Relative Mobility Prediction Based k-Hop Clustering Algorithm in AdHoc Networks
-
摘要: 针对网络节点随机移动造成的AdHoc网络分簇结构变化和路由失效问题，该文提出一种基于相对移动性预测的k跳分簇算法，分析和预测网络节点运动状态，自适应地调整分簇结构，提高簇结构稳定性。首先，使用多普勒频移计算节点间相对移动速度，预测节点移动性，得到节点间链路保持时间。然后，在簇形成阶段，采用面向节点稳定性的MAX-MIN启发式算法，根据节点的平均链路保持时间对簇首进行选择。进而，在簇保持阶段，提出一种基于节点运动状态的网络自适应调整算法，一方面调整节点信息数据发送周期以平衡数据开销和精确度，另一方面通过预测节点间链路通断情况调整分簇结构，以减少链路失效时的链路重建时间，提高网络运行质量。仿真实验表明，所提算法可以有效延长簇首持续时间，提高簇结构在动态环境下的稳定性。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.
-
Key words:
- AdHoc network /
- Clustering /
- Mobility prediction /
- Doppler shift /
- MAX-MIN algorithm
-
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. 张军强, 王汝传, 黄海平. 基于分簇的无线多媒体传感器网络数据聚合方案研究[J]. 电子与信息学报, 2014, 36(1): 8–14 doi: 10.3724/SP.J.1146.2012.00933ZHANG 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. 牛晓光, 崔莉, 黄长城. 移动自组织网络中基于优化分簇的混合路由协议[J]. 通信学报, 2010, 31(10): 58–67 doi: 10.3969/j.issn.1000-436X.2010.10.007NIU 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 张浩军, 朱艳琴, 纪其进. 面向异构网络的动态负载均衡算法及其收敛性分析[J]. 电子与信息学报, 2013, 35(9): 2247–2253 doi: 10.3724/SP.J.1146.2012.01360ZHANG 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. -
下载:
图(8)
计量
- 文章访问数: 1294
- HTML全文浏览量: 603
- PDF下载量: 43
- 被引次数: 0
下载:
