Energy Consumption Of Mobile Phones Research Articles

Energy Cycle Optimization of Mobile Phones Using A Sleep Cycle Optimization Algorithm

Researchers and mobile network operators are dealing with the steep rise in energy consumption of mobile phones. A massive amount of phones are available in the market which are updating services from time to time. The problem lies in their battery drainage in response to the usage of internet-based applications including online streaming, multimedia requests, social networking usage and many more. In this research, a new technique is proposed and evaluated for energy optimization in mobile phones by exploiting the listening cycle of the mobile station (MS) wake-up mode while connected to the base station (BS) that is connected to a mobile network based on IEEE 802.16e. An MS cannot communicate with the BS if it is in the sleep mode while the other is in the wake-up mode. Service time and sojourn time are assumed to be exponential and based on t-distribution. The confidence interval comes up to 95% for our technique. The relative error is computed between the earlier techniques available and the approximated proposed one. Results show that there is a considerable improvement in energy consumption as compared to the other available techniques.

Adaptive Predictive Power Management for Mobile LTE Devices

Reducing the energy consumption of mobile phones is a crucial design goal for cellular modem solutions for LTE and 5G NR standards. Most dynamic power management techniques targeting mobile devices proposed so far, however, are purely reactive in powering down and up system components. Promising approaches extend this, by predicting information from the cell and the communication protocol to take decisions proactively. In this paper, we present a complete proactive power management approach for the modem based on on-line grant prediction. In this context, we define proactive policies that allow a mobile device to go to sleep states more often compared to reactive power management systems, e.g., in time slots of predicted transmission inactivity in a cell. Furthermore, we propose and compare two algorithmic solutions to this proactive grant prediction problem, one a feed-forward neural network and one a SARSA-λ reinforcement agent. As the implementation of these machine learning techniques also creates additional energy and resource costs, both approaches are carefully designed, optimized, and evaluated not only in terms of prediction accuracy, but also in terms of overall energy savings. Notably, our predictor implementations are able to achieve up to 17 percent in overall energy savings on real-world traces.

Energy Modeling of IoT Mobile Terminals on WiFi Environmental Impacts †.

With the popularity of various IoT mobile terminals such as mobile phones and sensors, the energy problems of IoT mobile terminals have attracted increasingly more attention. In this paper, we explore the impacts of some important factors of WiFi environments on the energy consumption of mobile phones, which are typical IoT end devices. The factors involve the WiFi signal strength under good signal conditions, the type and the amount of protocol packets that are initiated by WiFi APs (Access Points) to maintain basic network communication with the phones. Controlled experiments are conducted to quantitatively study the phone energy impacts by the above WiFi environmental factors. To describe such impacts, we construct a time-based signal strength-aware energy model and packet type/amount-aware energy models. The models constructed in the paper corroborate the following user experience on phone energy consumption: (1) a phone’s energy is drawn faster under higher WiFi signal strengths than under lower ones even in normal signal conditions; (2) phones consume energy faster in a public WiFi network than in a private one even in the basic phone state. The energy modeling methods proposed in the paper enable ordinary developers to analyze phone energy draw conveniently by utilizing inexpensive power meters as measurement tools. The modeling methods are general and are able to be used for phones of any type and any platform.

Reducing energy consumption of mobile phones during data transmission and encryption for wireless body area network applications

Wireless body area networks WBANs are an exciting technology that will revolutionize physiological monitoring in the coming years. However, the widespread deployment of WBANs is restricted by steep energy limitations. Furthermore, they require acute security measures to protect user medical data. We aim to measure the energy consumption of a cellphone as it transmits and encrypts data in a mock WBAN scenario. We evaluated the impact of various design parameters in an effort to discover the ideal WBAN operational protocols. In conclusion, we recommend an optimal file size strategy, data communication network, and encryption algorithm that minimize energy consumption and enhance WBAN operation. Copyright © 2015John Wiley & Sons, Ltd.

Mobile multimedia streaming techniques: QoE and energy saving perspective

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 the best playback buffer configuration, which provides the most attractive trade-offs in particular situations.

A critical analysis of the sustainability of mobile phone use

In the last twenty years, there has been a sharp increase in the consumption of commodities with a short life-cycle. This is especially true for electronic equipment such as mobile phones, which are the focus of this paper. The short lifespan, which is due to continually substituting obsolete equipment with newer and more innovative models, has stimulated the growth in sales of these electronic goods. Europe continues to be the main mobile phone market in developed countries, but this growth has slowed down over the last two years. Despite being an already mature market, Italy has a “diffusion rate” (i.e., the number of active lines per 100 inhabitants) higher than 146, which is the highest in the European Union.This scenario demonstrated the need for a study examining the sustainability of the mobile phone sector according to two critical aspects that are often due to the behavioural patterns of the users: the first is the energy consumption of mobile phones and their associated equipment, and the second is related to the conflicting link between potential dematerialisation due to the miniaturisation of the devices and the resource consumption and waste generated in this sector. This paper discusses these two critical aspects and presents an overview of the Italian mobile phone sector, particularly related to the energy consumption during the use phase and increase of mass flows due to the devices circulating in Italy and the higher amount of the disposable products that have to be managed.The results show that, in Italy, the entire mobile phone system consumes approximately 2200GWh per year, which is equal to 0.7% of the national electricity consumption, and produces potential e-waste from end-of-life devices totalling over 11 thousand tonnes for the period from 2007 to 2012. Concerning the issue of resources consumption, this estimate highlights that the potential savings in inputs, due to the reduction in device weight over time, has always been counteracted by their increasing demand.

Analysis of material and energy consumption of mobile phones in China

Owing to booming mobile phone ownership and a short product innovation cycle, waste mobile phones are flooding China. In 2008, about 560 million mobile phones were produced and 634 million users subscribed to a mobile phone plan in China. These large numbers mean that the charging and disposal of mobile phones has the potential to have significant impacts on the environment. Thus the evaluation of material and energy consumption of mobile phones is an important task in the end-of-life management of electronic products. This paper uses material flow analysis (MFA) and life cycle assessment (LCA) methods to estimate the life cycle impacts of mobile phones in China from manufacturing energy, use phase and generation of waste mobile phones. Results indicate over the mobile phone life cycle, manufacturing accounts for 50% of the total energy consumption, whereas the use phase accounts for only 20%. Mobile phones and supporting infrastructures account for a rapidly increasing 0.17% of Chinese energy use. In 2008, around 77 million units of waste mobile phones were generated in China. To manage this energy use and recover valuable materials recommendations are made to increase lifespan, improve energy efficiency during use and ensure recycling.

Cooperative Mobile Web Browsing

This paper advocates a novel approach for mobile web browsing based on cooperation among wireless devices within close proximity operating in a cellular environment. In the actual state of the art, mobile phones can access the web using different cellular technologies. However, the supported data rates are not sufficient to cope with the ever increasing traffic requirements resulting from advanced and rich content services. Extending the state of the art, higher data rates can only be achieved by increasing complexity, cost, and energy consumption of mobile phones. In contrast to the linear extension of current technology, we propose a novel architecture where mobile phones are grouped together in clusters, using a short-range communication such as Bluetooth, sharing, and accumulating their cellular capacity. The accumulated data rate resulting from collaborative interactions over short-range links can then be used for cooperative mobile web browsing. By implementing the cooperative web browsing on commercial mobile phones, it will be shown that better performance is achieved in terms of increased data rate and therefore reduced access times, resulting in a significantly enhanced web browsing user experience on mobile phones.