Theory and Practice of RRC State Transitions in UMTS Networks

Perälä, Pekka H. J.; Barbuzzi, Antonio; Boggia, Gennaro; Pentikousis, Kostas

doi:10.1109/glocomw.2009.5360763

Cited by 39 publications

(15 citation statements)

References 12 publications

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“…Previous work [15,24] introduced 3G Transition Triggering Tool to infer RRC state machine parameters and to measure one-way delays in different RRC states. But their approach is based on a fixed state transition model and only infers the corresponding parameters (e.g., inactivity timers).…”

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

217

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

217

212

View full text Add to dashboard Cite

show abstract

“…RRC states are inferred and timer values are calculated by performing different experiments using the above mentioned setup. In the paper describing 3G3T [12], authors have validated their findings with Nemo outdoor.…”

Section: G3tmentioning

confidence: 96%

“…3G transition triggering tool (3G3T) [12] is a python based active measurement tool which allows the user to measure various RRC state transition parameters including the state inactivity timers and enables determining delay of different RRC procedures like channel set-up and paging. 3G3T typically runs on a laptop equipped with a 3G data card and a fast Ethernet card.…”

Section: G3tmentioning

confidence: 99%

Taxonomy of Tools and Techniques for Network Monitoring and Quality Assurance in 3G Networks

Gupta¹,

Garg²

2015

IJCA

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ABSTRACT3G cellular networks changed the face of technology completely by bringing to people's doorsteps high speed internet with improved bandwidth and better quality of experience. This accelerated the development of mobile apps harnessing the newly developed trend of near 24X7 connectivity on mobile phones. Today we have numerous applications fitting in the categories of VoIP, chat, social networking and mobile gaming. However, in the hassle of launching another feature rich app which can take the market by storm, its efficacy in terms of resource utilization and impact on the network is one area which often takes the back seat. Developers in majority are ignorant of the intricacies and modus operandi of 3G networks, and shortage of effective tools which can help them visualize the network efficiency of their app further aggravates the problem. The tools and techniques for quantifying an app's behavior in terms of its network efficiency or for the general purposes of network monitoring and bench-marking, are not only limited in number but they often go unnoticed as well. In this work, we target exactly that issue. We provide taxonomy of available tools and techniques for network monitoring and performance measurement in 3G networks. We try to categorize the tools on the basis of their functionality and use-case. Key features of every tool and technique are also highlighted. In the end, we present in tabular form important features used for classification and tools that incorporate them.

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“…Parameters for the 3G model: The T 1 and T 2 inactivity timers of a range of real networks are available in the literature [24,26,152,177,198] or can be obtained from a single power measurement when sending a single packet (from Fig. 2.4 in section 2.2.1) and observing the time spent in each state.…”

Section: Selection Of Parameter Valuesmentioning

confidence: 99%

Energy Modelling and Fairness for Efficient Mobile Communication

Alonso¹,

Jon²

2016

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Energy consumption and its management have been clearly identified as a challenge in computing and communication system design, where energy economy is obviously of paramount importance for battery powered devices. This thesis addresses the energy efficiency of mobile communication at the user end in the context of cellular networks.We argue that energy efficiency starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data traffic traces as input. EnergyBox offers an abstraction of the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for different operator settings and device characteristics. The tool is used throughout the thesis to quantify and reveal inefficient data communication patterns of widely used mobile applications.We consider two different perspectives in the search of energy-efficient solutions. From the application perspective, we show that systematically quantifying the energy consumption of design choices (e.g., communication patterns, protocols, and data formats) contributes to a significantly smaller energy footprint. From the system perspective, we devise a cross-layer solution that schedules packet transmissions based on the knowledge of the network parameters that impact the energy consumption of the handset. These attempts show that application level decisions require a better understanding of possible energy apportionment policies at system level.Finally, we study the generic problem of determining the contribution of an entity (e.g., application) to the total energy consumption of a given system (e.g., mobile device). We compare the state-of-the-art policies in terms of fairness leveraging cooperative game theory and analyse their required information and computational complexity. We show that providing incentives to reduce the total energy consumption of the system (as part of fairness) is tightly coupled to the policy selection. Our study provides guidelines to select an appropriate policy depending on the characteristics of the system. This work has been supported by the Swedish National Graduate School of Computer Science (CUGS), Sweden. v Populärvetenskaplig sammanfattningMobila tjänster som utnyttar kommunikationöver mobila nätverkär till stor nytta för mobiltelefonanvändare. Mobilanvändarna fokuserar på interaktionen med applikationerna och förväntar sig att kunna kommunicera när det behövs utan att tänka på batteriets livslängd. Dessvärre resulterar ineffektiv användning av trådlösa gränssnitt (t.ex. WiFi eller mobilnät) i snabb batteriurladdning. Energiförbrukning och energihanteringär en av de stora utmaningarna för informationsteknologin just nu. Den här avhandlingen behandlar energieffektiviteten i mobilkommunikation med fokus på de mobila enheterna och användarens upplevelse. Den energiförbrukning som orsakas av kommunikationär inte proportionell mot mängden data som skickas vilket beror på hur data skickasöver t...

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Theory and Practice of RRC State Transitions in UMTS Networks

Cited by 39 publications

References 12 publications

Characterizing radio resource allocation for 3G networks

Characterizing radio resource allocation for 3G networks

Taxonomy of Tools and Techniques for Network Monitoring and Quality Assurance in 3G Networks

Energy Modelling and Fairness for Efficient Mobile Communication

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