Data dissemination with interoperability in IoT network

Summary Internet of Things (IoT) is connected to heterogeneous devices. Efficient adaptive scheduling with encoding and decoding of data is an unaddressed issue in IoT. This paper processes the data under three major hierarchy: namely, adaptability, scheduling of data, and network coding for that da...

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Bibliographic Details
Published in:International journal of communication systems Vol. 33; no. 15
Main Authors: Rathanasalam, Radhika, Kanagasabai, Kulothungan
Format: Journal Article
Language:English
Published: Chichester Wiley Subscription Services, Inc 01.10.2020
Subjects:
adaptability
Adaptive control
Coding
Collision rates
Computer simulation
data dissemination
Decoding
Internet of Things
Internet of Things (IoT)
Interoperability
Network reliability
Neural networks
Polynomials
Redundancy
Scheduling
ISSN:1074-5351, 1099-1131
Online Access:Get full text
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Summary:Summary Internet of Things (IoT) is connected to heterogeneous devices. Efficient adaptive scheduling with encoding and decoding of data is an unaddressed issue in IoT. This paper processes the data under three major hierarchy: namely, adaptability, scheduling of data, and network coding for that data. The reliable access to the information is ensured by a device which is a primary eminence in IoT. Device must be able to adapt itself according to the changes in the network and to maintain its reliability as well as transparency and seamless access to the resources. To enhance the performance of the data dissemination, the scheduling process is investigated using the spatial grouping in IoT devices; this is achieved by joint spatial and code domain scheduling scheme, and the novel preconfigured access scheme is coined in order to minimize the collision rate of arbitrary access; during the data dissemination, the erasure coding scheme is used for the encoding and decoding of packets which provides optimal redundancy. We carried the simulation using Contiki and it shows the proposed Polymorphic Erasure Coding with Markov decision Adaptability and Neural networks (PECMAN) improves in terms of cost, overhead, and delay when compared with Multi‐user Shared Access (EMUSA), Polynomial‐time Optimal Storage Allocation (OSA) scheme, and Event‐Aware Back pressure Scheduling Scheme (EABS). The proposed Polymorphic Erasure Coding with Markov Decision Adaptability and Neural Networks (PECMAN) improves the performance of the data dissemination in networks. It uses Adaptive Markov Decision Process for identifying and allocating the available channels. The Scheduling with Neural Network using adaptive Programing helps in scheduling the available data, and the Polymorphic Erasure Coding Algorithm compresses the data and enhances the storage space efficiently. The proposed work improves in terms of cost, overhead, and delay when compared with Multiuser Shared Access (EMUSA), Polynomial time‐based optimal encoding and decoding Allocation (OSA) scheme, and Event‐Aware Back pressure Scheduling Scheme (EABS).
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ISSN:1074-5351
1099-1131
DOI:10.1002/dac.4513