scholarly journals Large-Scale Feedforward Neural Network Optimization by a Self-Adaptive Strategy and Parameter Based Particle Swarm Optimization

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 52473-52483 ◽  
Author(s):  
Yu Xue ◽  
Tao Tang ◽  
Alex X. Liu
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Network Optimization ◽  
Large Scale ◽  
Particle Swarm ◽  
Adaptive Strategy ◽  
Feedforward Neural Network ◽  
Swarm Optimization ◽  
Neural Network Optimization ◽  
Self Adaptive

Self Adaptive Particle Swarm Optimization for Efficient Virtual Machine Provisioning in Cloud

2012 ◽  
pp. 88-107 ◽  
Author(s):  
R. Jeyarani ◽  
N. Nagaveni ◽  
R. Vasanth Ram
Keyword(s):  
Particle Swarm Optimization ◽  
Large Scale ◽  
Virtual Machines ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Resource Dynamics ◽  
Virtual Machine Provisioning ◽  
Dynamic Resource ◽  
Self Adaptive

Cloud Computing provides dynamic leasing of server capabilities as a scalable, virtualized service to end users. The discussed work focuses on Infrastructure as a Service (IaaS) model where custom Virtual Machines (VM) are launched in appropriate servers available in a data-center. The context of the environment is a large scale, heterogeneous and dynamic resource pool. Nonlinear variation in the availability of processing elements, memory size, storage capacity, and bandwidth causes resource dynamics apart from the sporadic nature of workload. The major challenge is to map a set of VM instances onto a set of servers from a dynamic resource pool so the total incremental power drawn upon the mapping is minimal and does not compromise the performance objectives. This paper proposes a novel Self Adaptive Particle Swarm Optimization (SAPSO) algorithm to solve the intractable nature of the above challenge. The proposed approach promptly detects and efficiently tracks the changing optimum that represents target servers for VM placement. The experimental results of SAPSO was compared with Multi-Strategy Ensemble Particle Swarm Optimization (MEPSO) and the results show that SAPSO outperforms the latter for power aware adaptive VM provisioning in a large scale, heterogeneous and dynamic cloud environment.

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