Clustering is an efficient method for improving the communication performance of Vehicular Ad hoc NETworks (VANETs) that adopt Vehicle to Vehicle (V2V) communications. However, how to maximize the cluster stability while accounting for the high mobility of vehicles remains a challenging problem. In this paper, we first reconstruct the similarity function of the Affinity Propagation (AP) clustering algorithm by introducing communication-related parameters, so the vehicles with low relative mobility and good communication performance can easily be selected as cluster heads. Then, by formally defining three scaling functions, a weighted mechanism is designed to quantitatively assess the effect on the cluster stability when a vehicle joins it. Base on them, from the perspective of global balance, a new AP clustering algorithm for the whole clustering process is proposed. To ensure the validity of simulations, we use the vehicular mobility data generated on the realistic map of Cologne, Germany, and perform a series of simulations for eleven metrics commonly adopted in similar works. The results show that our proposed algorithm performs better than other algorithms in terms of the cluster stability, and it also effectively improves throughput and reduces packet loss rate of VANETs over the classical APROVE algorithm and the NMDP-APC algorithm. INDEX TERMS VANETs, V2V, clustering, affinity propagation. NOTATIONS CR One-hop communication radius of a vehicle V i Vehicle i, i is the ID of the vehicle az i Azimuth angle of V i Th az Threshold value for the difference of two azimuth angles v i Velocity of V i (x i , y i) Position of V i Th v Threshold value for the difference of two velocities v max Maximum velocity limit for the current road OCR i Owned communication rate of V i RCR i Required communication rate of V i NN L i Normal neighbor list of V i NN L i,j The jth list item of NN L i The associate editor coordinating the review of this manuscript and approving it for publication was Muhammad Alam. ER One-hop effective range of a vehicle d i,j Distance between V i and V j s (i, j) Similarity function between V i and V j r (i, j) Responsibility sent from V i to V j R i Responsibility list sent from V i to its onehop neighbor vehicles a (i, j) Availability sent from V j to V i A j Availability list sent from V j to its one-hop neighbor vehicles CH i Cluster head of V i ID (CH i) ID of V i 's cluster head CCH L i Candidate cluster head list of V i C i Cluster i whose cluster head is V i CM N C i Number of cluster members of C i CM N max Maximum number of cluster members of a cluster CM L i Cluster member list of V i whose state is Cluster Head (CH)
In order to decrease the fatigue of units caused by imbalance loads, the weight number assignment variable-pitch control strategy based on the azimuth angle signal of the pitch was presented according to the aerodynamics principle, wind shear characteristic and tower shadow effect. First the collective pitch angle is acquired according to the output power approximately equal to the rated power, then the blade pitch angles are redistributed through the related weight number according to each wind turbine blades under different wind speed. So the collective pitch angle was transformed into the individual variable pitch angle. At last, the collective pitches and individual pitches systems are designed, and mathematical models are built using MATLAB. The simulation results show that the proposed strategy not only ensure the pitch angle to change with the wind speed and obtain the stable output power, but also reduce the loads of blade and prolong service life of wind turbine, it has better dynamic performance and static error than general collective pitch control and easy to implement. Keywords-load; individual variable-pitch control; azimuth angle weight coefficient; wind shear effect; tower shadow effect; Matlab software
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