Conference proceeding
Real-Time Distributed Computing at Network Edges for Large Scale Industrial IoT Networks
2018 IEEE World Congress on Services (SERVICES), pp 63-64
Jul 2018
Abstract
Low-cost, real-time digital signal processors (DSPs) embedded in generic Internet of Things (IoT) edge devices can make significant contributions to distributed edge computing for industrial IoT (IIoT) networks. The DSP considered in this paper is the Texas Instruments (TI) TMS320C28x DSP (C28x). At the edge of the network, the C28x is programmed using low-level Embedded C programming language to construct the Morlet wavelet. Our implementation at this layer is the first known construction of the Morlet wavelet for C28x DSP using Embedded C. At the fog layer, near the edge of the IoT network, where more computing resources exist, the wavelet is then convolved with healthcare (electrocardiogram) and electrical network signals, using Matlab to reduce signal noise, and to identify important parts of examined signals. Convolution results indicates that the distributed computing approach for low-cost generic devices considered in this paper is suitable for use in large IIoT networks.
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Details
- Title
- Real-Time Distributed Computing at Network Edges for Large Scale Industrial IoT Networks
- Creators
- Emmanuel Oyekanlu - Drexel UniversityKevin Scoles - Drexel UniversityIEEE
- Publication Details
- 2018 IEEE World Congress on Services (SERVICES), pp 63-64
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000518201500032
- Scopus ID
- 2-s2.0-85057410199
- Other Identifier
- 991019168906104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Theory & Methods