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http://dx.doi.org/10.5762/KAIS.2020.21.7.12

Data Congestion Control Using Drones in Clustered Heterogeneous Wireless Sensor Network  

Kim, Tae-Rim (LIG Nex1)
Song, Jong-Gyu (LIG Nex1)
Im, Hyun-Jae (LIG Nex1)
Kim, Bum-Su (LIG Nex1)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.7, 2020 , pp. 12-19 More about this Journal
Abstract
The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.
Keywords
Wireless Sensor Network; Clustered Heterogeneous Network; Data Congestion Control; Data Congestion Map; System Modeling; Sensor Node; Cluster Head; Mobile Sink;
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