Modeling and Assessing Variability in Energy Consumption During the Use Stage of Online Multimedia Services

Schien, Daniel; Shabajee, Paul; Yearworth, Mike; Preist, Chris

doi:10.1111/jiec.12065

Cited by 48 publications

(68 citation statements)

References 20 publications

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“…In [31], this work was extended to include CPE and end devices, and to explore uncertainty and variability in assessments of digital services. In contrast to this chapter and to [30], which try to represent the existing variability in previous assessments, [31] estimates how uncertainty in energy intensity affects the overall result.…”

Section: Bottom-up Assessmentsmentioning

confidence: 99%

The Energy Intensity of the Internet: Home and Access Networks

Coroamă

Schien

Preist

et al. 2014

Advances in Intelligent Systems and Computing

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Estimates of the energy intensity of the Internet diverge by several orders of magnitude. We present existing assessments and identify diverging definitions of the system boundary as the main reason for this large spread. The decision of whether or not to include end devices influences the result by 1-2 orders of magnitude. If end devices are excluded, customer premises equipment (CPE) and access networks have a dominant influence. Of less influence is the consideration of cooling equipment and other overhead, redundancy equipment, and the amplifiers in the optical fibers. We argue against the inclusion of end devices when assessing the energy intensity of the Internet, but in favor of including CPE, access networks, redundancy equipment, cooling and other overhead as well as optical fibers. We further show that the intensities of the metro and core network are best modeled as energy per data, while the intensity of CPE and access networks are best modeled as energy per time (i.e., power), making overall assessments challenging. The chapter concludes with a formula for the energy intensity of CPE and access networks. The formula is presented both in generic form as well as with concrete estimates of the average case to be used in quick assessments by practitioners. The following chapter develops a similar formula for the core and edge networks. Taken together, the two chapters provide an assessment method of the Internet's energy intensity that takes into account dierent modeling paradigms for dierent parts of the network. Abstract. Estimates of the energy intensity of the Internet diverge by several orders of magnitude. We present existing assessments and identify diverging definitions of the system boundary as the main reason for this large spread. The decision of whether or not to include end devices influences the result by 1-2 orders of magnitude. If end devices are excluded, customer premises equipment (CPE) and access networks have a dominant influence. Of less influence is the consideration of cooling equipment and other overhead, redundancy equipment, and the amplifiers in the optical fibers. We argue against the inclusion of end devices when assessing the energy intensity of the Internet, but in favor of including CPE, access networks, redundancy equipment, cooling and other overhead as well as optical fibers. We further show that the intensities of the metro and core network are best modeled as energy per data, while the intensity of CPE and access networks are best modeled as energy per time (i.e., power), making overall assessments challenging. The chapter concludes with a formula for the energy intensity of CPE and access networks. The formula is presented both in generic form as well as with concrete estimates of the average case to be used in quick assessments by practitioners. The following chapter develops a similar formula for the core and edge networks. Taken together, the two chapters provide an assessment method of the Internet's energy intensity that takes into account different ...

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Section: Bottom-up Assessmentsmentioning

confidence: 99%

The Energy Intensity of the Internet: Home and Access Networks

Coroamă

Schien

Preist

et al. 2014

Advances in Intelligent Systems and Computing

Self Cite

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“…According to Schien et al [19], the lowest energy consumption can be reached when reading an online newspaper from a smartphone with cellular wireless connection. However, the overall impact depends on the total overall device use and the geographical location of the user, due to the electricity mix.…”

Section: Introductionmentioning

confidence: 99%

Environmental aspects of media scenarios for the future ICT society

Edwardsson¹

2014

Proceedings of the 2014 Conference ICT for Sustainability

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Abstract-During the past 50 years, the media channels, the media consumption patterns and the entire influence of media in society have changed dramatically. Looking into the future, the pace of change is not likely to decrease. In order to prepare for the future, it is important to increase our understanding of the present, in particular with regards to the environmental aspects of media consumption. In this study, I present four future scenarios related to media consumption trends and discuss these scenarios in relation to environmental aspects in the ICT society.I have tried to answer the following questions: What could be the characteristics of media consumption in different future scenarios? What parameters are central in future scenarios around media consumption, seen from an environmental perspective? How will changes in these parameters affect the environmental aspects of media consumption? I have limited the question to a Nordic context.A combination of different media theories, future studies methodology and interview techniques have been used. Interviews and workshops were conducted with media and environmental experts and with consumers. The result of the interviews with consumers shows that very few consumers connect media consumption with environmental concerns. The majority of the interviewed persons considered printed media as more environmentally damaging compared to electronic media, which was considered "clean".The environmental experts participating in this study considered the most central parameters in future scenarios of media consumption, seen from an environmental perspective, to be connected to electronic devices, travel, transportation, energy use and waste. The environmental aspects of these parameters depend not only on the amount of devices, travel, transportation, energy and waste, but also on the way the devices are produced and used, how the travel and transportation are done, what kind of energy is used, and how the waste is treated.The amount of environmental information available in society is yet another important parameter in order to create a more environmentally sustainable future, and this is where the media could play an important role.

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“…However, their findings also point out that downloading video content using a mobile phone in 3G network causes significant energy consumption particularly within the mobile access network, while the impacts on other parts of the value chain are minor. Other significant sources of the energy footprint within their study were user devices and data centers (Schien et al, 2013). However, their findings highlight the importance of considering the environmental impacts of mobile networks in future studies.…”

Section: Role Of Mobile Access Network In the Value Chain Of Electromentioning

confidence: 83%

“…With new energy efficient mobile devices, production of the device might be more significant source of environmental impacts, when compared to use phase . Other studies have pointed out that energy consumption of the mobile access network becomes significant when video content is downloaded using mobile devices (Schien et al, 2013). The development taking place in Finland indicates that increasing use of mobile devices and especially the video content is increasing the total energy consumption related to mobile networks, even though the normalized kWh/Gigabyte consumption is simultaneously decreasing.…”

Section: Impact Of User Behavior On Overall Energy Consumptionmentioning

confidence: 99%

“…While there are several studies that have evaluated the environmental impacts of ICT and data transfer, to our knowledge, not much information is currently available about the impacts of mobile services and networks. Existing studies (Malmodin & Lundén, 2016;Malmodin, Lundén, Moberg, Andersson, & Nilsson, 2014;Scharnhorst, Hilty, & Jolliet, 2006;Schien, Shabajee, Yearworth, & Preist, 2013) provide important information and a good starting point. However, due to rapid technical development in both radio network technology and changes in user behavior, existing studies are quickly outdated.…”

Section: Ict4s2018 5th International Conference On Information and Cmentioning

confidence: 99%

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Energy consumption of mobile data transfer – Increasing or decreasing? Evaluating the impact of technology development & user behavior

Pihkola¹,

Hongisto²,

Apilo³

et al.

EPiC Series in Computing

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Mobile data consumption in Finland is among the highest in the world. Increase in mobile data usage has been rapid and continuous growth is foreseen. While the energy consumed per transmitted gigabyte has substantially decreased, it seems that the absolute annual energy consumption related to mobile operators' activities has started to increase. Simultaneously, consumer behavior is changing. While new end-user devices are more and more energy-efficient, we use more and more time with mobile devices. Is increasing usage outweighing achieved energy savings? What kinds of options are available for tackling increasing energy demand? This paper discusses current and future trends related to energy consumption of mobile data transfer and mobile networks in Finland. Using a top-down approach and publicly available data, an illustrative trend (kWh/gigabyte) for the energy consumption of transmitted mobile data was constructed for the years 2010-2016. In addition, energy consumption related to mobile data transfer is discussed from a life cycle perspective, considering both direct and indirect energy use and challenges in conducting such assessments. Contributions of relevant technological and social developments (radio network technology transformations from 4G to 5G and consumer behavior) are analyzed considering possible trade-offs and pointing out aspects that require future studies.

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Modeling and Assessing Variability in Energy Consumption During the Use Stage of Online Multimedia Services

Cited by 48 publications

References 20 publications

The Energy Intensity of the Internet: Home and Access Networks

The Energy Intensity of the Internet: Home and Access Networks

Environmental aspects of media scenarios for the future ICT society

Energy consumption of mobile data transfer – Increasing or decreasing? Evaluating the impact of technology development & user behavior

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