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.
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