MPaaS: Mobility prediction as a service in telecom cloud

Xiong, Haoyi; Zhang, Daqing; Zhang, Daqiang; Gauthier, Vincent; Yang, Kun; Becker, Monique

doi:10.1007/s10796-013-9476-z

Cited by 20 publications

(23 citation statements)

References 46 publications

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“…Reference [16] propose location prediction as an infrastructure service inside a telecom cloud. Mobility Prediction as a Service (MPaaS) is intended to enhance applications as mobility-aware personalization and predictive resource allocation [16].…”

Section: Hybrid Methodsmentioning

confidence: 99%

“…Mobility Prediction as a Service (MPaaS) is intended to enhance applications as mobility-aware personalization and predictive resource allocation [16]. The predictor is based on combining Markov techniques and the study of collective behavioral patterns (CBP).…”

Section: Hybrid Methodsmentioning

confidence: 99%

“…Collective behavioral patterns are defined as an association between daily movement patterns of different users [16]. This is due to most people sharing common schedules between workplace and home.…”

Section: Hybrid Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Recent advances in location prediction methods for cellular communication networks

Leca

Tuta

Nicolaescu

et al. 2015

2015 23rd Telecommunications Forum Telfor (TELFOR)

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Predicting the future location of a device inside a cellular network has become an interesting field of study in recent years, as it offers new solutions for location based services. In this paper we analyze recently proposed methods for location prediction. Based on the proven limits of human predictability we propose that location prediction methods should not be limited only to movement pattern analysis. We conclude that location prediction methods can become more accurate by introducing social analysis methods based on call related information obtained from the network or the user's device.

show abstract

Section: Hybrid Methodsmentioning

confidence: 99%

Section: Hybrid Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Recent advances in location prediction methods for cellular communication networks

Leca

Tuta

Nicolaescu

et al. 2015

2015 23rd Telecommunications Forum Telfor (TELFOR)

View full text Add to dashboard Cite

show abstract

“…Predictions may be based on both aggregated historical data and the current real-time situation data. Mobility Prediction as a Service (MPaaS) has been proposed (Xiong et al, 2014) as an approach combining location information from mobile phones and forecasting algorithms to provide better forecasts of traffic flows.…”

Section: Predicted Traffic System Situationmentioning

confidence: 99%

Crowdsensing-based transportation services — An analysis from business model and sustainability viewpoints

Heiskala

Jokinen

Tinnilä

2016

Research in Transportation Business & Management

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“…Predicting mobile phone users' locations in next few hours is essential for a wide range of mobile applications, including location-based service, mobile access control, mobile multimedia QoS provision, as well as resource management for mobile computation and storage. The paper by Xiong et al (2014) entitled "MPaaS: Mobility Prediction as a Service in Telecom Cloud" proposes mobility prediction based on cellular traces as an infrastructural level service of telecom cloud. The proposed Mobility Prediction as a Service (MPaaS) embeds mobility mining and forecasting algorithms into a cloud-based user location-tracking framework.…”

Section: Mobile Cloud and Servicesmentioning

confidence: 99%