Learning probabilistic models of cellular network traffic with applications to resource management

2014 IEEE International Symposium on Dynamic Spectrum Access Networks, DYSPAN 2014

Volumn , Issue , 2014, Pages 82-91

  Paul, Utpal ^a   Ortiz, Luis ^a   Das, Samir R ^a   Fusco, Giordano ^a   Buddhikot, Milind Madhav ^b  

^a Stony Brook University   (United States)

^b LUCENT TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS; LEARNING SYSTEMS; NATURAL RESOURCES MANAGEMENT; RESOURCE ALLOCATION; SCHEDULING;

CELLULAR NETWORK TRAFFICS; CONDITIONAL DEPENDENCE; EXPONENTIAL INCREASE; MACHINE LEARNING TECHNIQUES; MONITORING TECHNIQUES; OPPORTUNISTIC SCHEDULING; PROBABILISTIC MODELS; TRAFFIC MEASUREMENTS;

BASE STATIONS;

EID: 84902190189     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DySPAN.2014.6817782     Document Type: Conference Paper

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