INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS Int. J. Commun. Syst. 2013; 26:888–911 Published online 22 November 2011 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/dac.1376 Distributed topology control in large-scale hybrid RF/FSO networks: SIMT GPU-based particle swarm optimization approach Osama Awwad 1 , Ala Al-Fuqaha 1, * ,† , Ghassen Ben Brahim 2 , Bilal Khan 3 and Ammar Rayes 4 1 Computer Science Department, Western Michigan University, Kalamazoo, MI 49008 USA 2 Integrated Defense Systems, Boeing Company, Huntington Beach, CA 92647 USA 3 John Jay College, City University of New York, New York, NY 10019 USA 4 Advanced Support Systems, Cisco Systems, San Jose, CA 95134 USA SUMMARY The tremendous power of graphics processing unit (GPU) computing relative to prior CPU-only architec- tures presents new opportunities for efficient solutions of previously intractable large-scale optimization problems. Although most previous work in this field focused on scientific applications in the areas of medicine and physics, here we present a Compute Unified Device Architecture-based (CUDA) GPU solu- tion to solve the topology control problem in hybrid radio frequency and free space optics wireless mesh networks by adapting and adjusting the transmission power and the beam-width of individual nodes accord- ing to QoS requirements. Our approach is based on a stochastic global optimization technique inspired by the social behavior of flocking birds — so-called ‘particle swarm optimization’ — and was implemented on the NVIDIA GeForce GTX 285 GPU. The implementation achieved a performance speedup factor of 392 over a CPU-only implementation. Several innovations in the memory/execution structure in our approach enabled us to surpass all prior known particle swarm optimization GPU implementations. Our results pro- vide a promising indication of the viability of GPU-based approaches towards the solution of large-scale optimization problems such as those found in radio frequency and free space optics wireless mesh network design. Copyright © 2011 John Wiley & Sons, Ltd. Received 9 February 2010; Revised 29 September 2011; Accepted 30 September 2011 KEY WORDS: CUDA; GPU; hybrid RF/FSO; PSO; QoS; topology control; wireless mesh networks 1. INTRODUCTION Adjusting the beam-width and the transmission power in hybrid radio frequency and free space optics (RF/FSO) mesh networks presents a competing local versus global trade-off. A node with a large beam width or high transmission power usually has more nodes in the transmission range and hence a higher degree, which reduces the average global path length, thus minimizing the end-to-end delay of multihop connections. However, a higher node degree implies higher link layer interference, which reduces local throughput because of high channel contention. On the other hand, nodes that employ a narrow beam width or low transmission power have a lower number of nodes in their transmission range, hence a lower node degree — this results in higher average global path lengths and in turn, high end-to-end delay. However, a lower node degree implies lower interference, which tends to ameliorate local throughput because channel contention decreases. As such, it appears that there is a trade-off and our objective is to construct a robust topology by minimizing the transmission power, adapting the beam width, and selecting different channels such that we meet joint throughput and end-to-end delay requirements. *Correspondence to: Ala Al-Fuqaha, Computer Science Department, Western Michigan University, Kalamazoo, MI 49008 USA. † E-mail: alfuqaha@cs.wmich.edu Copyright © 2011 John Wiley & Sons, Ltd.