationships between IoT entities (e.g., devices, apps, users) and offloading the burden of managing these relationships from users. A Relationship Management Service (RM Service) is described herein for the autonomous establishment, modification, and tear-down of relationships between IoT entities.

Automated relationship management of service layer entities in a communications network

A Data Sample Collection Service (DSCS) may be configured to receive various data sample collection requests from users and to process the one or more requests on behalf of the users. In order to properly describe what kind of Ready-to-Use Data Samples (RDS) a user needs, the DSCS may adopt a Data Sample Template (DST). By using the DST, the user can clearly depict what their desired data samples look like, along with various quality requirements regarding the data samples. The DSCS can further provide a DST Management function to users. In general, DST management involves the processes of DST creation, DST update, DST deletion and DST activation/de-activation. For example, a user may create a DST based on its data sample collection needs. Later, the created DST can also be updated and/or deleted based on dynamic changes to the needs of the user.

Data sample template (DST) management for enabling fog-based data processing

Some underlying networks such as Low-Power Wide-Area Networks (LPWAN) have limited communication bandwidth and strict requirements on maximum message size. These requirements may pose a challenge for data or resource exchange between two service layer (SL) entities, for example, because resource representations to be exchanged may have too large a size to be supported by the underlying networks. In some cases, traditional data compression algorithms can be used to alleviate this problem to some degree, but it is recognized herein that there are associated computation costs due to compression and decompression that may not be affordable for constrained IoT devices. Various embodiments described herein address this problem, among others by defining a Resource Representation Common Part (RRCP) and storing it at the service layer. In some cases, the RRCP is not transmitted between SL entities, thereby reducing SL message sizes to cater to the constraints of underlying networks.

Efficient resource representation exchange between service layers

An IoT/M2M service layer may be provided with the capability to protect user privacy. This functionality may allow the IoT/M2M service layer to anonymize user data, particularly when user data is shared with third party consumers. A privacy policy service may enable the IoT service layer system to generate anonymization (e.g., privacy) policies based on inputs such as legal obligations, subscriber privacy preferences, and an authorization level of the data consumer. Data anonymization policies may be output from the privacy policy service and may be sent to a data anonymization service, where raw data may be anonymized based on the one or more data anonymization policies. The output from the data anonymization service function may be a privatized (e.g., anonymized) version of data that may prevent the data consumer from discovering one or more identifying characteristics of a user.

Data anonymization for service subscriber's privacy

System and methods that improve the use of network functions on edge data networks are disclosed. A mechanism that supports edge-assisted UE context and trigger collection is described herein, where a UE can actively send its context information and/or any trigger (e.g. a request for a network function/service to be deployed in edge data networks, etc.) to an edge enabler server, which processes the received context and triggers from its UEs. The edge enabler server may also forward UE context and triggers to 5G core network (5GC) upon receiving a solicitation request from the 5GC, or if the 5GC has already made a subscription for getting notification on UE context and triggers. A network repository function is provided as a new network function collect, store, and manage edge data network information.

Edge aware distributed network

Methods, systems, and apparatuses that enable a Service Layer (SL) to support analysis of internet of things (IoT) data and enable shared access to information generated by the analysis. An analytics management service may allow SL entities to configure analytics functions for many different IoT sources of data and organize the results in a customizable manner. The SL may support coordinating the analysis of IoT data from multiple independent sources and organizing the results of the analysis.

Service layer-based methods to enable efficient analytics of IoT data

Some underlying networks such as Low-Power Wide-Area Networks (LPWAN) have limited communication bandwidth and strict requirements on maximum message size. It is recognized herein that these requirements may pose a challenge for data or resource exchange between two service layer (SL) entities, for example, because resource representations to be exchanged may have too large a size to be supported by the underlying networks. In some cases, traditional data compression algorithms can be used to alleviate this problem to some degree, but it is recognized herein that there are associated computation costs due to compression and decompression that may not be affordable for constrained IoT devices. Various embodiments described herein address this problem, among others, by defining a Resource Representation Common Part (RRCP) and storing it at the service layer. In some cases, the RRCP is not transmitted between SL entities, thereby reducing SL message sizes to cater to the constraints of underlying networks.

Methods and apparatuses are described herein for an automated product management (APM) service. An apparatus may receive from a second apparatus, at least one first request to enroll a third apparatus with a service layer associated with the second apparatus. The apparatus may send a second request to verify authenticity of the third apparatus and to generate a customized firmware or software for the third apparatus. The apparatus may send a third request to configure the third apparatus based on consent of a user of the third apparatus. The apparatus may send a response indicating whether the third apparatus has been enrolled with the service layer. The apparatus may receive a fourth request to diagnose or troubleshoot the third apparatus and a fifth request comprising information and the consent and requesting the fourth apparatus to perform at least one operation on the third apparatus.

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Conshohocken, PA, United States of America

Lu Liu