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Adaptive Data Transmission Optimization in Internet of Things
Saniya Zahoor1, Roohie Naaz Mir2

1Saniya Zahoor*, Department of Computer Science and Engineering, NIT Srinagar, India.
2Roohie Naaz Mir, Department of Computer Science and Engineering, NIT Srinagar, India.

Manuscript received on November 17, 2019. | Revised Manuscript received on 26 November, 2019. | Manuscript published on December 10, 2019. | PP: 1956-1964 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7859129219/2019©BEIESP | DOI: 10.35940/ijitee.B7859.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In most of the IoT applications, exchange of data among various physical and virtual IoT devices having different data flows, energy and delay constraints is a challenging task in such environments. This imposes constraints in IoT applications at the node, network and application level, and to meet such constraints, we propose an adaptive IoT system that adapts to different data flows in IoT network having different time and energy constraints. The proposed scheme consists of two algorithms viz., coarse grain transmission path algorithm for low-deadline IoT applications, where time, traffic load and energy consumption are considered as the main parameters; and a fine-grain algorithm for high-deadline situations, where low latency and power constraints are the important performance parameters. Finally, the performance of proposed strategy is evaluated by simulation. The results of the proposed scheme in this paper outperform the existing algorithms in terms of energy, power, number of alive nodes and delay. The proposed scheme is used for data transmission optimization in delay-sensitive resource-constrained IoT applications. 
Keywords: Coarse-Grain Transmission, Data Aggregation, Edge, Fine-Grain Transmission, Internet of Things.
Scope of the Article: Internet of Things.