Energy-aware multi-layer flexible optical network operation

2015 ◽  
Author(s):  
Vasileios Gkamas ◽  
Konstantinos Christodoulopoulos ◽  
Emmanouel Varvarigos
Keyword(s):  
Optical Network ◽  
Energy Aware ◽  
Network Operation

Energy Aware Optimized Routing Protocols for Wireless Ad Hoc Sensor Network

2017 ◽  
pp. 156-183 ◽  
Author(s):  
Alok R. Prusty ◽  
Srinivas Sethi ◽  
Ajit Kumar Nayak
Keyword(s):  
Sensor Network ◽  
Ad Hoc ◽  
Human Life ◽  
Dynamic Environment ◽  
Sensor Nodes ◽  
Transmission Range ◽  
Energy Aware ◽  
Hierarchical Routing ◽  
Ongoing Research ◽  
Network Operation

Advancement in wireless technology made human life become simple and easy going. Wireless Ad Hoc Sensor Network (WASN) is one of the friendly wireless networks used to monitor the most unfriendly and ever changing dynamic environment that restricts continuous human attention. WASN has drawn significant attentions due to its unique capabilities to deal with complex network operation in highly resource constrained network construct. This ad hoc and unstructured deployment of tiny sensor nodes operate with controlled transmission range, processing capabilities, as well as very limited battery backup. The severe power depletion affects the existence of active nodes. Hence, data forwarding and reliable packet routing in such phenomenon oriented network becoming a challenge. In this chapter the clustering and hierarchical routing approaches for WASN environment has been briefly presented followed by some optimization strategies applicable to cluster routing process. This chapter can help researchers to think fresh dimensions of ongoing research in WASN cluster routing.

Control Spatial Load Allocation and Resource Usage in Optical Communication Network

2011 ◽  
Vol 474-476 ◽  
pp. 1487-1490
Author(s):  
Ning Zhang ◽  
Xue Mei Xu
Keyword(s):  
Optical Communication ◽  
Performance Optimization ◽  
Traffic Engineering ◽  
Traffic Management ◽  
Optical Network ◽  
Wavelength Assignment ◽  
Network Utilization ◽  
Network Operation ◽  
Main Factors ◽  
Traffic Balance

In this paper, a new design for the network traffic balance method is presented. In optical network, the wavelength is one of the most important resources, and wavelength assignment is one of the main factors that affect the efficiency of the network utilization. The performance optimization of networks is actually a control problem. Traffic engineering should provide sufficient control in an adaptive feedback control system. The tasks of a controller consist of the modification of traffic management parameters, the modification of routing parameters, and modifications of resource attributes and constraints. With the traffic balance, the network operation will be more efficient and the network blocking may decrease.<b></b>

scholarly journals OSNR Prediction Based on Federal Learning in Multi-Domain Optical Networks

2021 ◽  
Author(s):  
Junhua Huang ◽  
Bohan Zhu ◽  
Hongxi Zhou ◽  
Qiwei Zheng ◽  
Zhuo Chen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Optical Networks ◽  
Low Cost ◽  
Optical Network ◽  
Main Idea ◽  
Learning Model ◽  
Important Indicator ◽  
Machine Learning Model ◽  
Network Operation ◽  
Model Training

With the continuous expansion of the scale of optical communication network and the rapid increase of network traffic demand, the management form of multi-domain optical network has widely existed. OSNR is an important indicator to judge the quality of communication. It is very important to predict OSNR more accurately in a low-cost and energy-saving way in multi-domain optical networks. In this paper, a scheme of federal learning in multi-domain optical networks is proposed to improve the accuracy of the OSNR prediction. The main idea is to train hybrid machine learning model in each single domain, then the strategy of federal learning is used for optimization it in multi-domains. The performance of the proposed scheme is verified by simulation experiments. The strategy can alleviate the problems of data silos and model training set caused by multi-domain optical network. According to simulation result, when the amount of data reaches 5×103, adding this strategy will reduce the mean square error of the prediction model by about 18%. It can improve the performance of machine learning model, the ability of OSNR prediction and the reliability of network operation.

scholarly journals Simulation of optical network operation using simulator ns-2

2007 ◽  
Vol 55 (2) ◽  
pp. 192-197
Author(s):  
Milovan Kostadinovic-Disovic ◽  
Dragan Ilic
Keyword(s):  
Optical Network ◽  
Network Operation

scholarly journals Energy-Aware Virtual Optical Network Embedding in Sliceable-Transponder-Enabled Elastic Optical Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 41897-41912 ◽  
Author(s):  
Min Zhu ◽  
Qing Sun ◽  
Shengyu Zhang ◽  
Pan Gao ◽  
Bin Chen ◽  
...  
Keyword(s):  
Optical Networks ◽  
Optical Network ◽  
Network Embedding ◽  
Energy Aware
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