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Multimedia streaming to mobile devices is challenging for two reasons. First, the way content is delivered to a client must ensure that the user does not experience a long initial playback delay or a distorted playback in the middle of a streaming session. Second, multimedia streaming applications are among the most energy hungry applications in smartphones. The energy consumption mostly depends on the delivery techniques and on the power management techniques of wireless access technologies (Wi-Fi, 3G, and 4G). In order to provide insights on what kind of streaming techniques exist, how they work on different mobile platforms, their efforts in providing smooth quality of experience, and their impact on energy consumption of mobile phones, we did a large set of active measurements with several smartphones having both Wi-Fi and cellular network access. Our analysis reveals five different techniques to deliver the content to the video players. The selection of a technique depends on the mobile platform, device, player, quality, and service. The results from our traffic and power measurements allow us to conclude that none of the identified techniques is optimal because they take none of the following facts into account: access technology used, user behavior, and user preferences concerning data waste. We point out the technique with optimal playback buffer configuration, which provides the most attractive trade-offs in particular situations.

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...

As computing power increases, more complex computational models are utilized for biomass supply system studies. The paper describes three commonly used modeling methods in this context, geographic information systems, life-cycle assessment, and discrete-time simulation and presents bibliometric analysis of work using these three study methods. Of the 498 publications identified in searches of the Scopus and Web of Science databases, 17 reported on combinations of methods: 10 on life-cycle assessment and geographic information systems, six on joint use of life-cycle assessment and discrete-time simulation, and one on use of geographic information systems jointly with discrete-time simulation. While no articles dealt directly with simultaneous use of all three methods, several acknowledged the potential of this. The authors discuss numerous challenges identified in the review that arise in combining methods, among them computational load, the increasing number of assumptions, guaranteeing coherence between the models used, and the large quantities of data required.Discussion of issues such as the complexity of reporting and the need for standard procedures and terms becomes more critical as repositories bring together research materials, including entire models, from various sources. Efforts to mitigate many of modeling's challenges have involved phase-specific modeling and use of such methods as expressions or uncertainty analysis in place of a complex secondary model. The authors conclude that combining modeling methods offer considerable potential for taking more variables into account; improving the results; and benefiting researchers, decision-makers, and operation managers by producing more reliable information.

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