Comprehensive Mobility Prediction Based Clustering Algorithm for Ad Hoc UAV Networks
Yunlong Yu, Le Ru, Kun Fang, Xufeng Jia
Available Online March 2016.
- https://doi.org/10.2991/icmmct-16.2016.121How to use a DOI?
- ad hoc UAV networks, highly dynamic, large scale, comprehensive mobility prediction, clustering
- Clustering is an effective method which can increase the performance of large-scale ad hoc UAV networks. However, the ad hoc UAV networks have the feature of high mobility and quick network topology change, using conventional clustering algorithm will lead to the decrease of link connection lifetime and cluster head lifetime, frequent updates of cluster topology would cause the instability of cluster structure and the increase of control overhead. In order to solve the problem that traditional clustering algorithm cannot adapt to the highly dynamic large-scale ad hoc UAV networks, CMPC (Comprehensive Mobility Prediction Based Clustering) algorithm is proposed. This algorithm predicts the comprehensive relative mobility between two UAVs which can get from the signal feature of Hello packets. Making use of the comprehensive stability between two UAVs which derives from comprehensive mobility between two UAVs, we can conduct the cluster formation and maintenance effectively. Simulations have shown that the CMPC algorithm outperforms the classical clustering algorithm in terms of average link connection lifetime and average cluster head lifetime, which can make the cluster structure more stable. As a result, this algorithm is ideal for highly dynamic large-scale ad hoc UAV networks.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yunlong Yu AU - Le Ru AU - Kun Fang AU - Xufeng Jia PY - 2016/03 DA - 2016/03 TI - Comprehensive Mobility Prediction Based Clustering Algorithm for Ad Hoc UAV Networks BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology PB - Atlantis Press SP - 600 EP - 613 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-16.2016.121 DO - https://doi.org/10.2991/icmmct-16.2016.121 ID - Yu2016/03 ER -