TY - GEN
T1 - Distributed parallelization of greedy Mobile Network Optimization algorithms
AU - Ye, Yuanzhou
AU - Cadenas, Oswaldo
AU - Megson, Graham
PY - 2013
Y1 - 2013
N2 - The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.
AB - The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.
KW - Distributed and Parallel Computing
KW - Dynamic Network Optimization
KW - Inter Process Communications
KW - Mobile Network Optimization
KW - Quality of Service
UR - http://www.scopus.com/inward/record.url?scp=84893398467&partnerID=8YFLogxK
U2 - 10.1109/SoftCOM.2013.6671867
DO - 10.1109/SoftCOM.2013.6671867
M3 - Conference contribution
AN - SCOPUS:84893398467
SN - 9789532900439
T3 - 2013 21st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2013
BT - 2013 21st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2013
T2 - 2013 21st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2013
Y2 - 18 September 2013 through 20 September 2013
ER -