基于相對移動性預(yù)測的k跳AdHoc網(wǎng)絡(luò)分簇算法

孟洛明; 江彥馥; 劉彥君; 蘇漢; 徐思雅; 亓峰

doi:10.11999/JEIT180192

基于相對移動性預(yù)測的k跳AdHoc網(wǎng)絡(luò)分簇算法

doi: 10.11999/JEIT180192 cstr: 32379.14.JEIT180192

1.
北京郵電大學(xué)網(wǎng)絡(luò)與交換技術(shù)國家重點(diǎn)實(shí)驗(yàn)室 ??北京 ??100876
2.
國網(wǎng)河北省電力有限公司 ??石家莊 ??050021

基金項(xiàng)目: 國家自然科學(xué)基金(61702048)

詳細(xì)信息

作者簡介:
孟洛明：男，1955年生，教授，研究方向?yàn)橥ㄐ跑浖途W(wǎng)絡(luò)管理

江彥馥：女，1993年生，碩士生，研究方向?yàn)锳dHoc網(wǎng)絡(luò)管理與優(yōu)化

劉彥君：男，1964年生，高級工程師，研究方向?yàn)殡娏νㄐ啪W(wǎng)絡(luò)管理

蘇漢：男，1977年生，高級工程師，研究方向?yàn)殡娏νㄐ啪W(wǎng)絡(luò)管理

徐思雅：女，1988年生，博士后，研究方向?yàn)橹悄茈娏νㄐ啪W(wǎng)絡(luò)管理與優(yōu)化

亓峰：男，1971年生，教授，研究方向?yàn)殡娏νㄐ啪W(wǎng)絡(luò)管理

通訊作者:
江彥馥　 paperJYF@163.com

中圖分類號: TN929.5
計(jì)量
- 文章訪問數(shù): 1392
- HTML全文瀏覽量: 703
- PDF下載量: 44
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2018-02-11
- 修回日期: 2018-08-13
- 網(wǎng)絡(luò)出版日期: 2018-08-21
- 刊出日期: 2018-12-01

Relative Mobility Prediction Based k-Hop Clustering Algorithm in AdHoc Networks

1.
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2.
State Grid Hebei Electric Power Company, Shijiazhuang 050021, China

Funds: The National Natural Science Foundation of China (61702048)

摘要

摘要: 針對網(wǎng)絡(luò)節(jié)點(diǎn)隨機(jī)移動造成的AdHoc網(wǎng)絡(luò)分簇結(jié)構(gòu)變化和路由失效問題，該文提出一種基于相對移動性預(yù)測的k跳分簇算法，分析和預(yù)測網(wǎng)絡(luò)節(jié)點(diǎn)運(yùn)動狀態(tài)，自適應(yīng)地調(diào)整分簇結(jié)構(gòu)，提高簇結(jié)構(gòu)穩(wěn)定性。首先，使用多普勒頻移計(jì)算節(jié)點(diǎn)間相對移動速度，預(yù)測節(jié)點(diǎn)移動性，得到節(jié)點(diǎn)間鏈路保持時(shí)間。然后，在簇形成階段，采用面向節(jié)點(diǎn)穩(wěn)定性的MAX-MIN啟發(fā)式算法，根據(jù)節(jié)點(diǎn)的平均鏈路保持時(shí)間對簇首進(jìn)行選擇。進(jìn)而，在簇保持階段，提出一種基于節(jié)點(diǎn)運(yùn)動狀態(tài)的網(wǎng)絡(luò)自適應(yīng)調(diào)整算法，一方面調(diào)整節(jié)點(diǎn)信息數(shù)據(jù)發(fā)送周期以平衡數(shù)據(jù)開銷和精確度，另一方面通過預(yù)測節(jié)點(diǎn)間鏈路通斷情況調(diào)整分簇結(jié)構(gòu)，以減少鏈路失效時(shí)的鏈路重建時(shí)間，提高網(wǎng)絡(luò)運(yùn)行質(zhì)量。仿真實(shí)驗(yàn)表明，所提算法可以有效延長簇首持續(xù)時(shí)間，提高簇結(jié)構(gòu)在動態(tài)環(huán)境下的穩(wěn)定性。
- AdHoc網(wǎng)絡(luò) /
- 分簇 /
- 移動性預(yù)測 /
- 多普勒頻移 /
- MAX-MIN算法
Abstract: To solve the problem of network structure change and route failure caused by random movement of network nodes, a relative mobility prediction based k-hop clustering algorithm is proposed, the movement of nodes are analyzed and predicted, the cluster structure is adjusted adaptively, the stability of cluster structure is improved. First, the Doppler shift is used to calculate the relative moving speed and obtain the link expiration time between nodes. Then, during the cluster formation stage, the MAX-MIN heuristic algorithm is used to select the cluster head according to the average link expiration time of the node. Furthermore, during the cluster maintenance stage, a network adaptive adjustment method is proposed based on node motion. On the one hand, the node information transmission cycle is adjusted to balance the data overhead and accuracy; On the other hand, the cluster structure is adjusted by predicting the link disconnection to reduce link reconstruction time and improve the quality of network operation. Simulation results show that the proposed algorithm can effectively prolong the duration of cluster head and improve the stability of cluster structure in dynamic environment.
- AdHoc network /
- Clustering /
- Mobility prediction /
- Doppler shift /
- MAX-MIN algorithm

HTML全文

圖 1 2跳AdHoc網(wǎng)絡(luò)分簇結(jié)構(gòu)

下載: 全尺寸圖片幻燈片

圖 2 節(jié)點(diǎn)相對位置示意圖

下載: 全尺寸圖片幻燈片

圖 3 KMPC簇首選擇過程

下載: 全尺寸圖片幻燈片

圖 4 簇首持續(xù)時(shí)間隨節(jié)點(diǎn)總數(shù)的變化(k=2)

下載: 全尺寸圖片幻燈片

圖 5 簇首持續(xù)時(shí)間隨最大運(yùn)動速度的變化(k=2)

下載: 全尺寸圖片幻燈片

圖 6 簇維護(hù)開銷

下載: 全尺寸圖片幻燈片

圖 7 簇首切換時(shí)間

下載: 全尺寸圖片幻燈片

圖 8 節(jié)點(diǎn)運(yùn)動速度隨時(shí)間的變化

下載: 全尺寸圖片幻燈片

參考文獻(xiàn)(16)

KASHYAP V K, ASTYA R, NAND P, et al. Comparative study of AODV and DSR routing protocols in wireless sensor network using NS-2 simulator[C]. International Conference on Computing, Communication and Automation, Greater Noida, India, 2017: 687–690.

AHN S and KIM C K. An adaptive mechanism to resolve the DSR cached route reply storm of multi-hop wireless networks[C]. International Conference on Ubiquitous and Future Networks, Milan, Italy, 2017: 1022–1024.

張軍強(qiáng), 王汝傳, 黃海平. 基于分簇的無線多媒體傳感器網(wǎng)絡(luò)數(shù)據(jù)聚合方案研究[J]. 電子與信息學(xué)報(bào), 2014, 36(1): 8–14 doi: 10.3724/SP.J.1146.2012.00933

ZHANG Junqiang, WANG Ruchuan, and HUANG Haiping. Research on cluster-based data aggregation for wireless multimedia sensor networks[J]. Journal of Electronics&Information Technology, 2014, 36(1): 8–14 doi: 10.3724/SP.J.1146.2012.00933

CHAI Yuan and SHI Wenxiao. Access-enhanced hybrid routing protocol for hybrid wireless mesh network[C]. International Conference on Communication Software and Networks, Guangzhou, China, 2017: 138–141.

牛曉光, 崔莉, 黃長城. 移動自組織網(wǎng)絡(luò)中基于優(yōu)化分簇的混合路由協(xié)議[J]. 通信學(xué)報(bào), 2010, 31(10): 58–67 doi: 10.3969/j.issn.1000-436X.2010.10.007

NIU Xiaoguang, CUI Li, and HUANG Changcheng. Hybrid optimal cluster routing protocol for mobile ad hoc network[J]. Journal of Communication, 2010, 31(10): 58–67 doi: 10.3969/j.issn.1000-436X.2010.10.007

ABUASHOUR A and KADOCH M. Performance improvement of cluster-based routing protocol in VANET[J]. IEEE Access, 2017, 99(5): 15354–15371 doi: 10.1109/ACCESS.2017.2733380

張浩軍, 朱艷琴, 紀(jì)其進(jìn). 面向異構(gòu)網(wǎng)絡(luò)的動態(tài)負(fù)載均衡算法及其收斂性分析[J]. 電子與信息學(xué)報(bào), 2013, 35(9): 2247–2253 doi: 10.3724/SP.J.1146.2012.01360

ZHANG Haojun, ZHU Yanqin, and JI Qijin. A diffusion-based dynamic load balancing algorithm for heterogeneous networks and its convergence analysis[J]. Journal of Electronics&Information Technology, 2013, 35(9): 2247–2253 doi: 10.3724/SP.J.1146.2012.01360

NARENDRAN M and PRAKASAM P. Optimized lowest ID in wireless sensor network using Invasive Weed Optimization (IWO)-Genetic Algorithm (GA)[C]. International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies, Chennai, India, 2017: 1–6.

NGUYEN V D, KIM O T T, DANG D N M, et al. Application of the lowest-ID algorithm in cluster-based TDMA system for VANETs[C]. International Conference on Information Networking, Cambodia, Cambodia, 2015: 25–30.

ZHANG Jinbei, FU Luoyi, WANG Qi, et al. Connectivity analysis in wireless networks with correlated mobility and cluster scalability[J]. IEEE/ACM Transactions on Networking, 2017, 25(4): 2375–2390 doi: 10.1109/TNET.2017.2692774

HAN S, LEE H, KIM J, et al. On the connectivity in opportunistic D2D networks with hierarchical and non-hierarchical clustering[C]. IEEE Global Communications Conference Workshops, Washington DC, USA, 2016: 1–6.

CHEN Geng, NOCETTI F G, GONZALEZ J S, et al. Connectivity based k-hop clustering in wireless networks[C]. International Conference on System Sciences, Hawaii, USA, 2002: 2450–2459.

AMIS A D, PRAKASH R, VUONG T, et al. Max min D-cluster formation in wireless ad hoc networks[C]. IEEE International Conference on Computer Communications, Tel Aviv, Israel, 2000: 32–41.

LENG Supeng, ZHANG Yan, CHEN Xiaohua, et al. A novel k-hop compound metric based clustering scheme for ad hoc wireless networks[J]. IEEE Transactions on Wireless Communications, 2009, 8(1): 367–375 doi: 10.1109/T-WC.2009.080186

SAKHAEE E and JAMALIPOUR A. A new stable clustering scheme for pseudo-linear highly mobile ad hoc networks[C]. IEEE Global Communications Conference, Washington DC, USA, 2007: 1169–1173.

MA Xufeng. A k-hop cluster maintaining mechanism for mobile ad hoc networks[C]. International Conference on Wireless Communications, Networking and Mobile Computing, Wuhan, China, 2011: 1–4.

相關(guān)文章

施引文獻(xiàn)

資源附件(0)

訪問統(tǒng)計(jì)