Computer Science ›› 2019, Vol. 46 ›› Issue (6): 107-111.doi: 10.11896/j.issn.1002-137X.2019.06.015

Previous Articles     Next Articles

Hybrid-based Network Congestion Control Routing Algorithm for LLN

WANG Hua-hua, ZHOU Yuan-wen, LIU Jiang-bing   

  1. (Key Laboratory of Mobile Communications Technology of Chongqing,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
  • Received:2018-04-24 Published:2019-06-24

Abstract: Because the existing network congestion control routing algorithms in low power and lossy networks (LLN) cannot alleviate the current network congestion effectively,this paper proposed a hybrid-based network congestion control routing algorithm (HNCCRA).This algorithm mainly contains three innovations.Firstly,to reduce the probability of network congestion effectively,each node selects the parent node according to the load state of its alternative parent node in the process of network construction.Secondly,to avoid the problem that the child node of network congestion node selects the alternative parent node with a heavy traffic state as the new parent node when changing the data transmission path,each node notifies its own load status in real time during the maintenance process of the network topology.Finally,for alleviating the current network congestion effectively,network congestion control is conducted by combining the idea of data flow and the way of replacing the data transmission paths.The simulation results show that HNCCRA algorithm can improve the performance of all aspects of the network effectively compared with the existing network congestion control routing algorithm in LLN.Specifically,the network congestion probability is decreased by 19.89%,the average throughput of sink node is increased by 11.35%,and the network lifetime is extended by 9.75%.

Key words: Hybrid, Low power and lossy networks (LLN), Network congestion control, Routing algorithm

CLC Number: 

  • TP393
[1]CHEN H M,SHI H L,LI M,et al.Service Middleware for Internet of Things:Challenges and Approaches[J].Chinese Journal of Computers,2017,40(8):1725-1749.(in Chinese)
陈海明,石海龙,李勐,等.物联网服务中间件:挑战与研究进展[J].计算机学报,2017,40(8):1725-1749.
[2]RIZZI M,FERRARI P,FLAMMINI A,et al.Evaluation of the IoT LoRaWAN Solution for Distributed Measurement Applications[J].IEEE Transactions on Instrumentation and Measurement,2017,66(12):3340-3349.
[3]KHALFI B,HAMDAOUI B,GUIZANI M.Extracting and Exploiting Inherent Sparsity for Efficient IoT Support in 5G:Challenges and Potential Solutions[J].IEEE Wireless Communications,2017,24(5):68-73.
[4]KIM H S,KIM H,LEE M S,et al.A measurement study of TCP over RPL in low-power and lossy networks[J].Journal of Communications and Networks,2015,17(6):647-655.
[5]PAEK J.Fast and Adaptive Mesh Access Control in Low-Power and Lossy Networks[J].IEEE Internet of Things Journal,2015,2(5):435-444.
[6]LIU X,SHENG Z,YIN C,et al.Performance analysis of Routing Protocol for Low power and Lossy Networks(RPL) in large scale networks[J].IEEE Internet of Things Journal,2017,4(6):2172-2185.
[7]WINTER T,THUBERT P,BRANDT A,et al.RPL:IPv6 routing protocol for low-power and lossy networks:RFC 6550 [S].IETF,2012:1-157.
[8]WAN C Y,EISENMAN S B,CAMPBELL A T.Energy-efficient congestion detection and avoidance in sensor networks[J].ACM Transactions on Sensor Networks(TOSN),2011,7(4):1-32.
[9]DESHPANDE V S,CHAVAN P P,WADHAI V M,et al.Congestion control in Wireless Sensor Networks by using Differed Reporting Rate[C]∥Proceedings of the 2012 2nd World Congress on Information and Communication Technologies(WICT).Trivandrum:IEEE Press,2012:209-213.
[10]JIN J,PALANISWAMI M,KRISHNAMACHARI B.Rate control for heterogeneous wireless sensor networks:characterization,algorithms and performance[J].Computer Networks,2012,56(17):3783-3794.
[11]KIM H S,KIM H,PAEK J,et al.Load balancing under heavy traffic in RPL routing protocol for low power and lossy networks[J].IEEE Transactions on Mobile Computing,2017,16(4):964-979.
[12]DJAMAA B,RICHARDSON M.Optimizing the Trickle Algorithm[J].IEEE Communications Letters,2015,19(5):819-822.
[13]MA C,SHEU J P,HSU C X.A game theory based congestion control protocol for wireless personal area networks[J/OL].Journal of Sensors.http://dx.doi.org/10.1155/2016/6168535.
[14]YAO Y K,LIU J B,REN Z,et al.High-Efficient RPL routing protocol for centralized network congestion control[J].Systems Engineering and Electronics,2017,39(12):2810-2816.(in Chinese)
姚玉坤,刘江兵,任智,等.集中式网络拥塞控制的高效 RPL 路由协议[J].系统工程与电子技术,2017,39(12):2810-2816.
[1] LYU You, WU Wen-yuan. Privacy-preserving Linear Regression Scheme and Its Application [J]. Computer Science, 2022, 49(9): 318-325.
[2] WANG Lei, LI Xiao-yu. LBS Mobile Privacy Protection Scheme Based on Random Onion Routing [J]. Computer Science, 2022, 49(9): 347-354.
[3] LIU Gao-cong, LUO Yong-ping, JIN Pei-quan. Accelerating Persistent Memory-based Indices Based on Hotspot Data [J]. Computer Science, 2022, 49(8): 26-32.
[4] PIAO Yong, ZHU Si-yuan, LI Yang. Hybrid Housing Resource Recommendation Based on Combined User and Location Characteristics [J]. Computer Science, 2022, 49(6A): 733-737.
[5] LI Sun, CAO Feng. Analysis and Trend Research of End-to-End Framework Model of Intelligent Speech Technology [J]. Computer Science, 2022, 49(6A): 331-336.
[6] LIU Peng, LIU Bo, ZHOU Na-qin, PENG Xin-yi, LIN Wei-wei. Survey of Hybrid Cloud Workflow Scheduling [J]. Computer Science, 2022, 49(5): 235-243.
[7] YAN Lei, ZHANG Gong-xuan, WANG Tian, KOU Xiao-yong, WANG Guo-hong. Scheduling Algorithm for Bag-of-Tasks with Due Date Constraints on Hybrid Clouds [J]. Computer Science, 2022, 49(5): 244-249.
[8] JIANG Rui, XU Shan-shan, XU You-yun. New Hybrid Precoding Algorithm Based on Sub-connected Structure [J]. Computer Science, 2022, 49(5): 256-261.
[9] LIU Jiang, LIU Wen-bo, ZHANG Ju. Hybrid MPI+OpenMP Parallel Method on Polyhedral Grid Generation in OpenFoam [J]. Computer Science, 2022, 49(3): 3-10.
[10] WU Yu-kun, LI Wei, NI Min-ya, XU Zhi-cheng. Anomaly Detection Model Based on One-class Support Vector Machine Fused Deep Auto-encoder [J]. Computer Science, 2022, 49(3): 144-151.
[11] GENG Hai-jun, WANG Wei, YIN Xia. Single Node Failure Routing Protection Algorithm Based on Hybrid Software Defined Networks [J]. Computer Science, 2022, 49(2): 329-335.
[12] TAO Xing-peng, XU Hong-hui, ZHENG Jian-wei, CHEN Wan-jun. Hyperspectral Image Denoising Based on Nonconvex Low Rank Matrix Approximation and TotalVariation Regularization [J]. Computer Science, 2021, 48(8): 125-133.
[13] LI Yan, FAN Bin, GUO Jie, LIN Zi-yuan, ZHAO Zhao. Attribute Reduction Method Based on k-prototypes Clustering and Rough Sets [J]. Computer Science, 2021, 48(6A): 342-348.
[14] CHEN Jing-yu, GUO Zhi-jun, YIN Ya-kun. Full Traversal Path Planning and System Design of Intelligent Lawn Mower Based on Hybrid Algorithm [J]. Computer Science, 2021, 48(6A): 633-637.
[15] LIU Meng-yang, WU Li-juan, LIANG Hui, DUAN Xu-lei, LIU Shang-qing, GAO Yi-bo. A Kind of High-precision LSTM-FC Atmospheric Contaminant Concentrations Forecasting Model [J]. Computer Science, 2021, 48(6A): 184-189.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!