Using JSON to manage communication between services in the Internet of Things

Wehner, Philipp; Piberger, Christina; Göhringer, Diana

doi:10.1109/recosoc.2014.6861361

Cited by 34 publications

(11 citation statements)

References 5 publications

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“…Interactive, on the other hand, refers to the end user being able to be involved in each step. The KDD steps involved include (1) Establishing the application domain (2) Building a target data set (3) Data cleaning and pre-processing (4) Data transformation (5) Selecting the suitable DM task [50] Selecting the DM algorithm (7) Applying the DM algorithm (8) Evaluation and interpretation of mined data (9) Consolidation of newly created knowledge [14].…”

Section: Kddmentioning

confidence: 99%

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

2020

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A core subfield of knowledge management (KM) and data mining (DM) constitutes an integral part of the knowledge discovery in database process. With the explosion of information in the new digital age, research studies in the DM and KM continue to heighten up in the business organisations, especially so, for the small and medium enterprises (SMEs). DM is crucial in supporting the KM application as it processes the data to useful knowledge and KM role next, is to manage these knowledge assets within the organisation systematically. At the comprehensive appraisal of the large enterprise in the transportation sector and the SMEs across various industries-it was gathered that there is limited research case study conducted on the application of DM-KM on the transportation SMEs in specific. From the extensive review of the case studies, it was uncovered that majority of the organisations are not leveraging on the use of tacit knowledge and that the SMEs are adopting a more traditional use of ICTs to its KM approach. In addition, despite DM-KM is being widely implemented-the case studies analysis reveals that there is a limitation in the presence of an integrated DM-KM assessment to evaluate the outcome of the DM-KM application. This paper concludes that there is a critical need for a novel DM-KM assessment plan template to evaluate and ensure that the knowledge created and implemented are usable and relevant, specifically for the SMEs in the transportation sector. Therefore, this research paper aims to carry out an in-depth review

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Section: Kddmentioning

confidence: 99%

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

2020

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“…Additionally, a standardized format is required for the transmission of data between the fine blanking machine and the FE simulation AAS. The JavaScript Object Notation (JSON) is suitable for this, because the format is very flexible and human readable, has a low overhead, and can be interpreted by all common programming languages [19]. These features make it well suited for an Internet of Things and a service-oriented architecture.…”

Section: Requirement Analysismentioning

confidence: 99%

Development of a hybrid DLT cloud architecture for the automated use of finite element simulation as a service for fine blanking

Stanke

Unterberg

Trauth

et al. 2020

Int J Adv Manuf Technol

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Networking and digitization in manufacturing enable novel methods of data-driven analysis and optimization of processes through cross-process data availability. The creation of digital twins plays an important role in this. However, not all data relevant for a digital twin can be measured directly in the process. Therefore, methods are needed that enable the modelling of quantities that are difficult or impossible to measure directly in the process, such as the finite element method. In many companies, however, neither the know-how nor the necessary IT infrastructure for finite element simulations is available. External commissioning processes are also not suitable for achieving the goals of higher productivity and agility pursued with the digitization and networking of manufacturing processes. In this contribution, an architecture is presented that enables the fully automated use of finite element simulation as a service. The architecture is developed using the case study of fine blanking. First, the requirements of the architecture to be created are determined. Important characteristics of the architecture should be scalability as well as interfaces and means of payment suitable for machine communication. In addition, ensuring data integrity is an important requirement when creating the digital twin. Based on the identified requirements, an architecture is then presented that meets these requirements by using cloud computing and distributed ledger technologies and interfaces that can directly process measurement signals from the process and communicate with the architecture. Finally, the capability of the architecture is tested, possible applications and limitations are discussed, and future extensions are considered.

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“…form a family of contemporary semi-structured data (herein referred to as JSON-family data types or simply JSON). Together, they play a fundamental role in the modern computing infrastructure, ranging from cloud computing [24,45] and microservice architectures [29,61], to Internet of Things (IoT) [62] and NoSQL data stores [36,43]. For example, major cloud providers, such as Azure [5], AWS [3], Firebase [31], and Oracle Cloud [25], all support JSON-based cloud services.…”

Section: Introductionmentioning

confidence: 99%

Scalable Processing of Contemporary Semi-Structured Data on Commodity Parallel Processors - A Compilation-based Approach

Jiang

Sun

Farooq

et al. 2019

Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Syst

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JSON (JavaScript Object Notation) and its derivatives are essential in the modern computing infrastructure. However, existing software often fails to process such types of data in a scalable way, mainly for two reasons: (i) the processing often requires to build a memory-consuming parse tree; (ii) there exist inherent dependences in processing the data stream, preventing any data-level parallelization. Facing the challenges, developers often have to construct ad-hoc pre-parsers to split the data stream in order to reduce the memory consumption and increase the data parallelism. However, this strategy requires more programming efforts. Moreover, the pre-parsing itself is non-trivial to parallelize, thus introducing a new serial bottleneck. To solve the dilemma, this work introduces a scalable yet fully automatic solution-a compilation system, namely JPStream, that compiles standard JSONPath queries into parallel executables with bounded memory footprints. First, JPStream adopts a stream processing design that combines the querying and parsing into one pass, without generating any in-memory parse tree. To achieve this, JPStream uses a novel joint compilation technique that compiles the queries and the JSON syntax together into a single automaton. Furthermore, JPStream leverages the "enumerability" of automaton to break the dependences and reason about the transition rules to prune infeasible cases. It also features a module that learns data constraints from the input data to enhance the pruning. Evaluation on real-world JSON datasets with standard JSONPath queries shows that JPStream can reduce the memory consumption significantly, by up to 95%, meanwhile achieving near-linear speedup on multicore and manycore processors.

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Using JSON to manage communication between services in the Internet of Things

Cited by 34 publications

References 5 publications

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

Development of a hybrid DLT cloud architecture for the automated use of finite element simulation as a service for fine blanking

Scalable Processing of Contemporary Semi-Structured Data on Commodity Parallel Processors - A Compilation-based Approach

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