Impacts of inactivity timer values on UMTS system capacity

Chuah, Mooi Choo; Luo, Wei; Zhang, X.

doi:10.1109/wcnc.2002.993390

Cited by 34 publications

(15 citation statements)

References 1 publication

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“…Among them, Chuah et al [16] studied the impact of inactivity timers on UMTS network capacity by simulating the performance of web browsing. Some [20,32] proposed analytical models to measure the energy consumption of user devices under different timer values.…”

Section: Related Workmentioning

confidence: 99%

Characterizing radio resource allocation for 3G networks

Qian

Wang

Gerber

et al. 2010

Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement

218

212

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ABSTRACT3G cellular data networks have recently witnessed explosive growth. In this work, we focus on UMTS, one of the most popular 3G mobile communication technologies. Our work is the first to accurately infer, for any UMTS network, the state machine (both transitions and timer values) that guides the radio resource allocation policy through a light-weight probing scheme. We systematically characterize the impact of operational state machine settings by analyzing traces collected from a commercial UMTS network, and pinpoint the inefficiencies caused by the interplay between smartphone applications and the state machine behavior. Besides basic characterizations, we explore the optimal state machine settings in terms of several critical timer values evaluated using real network traces. Our findings suggest that the fundamental limitation of the current state machine design is its static nature of treating all traffic according to the same inactivity timers, making it difficult to balance tradeoffs among radio resource usage efficiency, network management overhead, device radio energy consumption, and performance. To the best of our knowledge, our work is the first empirical study that employs real cellular traces to investigate the optimality of UMTS state machine configurations. Our analysis also demonstrates that traffic patterns impose significant impact on radio resource and energy consumption. In particular, We propose a simple improvement that reduces YouTube streaming energy by 80% by leveraging an existing feature called fast dormancy supported by the 3GPP specifications.

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Section: Related Workmentioning

confidence: 99%

Characterizing radio resource allocation for 3G networks

Qian

Wang

Gerber

et al. 2010

Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement

218

212

View full text Add to dashboard Cite

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“…In particular, the study of 3G's energy consumption characteristics important and non-intuitive implications for the design of efficient energy application. Analytical modeling: Previous studies such as [2], [8], [12] have studied the impact of different energy-saving techniques in 3G networks using analytical models [7].…”

Section: A Tailendermentioning

confidence: 99%

An experimental methodology for modeling the energy consumption of mobile devices

Hamzaoui

Berrajaa

Azizi

et al. 2017

2017 First International Conference on Embedded &Amp; Distributed Systems (EDiS)

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Abstract-Energy consumption is the result of interactions between hardware, software, users, and the application environment. Optimization of energy consumption has become crucial, energy metric is considered a critical metric, so it is important knowing how to measure and understand how energy is consumed on mobile devices. Accurate knowledge will allow us to propose different solutions to reduce energy consumption in order to improve the user experience. In this paper we propose an experimental methodology to build a model of the energy consumption of an application. We show in this paper how to build a simple predictive model of the energy consumption of an unconnected application based on precise measurements.

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“…In [7] and [9], different values for tail time has been suggested and proven to reduce the energy consumption. In [11,17,18] dynamic assignment of tail time based on usage pattern has been proposed.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Scheduling for Mobile Push Notifications

Acer

Mashhadi

Forlivesi

et al. 2015

Proceedings of the 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

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Push notifications are small and succinct messages used by mobile applications to inform users of new events and updates. These notifications are pushed to the user devices by a set of dedicated notification servers (e.g., Apple Push Notification Server, Google Cloud Messaging Server, etc.) as they arrive from the content providers of the mobile applications. However, due to their intrinsic small size and sporadic nature, the transfer of these messages is not power efficient, especially on cellular networks. To address this, we propose a network centric scheduling mechanism that delays the delivery of these messages as appropriate by sensing and predicting users' cellular network activities. A trace based evaluation with 60 users' cellular network logs of 30 days shows that we can reduce the energy consumption of mobile devices by 10% for an average delay of 150 seconds in notification delivery. As a network based system that does not require any modifications to user devices, scheduling push notifications opens up interesting opportunities for mobile operators to provide value added and differentiating services, especially considering the sharp rise of non-critical push notification messages.

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Impacts of inactivity timer values on UMTS system capacity

Cited by 34 publications

References 1 publication

Characterizing radio resource allocation for 3G networks

Characterizing radio resource allocation for 3G networks

An experimental methodology for modeling the energy consumption of mobile devices

Energy Efficient Scheduling for Mobile Push Notifications

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