MR-MC无线传感器网络最小延迟数据聚集调度研究

doi:10.3969/j.issn.1000-436x.2014.10.022

通信学报 ›› 2014, Vol. 35 ›› Issue (10): 192-199.doi: 10.3969/j.issn.1000-436x.2014.10.022

MR-MC无线传感器网络最小延迟数据聚集调度研究

李金宝^1,²,王蒙^1,²,郭龙江^1,²

¹ 黑龙江大学计算机科学技术学院，黑龙江哈尔滨 150080
² 黑龙江省数据库与并行计算重点实验室，黑龙江哈尔滨 150080

出版日期:2014-10-25 发布日期:2017-06-14
基金资助:
国家自然科学基金资助项目;国家自然科学基金资助项目;黑龙江省杰出青年基金资助项目;黑龙江省高校科技创新团队建设计划基金资助项目;教育部新世纪优秀人才支持计划基金资助项目;黑龙江省教育厅高校新世纪优秀人才支持计划基金资助项目

Minimum latency data aggregation scheduling in MR-MC wireless sensor networks

Jin-bao LI^1,²,Meng WANG^1,²,Long-jiang GUO^1,²

¹ School of Computer Science and Technology,Heilongjiang University,Harbin 150080,China
² Key Laboratory of Database and Parallel Computing of Heilongjiang Province,Harbin 150080,China

Online:2014-10-25 Published:2017-06-14
Supported by:
The National Natural Science Foundation of China;The National Natural Science Foundation of China;Heilongjiang Province Founds for Distinguished Young Scientists;Program for Group of Science and Technology Innovation of Heilongjiang Educational Committee;Program for New Century Excellent Talents in University;Programs Foundation of Heilongjiang Educational Committee for New Century Excellent Talents in University

摘要/Abstract

摘要：

单radio单信道无线传感器网络的最小延迟聚集调度是一个NPC问题，已提出许多解决方案。在多radio多信道网络中，节点可以同时接收多个不同节点传输的数据，降低延迟。基于上述特点，考虑树结构约束，时槽、信道和radio分配等约束条件，将多radio多信道无线传感器网络最小延迟聚集调度问题定义为一个优化问题，并分解为建立聚集树和节点调度2个子问题，针对这2个子问题分别提出启发式算法。实验结果表明，提出的算法具有良好的性能。

关键词: 无线传感器网络, 信道, 数据聚集, 调度, 延迟

Abstract:

The problem of minimum latency data aggregation scheduling in single-radio single-channel wireless sensor networks is a NPC problem and many solutions have been proposed.In multi-radio multi-channel networks,the latency may be lower as a node may receive transmission data from other different nodes simultaneously.It formulates the minimum latency data aggregation scheduling into an optimization problem with joint consider of tree structure,time slot assignment,channel assignment and radio assignment.The problem is divided into constructing data aggregation tree and designing a node schedule subproblems.For each subproblem,heuristic algorithm has been proposed.The simulation results show that the proposed algorithm achieve good performance.

Key words: WSN, channel, data aggregation, scheduling, latency

李金宝,王蒙,郭龙江. MR-MC无线传感器网络最小延迟数据聚集调度研究[J]. 通信学报, 2014, 35(10): 192-199.

Jin-bao LI,Meng WANG,Long-jiang GUO. Minimum latency data aggregation scheduling in MR-MC wireless sensor networks[J]. Journal on Communications, 2014, 35(10): 192-199.

图/表 8

表1

图1

表2

图2

图3

图4

图5

图6

参考文献 15

[1]	CHENG S , LI J Z , CAI Z P . O(ε)-approximation to physical world by sensor networks[A]. IEEE INFOCOM 2013[C]. Turin,Italy, 2013. 3084-3092.
[2]	JI S L , CAI Z P . Distributed data collection and its capacity in asynchronous wireless sensor networks[A]. INFOCOM 2012[C]. Orlando,USA, 2012. 2113-2121.
[3]	JI S L , BEYAH R , CAI Z P . Snapshot/continuous data collection capacity for large-scale probabilistic wireless sensor networks[A]. INFOCOM 2012[C]. Orlando,USA, 2012. 1035-1043.
[4]	CHEN X J , HU X D , ZHU J M . Minimum data aggregation time problem in wireless sensor networks[J]. Mobile Ad-Hoc and Sensor Networks, 2005,37(4): 133-142.
[5]	KUO T W , TSAI M J . On the construction of data aggregation tree with minimum energy cost in wireless sensor networks:NP-completeness and approximation algorithms[A]. INFOCOM 2012[C]. Orlando,USA, 2012. 2591-2595.
[6]	CHAUHAN R , GUPTA V . Energy efficient sleep scheduled clustering& spanning tree based data aggregation in wireless sensor network[A]. Recent Advances in Information Technology (RAIT),2012 1st International Conference on IEEE[C]. Dhanbad,India, 2012. 536-541.
[7]	CHEN Z , YANG G , CHEN L ,et al. A load-balanced data aggregation scheduling for duty-cycled wireless sensor networks[A]. Cloud Computing Technology and Science (CloudCom),2012 IEEE 4th International Conference on IEEE[C]. Taipei,China, 2012. 888-893.
[8]	LUO D , ZHU X , WU X ,et al. Maximizing lifetime for the shortest path aggregation tree in wireless sensor networks[A]. INFOCOM2011[C]. Shanghai,China, 2011. 1566-1574.
[9]	LI Z , PENG Y , QIAO D ,et al. LBA:Lifetime balanced data aggregation in low duty cycle sensor networks[A]. INFOCOM2012[C]. Orlando,USA, 2012. 1844-1852.
[10]	HUANG S C H , WAN P J , VU C T ,et al. Nearly constant approximation for data aggregation scheduling in wireless sensor networks[A]. INFOCOM 2007,26th IEEE International Conference on Computer Communications[C]. Anchorage,AK, 2007. 366-372.
[11]	WAN P J , HUANG S C H , WANG L ,et al. Minimum-latency aggregation scheduling in multihop wireless networks[A]. Proceedings of the tenth ACM International Symposium on Mobile Ad Hoc Networking and Computing[C]. ACM, 2009. 185-194.
[12]	CHENG H , LI F , YANG L T ,et al. An efficient scheme for minimum-latency data aggregation in two-and three-dimensional wireless sensor networks[A]. Cloud and Green Computing (CGC),2012 Second International Conference on IEEE[C]. Xiangtan,China, 2012. 252-259.
[13]	LI D , ZHU Q , DU H ,et al. Conflict-free many-to-one data aggregation scheduling in multi-channel multi-hop wireless sensor networks[A]. Communications (ICC),2011 IEEE International Conference on IEEE[C]. Tyoto,Japan, 2011. 1-5.
[14]	BAGAA M , DERHAB A , LASLA N ,et al. Semi-structured and unstructured data aggregation scheduling in wireless sensor networks[A]. INFOCOM 2012[C]. IEEE, 2012. 2671-2675.
[15]	YAN M , JI S L , CAI Z P . Time efficient data aggregation scheduling in cognitive radio networks[A]. IEEE Global Telecommunications Conference (GLOBECOM 2013)[C]. Atlanta,USA, 2013. 1185-1190.

节点	干扰集	节点	干扰集	节点	干扰集
1	2,3,4	5	6,7	9	1,2,6,10
2	1,3,4	6	5,7	10	1,2,6,9
3	1,2,4	7	5,6	11	3,4,7,12
4	1,2,3	8	3	12	3,4,11

节点	调度	节点	调度
1	1,1,1,s,1	7	2,1,1,1,1
2	3,1,1,s,1	8	2,1,,1,4,1
3	1,2,2,s,2	9	1,1,1 ,5,1
4	3,2,2,s,2	10	1,2,2,5,2
5	2,2,2,2,2	11	1,1,1,8,1
6	1,1,1,2,1	12	1,2,2,8,2

MR-MC无线传感器网络最小延迟数据聚集调度研究

Minimum latency data aggregation scheduling in MR-MC wireless sensor networks

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 15

相关文章 15

Metrics

推荐阅读 0

[1]	王莉, 费爱国, 张平, 徐连明. 智能应急指挥通信网络新框架与关键技术研究[J]. 通信学报, 2023, 44(6): 1-11.
[2]	杨龙, 赵丽, 周雨晨, 贺冰涛, 陈健. 缓存辅助的协作NOMA携能传输[J]. 通信学报, 2023, 44(6): 77-89.
[3]	郑震, 严迎建, 蔡爵嵩, 刘燕江. 基于双样本KS检验的非特定TVLA方法[J]. 通信学报, 2023, 44(5): 137-147.
[4]	唐明, 胡一凡. Load-to-store: store buffer暂态窗口时间泄露的利用[J]. 通信学报, 2023, 44(4): 64-77.
[5]	鲁蔚锋, 李宁, 徐佳, 徐力杰, 徐建. 多接入边缘计算中相关性任务的联合调度算法[J]. 通信学报, 2023, 44(4): 87-98.
[6]	崔伟, 于颖, 于海霞, 陈超, 李云鹏. 基于IOC-CSMP的OFDM系统稀疏信道快速重构算法[J]. 通信学报, 2023, 44(2): 52-58.
[7]	赵庶旭, 韦萍, 王小龙. 多任务并发边缘计算环境中最优联盟结构生成策略[J]. 通信学报, 2023, 44(2): 172-184.
[8]	赵越, 李赞, 李冰, 郝本建. TDoA定位盲区分析与节点部署策略研究[J]. 通信学报, 2023, 44(1): 1-13.
[9]	李国军, 向翠玲, 叶昌荣, 王尊立. 短波数字信道化通信探测一体化快速建链方法[J]. 通信学报, 2023, 44(1): 89-102.
[10]	聂宏蕊, 李绍胜, 刘勇. 时间敏感网络中基于IEEE 802.1Qch标准的优化调度机制[J]. 通信学报, 2022, 43(9): 12-26.
[11]	李雷孝, 杜金泽, 林浩, 高昊昱, 杨艳艳, 高静. 区块链网络隐蔽信道研究进展[J]. 通信学报, 2022, 43(9): 209-223.
[12]	沙宗轩, 霍如, 孙闯, 汪硕, 黄韬. 基于深度强化学习的转发效能感知流量调度算法[J]. 通信学报, 2022, 43(8): 30-40.
[13]	曾嵘, 杭潇. 车联网环境下可重构智能反射面辅助无线信道估计算法[J]. 通信学报, 2022, 43(8): 142-150.
[14]	何世文, 袁军, 安振宇, 张敏, 黄永明, 张尧学. 基于图神经网络的联合用户调度与波束成形优化算法[J]. 通信学报, 2022, 43(7): 73-84.
[15]	王志勤, 江甲沫, 刘沛西, 曹晓雯, 李阳, 韩凯峰, 杜滢, 朱光旭. 6G联邦边缘学习新范式：基于任务导向的资源管理策略[J]. 通信学报, 2022, 43(6): 16-27.