Titlebook: Machine Learning for Networking; First International éric Renault,Paul Mühlethaler,Selma Boumerdassi Conference proceedings 2019 Springer

ANTIC

Energy-Based Connected Dominating Set for Data Aggregation for Intelligent Wireless Sensor Networksted way based on predefined energy constraints, it represents an intelligent fault tolerance mechanism to maintain our network and to deal with packet loss. The simulation results show that our proposed method outperforms existing methods.

gout109

LSTM Recurrent Neural Network (RNN) for Anomaly Detection in Cellular Mobile Networks,ithm. We have applied DNN (Deep Neural Network) to generate a profile on KPI features from historical data. It gave us deeper insight into how the cell is performing over time and can connect with the root causes or hidden fault of a major failure in the cellular network.

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Conference proceedings 2019s; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks..

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征兵

Towards Analysing Cooperative Intelligent Transport System Security Data,tor servers, smartphone applications. These amounts of data can be exploited and analysed in order to extract pertinent information as driver profiles, abnormal driving behaviours, etc. In this paper, we present a methodology for analysis of data provided by a real experimentation of a cooperative i

phlegm

Towards a Statistical Approach for User Classification in Twitter,inguish the patterns of users from those of organizations and individuals. The ability of distinguishing between the two account types is needed for developing recommendation engines, consumer products opinion mining tools, and information dissemination platforms. However, such a task is non-trivial

GRAVE

RILNET: A Reinforcement Learning Based Load Balancing Approach for Datacenter Networks,balancing mechanism which is widely used in?today’s datacenters, can balance load poorly and lead to congestion. Variety of load balancing schemes are proposed to address the problems of ECMP. However, these traditional schemes usually make load balancing decision only based on network knowledge for