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 wireless network communication, in-band full-duplex technique is a useful and important technique that can enlarge the whole throughput of the wireless networks. However, its use needs harsh environment. The successive interference cancellation can make several transmitters’ data be received simultaneously by the receiver, and can make the in-band full-duplex technique be used easily in reality. In this paper, we try to propose an optimal algorithm for increasing the throughput of full-duplex multi-hop wireless networks with successive interference cancellation, which we call the full-duplex successive interference cancellation (FD-SIC) wireless networks. We first describe the mathematical model for the FD-SIC wireless networks and show it is NP-hard in general. Then, we propose a heuristic algorithm, namely the use-up-link-capacity iterative (UULC-iterative) algorithm, for each node’s routing and transmitting scheme. Simulation results show that the proposed algorithm for FD-SIC wireless networks can achieve better throughput compared with SIC-only networks and the interference avoidance networks.
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