Power consumption analysis of constant bit rate video transmission over 3G networks

Ukhanova, Anna; Belyaev, Evgeny; Wang, Le; Forchhammer, Søren

doi:10.1016/j.comcom.2012.05.010

Cited by 15 publications

(5 citation statements)

References 29 publications

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“…However, the lack of a constant power supply and limited battery capacity puts some restrictions on the overall power consumption of the sensor nodes. 26 Therefore, minimization of the power depletion in wearable nodes is a great challenge. Hence, a profound research in this field has concentrated on power consumption minimization.…”

Section: Energy Efficiency With Tpcmentioning

confidence: 99%

“…44 CBR transmission of VBR video can be performed with the optimal choice of buffer size, and the power consumption during CBR video transmission was analyzed. 26 This work describes the power consumption in the transmission part of the nodes, followed by a detailed analysis and measurements of the power consumption in the wireless on-body channel. Moreover, it was observed that much of the difficulty in determining WBSNs' battery lifetime comes from modeling the transceiver's power consumption as a function of time.…”

Section: Crcpmentioning

confidence: 99%

See 1 more Smart Citation

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Sodhro

Chen

Sekhari

et al. 2018

International Journal of Distributed Sensor Networks

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This article presents comparison between data rate or rate control, that is, video transmission rate control algorithm and transmission power control algorithms for two different cases. First, energy consumption due to high peak variable data rates in video transmission. Second, energy depletion due to high transmission power consumption and dynamic nature of wireless on-body channel. The former one focuses on constant (fixed) transmission power level and variable data rate (''severe'' conditions), for example, medical monitoring of the emergency patients. The latter considers variable transmission power level and constant (fixed) data rate (''less severe'' conditions), for example, electrocardiography measurement for patients in wireless body sensor networks. Besides, energy efficiency comparison analysis of battery-driven or video transmission rate control algorithm and transmission power control-driven or power control algorithm is presented. Finally, proposed algorithms are analyzed and categorized as energy-efficient and battery-friendly for medical applications in wireless body sensor networks.

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Section: Energy Efficiency With Tpcmentioning

confidence: 99%

Section: Crcpmentioning

confidence: 99%

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Sodhro

Chen

Sekhari

et al. 2018

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

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“…Falaki et al [2010] proposed the total of T1+T2 = 4.5 s based on their observation on packet inter-arrival time in traffic traces. Ukhanova et al [2012] also suggested aggressive timer configuration for CBR video transmission from mobile devices. Deng and Balakrishnan [2012] proposed to initiate FD dynamically instead of a fixed timeout value.…”

Section: Related Workmentioning

confidence: 99%

Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach

Hoque

Siekkinen

Nurminen

et al. 2014

ACM Trans. Multimedia Comput. Commun. Appl.

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This paper proposes a novel energy-efficient multimedia delivery system called EStreamer. First, we study the relationship between buffer size at the client, burst-shaped TCP-based multimedia traffic, and energy consumption of wireless network interfaces in smartphones. Based on the study, we design and implement EStreamer for constant bit rate and rate-adaptive streaming. EStreamer can improve battery lifetime by 3x, 1.5x and 2x while streaming over Wi-Fi, 3G and 4G respectively. • Hoque et al.over a period of time and then sent together as one burst to the client using all the available bandwidth. In this way, the WNI is kept active only for a short period of time to receive the burst, instead of keeping the interface always active. When the burst size exceeds the playback buffer, there is packet loss. Therefore, the maximum size of a burst, or equivalently the length of a burst interval, is tuned based on an acceptable range of packet loss [Korhonen and Wang 2005].Today HTTP over TCP is by far the most prevalent set of protocols used for streaming [Guo et al. 2006]. Traffic shaping saves energy with TCP-based streaming as well [Hoque et al. 2011]. TCP-based streaming differs from the case of UDP-based streaming in one major way: TCP is a reliable protocol. When the player buffer becomes full, data accumulates into the TCP receive buffer. As a result, an arbitrarily large burst, which is larger than the playback buffer, can be used without any packet loss. However, the exact impact on the energy consumption of smartphones is not well understood. In this article, we first study the interplay between the burst size and the power consumption of smartphones. Specifically, we model the energy consumption of WNIs for bursty TCP traffic. We show that the power consumption of a smartphone decreases when the receiving burst size increases and as long as the client device can accommodate the entire burst. In contrast, the power consumption rapidly increases, if the burst size is too large compared to the available buffer space at the client.As a proof of concept, we design and implement an energy-efficient multimedia delivery system called EStreamer. It determines an energy-optimal burst size so that smooth playback of the streaming applications is not distorted. EStreamer relies on standard TCP feedback from the client. We thoroughly evaluate EStreamer through measurements with real streaming services. We focus on two aspects: (a) the potential to save energy in smartphones using Wi-Fi, 3G (HSPA) and 4G (LTE) and (b) the impact on the radio access network (RAN) signaling load when using a cellular access network.Concerning the first aspect, we measure the energy savings in four different smartphones while streaming from popular streaming services via EStreamer, such as Internet radio, YouTube, and Dailymotion. The results demonstrate that the largest energy savings can be achieved with Wi-Fi (65%), followed by 4G (50-60%), after which comes 3G (38%). It is also shown that a client can achieve similar range of energy sav...

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“…The power consumption of the DCH state is modelled as a linear equation using measurements on a Nokia N900 given the uplink and downlink power consumption for different of packet sizes [245]. Their device-specific model can be easily applied to model the different data rates in the DCH state for EnergyBox.…”

Section: Measurement-based Modelsmentioning

confidence: 99%

“…Puustinen et al [191] measure the impact of unwanted Internet traffic on the energy consumption for 3G and propose blocking traffic and fast dormancy as potential solution. Ukhanova et al [245] study the energy consumption of constant bit rate video communication over 3G and propose a RRC state machine parameter selection method to decrease the uplink energy consumption. Their work shows that by adapting the video quality and transmission power one can achieve energy savings.…”

Section: Cellular Communicationmentioning

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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Power consumption analysis of constant bit rate video transmission over 3G networks

Cited by 15 publications

References 29 publications

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach

Energy Modelling and Fairness for Efficient Mobile Communication

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