Evaluation of data compression for energy-aware communication in mobile networks

Wang, Le; Manner, Jukka

doi:10.1109/cyberc.2009.5342172

Cited by 14 publications

(14 citation statements)

References 6 publications

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“…Various works show the benefit of compression for transmitting less network data and thus reducing the energy cost [194,255,262]. We analysed the compression performance of the default compression strategy in Android 1 on the actual messages from the collected WhatsApp logs.…”

Section: Message Sizementioning

confidence: 99%

“…Experimental setups for energy consumption studies on mobile devices either use built-in software in mobile devices like Nokia Energy Profiler (NEP) [24,90,176,179,191,252] or external power meters [77,198,208,223,255]. We categorise the studies based on the radio technology used in their work.…”

Section: Energy Measurement Studiesmentioning

confidence: 99%

“…The viability of data compression for wireless communication in mobile devices is studied by Wang et al [255] concluding that it can provide up to 50% of energy savings by reducing the amount of data transmitted. Stratus [4] combines compression with bursty communication during good signal strength periods.…”

Section: Traffic Adaptation Techniquesmentioning

confidence: 99%

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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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Section: Message Sizementioning

confidence: 99%

Section: Energy Measurement Studiesmentioning

confidence: 99%

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Energy Modelling and Fairness for Efficient Mobile Communication

Alonso¹,

Jon²

2016

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“…Energy consumption studies: experimental setups for energy consumption studies on mobile devices either use built-in software in mobile devices like Nokia Energy Profiler (NEP) [3,12,15,22] or external power meters [9,[18][19][20]23]. The main advantage of our measurement setup is that we are able to isolate the energy consumption of data transfers by performing measurements in a 2G/3G/GPS module.…”

Section: Related Workmentioning

confidence: 99%

Energy-aware cross-layer burst buffering for wireless communication

Vergara

Nadjm‐Tehrani

2012

Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet

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The massive explosion of mobile applications with the ensuing data exchange over the cellular infrastructure is not only a blessing to the mobile user but also has a price in terms of regular discharging of the device battery. A big contributor to this energy consumption is the power hungry wireless network interface. We leverage a measurement kit to perform accurate physical energy consumption measurements in a third generation (3G) telecommunication modem thus isolating the energy footprint of data transfers as opposed to other mobile phone-based measurement studies. Using the measurement kit we show how the statically configured network parameters, i.e., channel switch timers, and buffer thresholds, in addition to the transfer data pattern and the radio coverage, impact the communication energy footprint. We then demonstrate that being aware of static network parameters creates room for energy savings. This is done by devising a set of algorithms that (a) infer the network parameters efficiently, and (b) use the parameters in a new packet scheduler in the device. The combined regime is shown to transfer background uplink data, from real world traces of Facebook and Skype, with significant energy saving compared to the state-of-the-art.

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“…Experimental setups for energy consumption studies on mobile devices are characterised for using either built-in software in mobile devices like Nokia Energy Profiler (NEP) [18,39,80,83,89,111] or external power meters [36,95,99,104,113].…”

Section: Measurement Studiesmentioning

confidence: 99%

Exploiting Energy Awareness in Mobile Communication

Alonso¹,

Jon²

2013

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Although evolving mobile technologies bring millions of users closer to the vision of information anywhere-anytime, device battery depletions hamper the quality of experience to a great extent. The massive explosion of mobile applications with the ensuing data exchange over the cellular infrastructure is not only a blessing to the mobile user, but also has a price in terms of rapid discharge of the device battery. Wireless communication is a large contributor to the energy consumption. Thus, the current call for energy economy in mobile devices poses the challenge of reducing the energy consumption of wireless data transmissions at the user end by developing energy-e cient communication.This thesis addresses the energy e ciency of data transmission at the user end in the context of cellular networks. We argue that the design of energy-e cient solutions starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data tra c traces as input. EnergyBox abstracts the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for di↵erent operator settings and device characteristics.Next, we devise an energy-e cient algorithm that schedules the packet transmissions at the user end based on the knowledge of the network parameters that impact the handset energy consumption. The solution focuses on the characteristics of a given tra c class with the lowest quality of service requirements. The cost of running the solution itself is studied showing that the proposed cross-layer scheduler uses a small amount of energy to significantly extend the battery lifetime at the cost of some added latency.Finally, the benefit of employing EnergyBox to systematically study the di↵erent design choices that developers face with respect to data transmissions of applications is shown in the context of location sharing services and instant messaging applications. The results show that quantifying energy consumption of communication patterns, protocols, and data formats can aid the design of tailor-made solutions with a significantly smaller energy footprint.

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Evaluation of data compression for energy-aware communication in mobile networks

Cited by 14 publications

References 6 publications

Energy Modelling and Fairness for Efficient Mobile Communication

Energy Modelling and Fairness for Efficient Mobile Communication

Energy-aware cross-layer burst buffering for wireless communication

Exploiting Energy Awareness in Mobile Communication

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