Distributed topology control in large‐scale hybrid RF/FSO networks: SIMT GPU‐based particle swarm optimization approach. (22nd November 2011)
- Record Type:
- Journal Article
- Title:
- Distributed topology control in large‐scale hybrid RF/FSO networks: SIMT GPU‐based particle swarm optimization approach. (22nd November 2011)
- Main Title:
- Distributed topology control in large‐scale hybrid RF/FSO networks: SIMT GPU‐based particle swarm optimization approach
- Authors:
- Awwad, Osama
Al‐Fuqaha, Ala
Ben Brahim, Ghassen
Khan, Bilal
Rayes, Ammar - Abstract:
- <abstract abstract-type="main" id="dac1376-abs-0001"> <title>SUMMARY</title> <p id="dac1376-para-0006">The tremendous power of graphics processing unit (GPU) computing relative to prior CPU‐only architectures 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 solution 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 according 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 provide 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 &amp; Sons, Ltd.</p><abstract abstract-type="main" id="dac1376-abs-0001"> <title>SUMMARY</title> <p id="dac1376-para-0006">The tremendous power of graphics processing unit (GPU) computing relative to prior CPU‐only architectures 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 solution 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 according 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 provide 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 &amp; Sons, Ltd.</p> </abstract> … (more)
- Is Part Of:
- International journal of communication systems. Volume 26:Number 7(2013:Jul.)
- Journal:
- International journal of communication systems
- Issue:
- Volume 26:Number 7(2013:Jul.)
- Issue Display:
- Volume 26, Issue 7 (2013)
- Year:
- 2013
- Volume:
- 26
- Issue:
- 7
- Issue Sort Value:
- 2013-0026-0007-0000
- Page Start:
- 888
- Page End:
- 911
- Publication Date:
- 2011-11-22
- Subjects:
- Telecommunication systems -- Periodicals
621.382 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/dac.1376 ↗
- Languages:
- English
- ISSNs:
- 1074-5351
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.172515
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 3637.xml