اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدOn the Battery Consumption of Mobile Browsers
239
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Mobile web browsing has recently surpassed desktop browsing both in term of popularity and traffic. Following its desktop counterpart, the mobile browsers ecosystem has been growing from few browsers (Chrome, Firefox, and Safari) to a plethora of browsers, each with unique characteristics (battery friendly, privacy preserving, lightweight, etc.). In this paper, we introduce a browser benchmarking pipeline for Android browsers encompassing automation, in-depth experimentation, and result analysis. We tested 15 Android browsers, using Cappuccino a novel testing suite we built for third party Android applications. We perform a battery-centric analysis of such browsers and show that: 1) popular browsers tend also to consume the most, 2) adblocking produces significant battery savings (between 20 and 40% depending on the browser), and 3) dark mode offers an extra 10% battery savings on AMOLED screens. We exploit this observation to build AttentionDim, a screen dimming mechanism driven by browser events. Via integration with the Brave browser and 10 volunteers, we show potential battery savings up to 30%, on both devices with AMOLED and LCD screens.
قيم البحث
اقرأ أيضاً
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 se
ssion. 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.
In this paper, we propose to model the energy consumption of smart grid households with energy storage systems as an intertemporal trading economy. Intertemporal trade refers to transaction of goods across time when an agent, at any time, is faced wi
th the option of consuming or saving with the aim of using the savings in the future or spending the savings from the past. Smart homes define optimal consumption as either balancing/leveling consumption such that the utility company is presented with a uniform demand or as minimizing consumption costs by storing energy during off-peak time periods when prices are lower and use the stored energy during peak time periods when prices are higher. Due to the varying nature of energy requirements of household and market energy prices over different time periods in a day, households face a trade-off between consuming to meet their current energy requirements and/or storing energy for future consumption and/or spending energy stored in the past. These trade-offs or consumption preferences of the household are modeled as utility functions using consumer theory. We introduce two different utility functions, one for cost minimization and another for consumption balancing/leveling, that are maximized subject to respective budget, consumption, storage and savings constraints to solve for the optimum consumption profile. The optimization problem of a household with energy storage is formulated as a geometric program for consumption balancing/leveling, while cost minimization is formulated as a linear programming problem. Simulation results show that the proposed model achieves extremely low peak to average ratio in the consumption balancing/leveling scheme with about 8% reduction in consumption costs and the least possible amount for electricity bill with about 12% reduction in consumption costs in the cost minimization scheme.
Web Based Query Management System (WBQMS) is a methodology to design and to implement Mobile Business, in which a server is the gateway to connect databases with clients which sends requests and receives responses in a distributive manner. The gatewa
y, which communicates with mobile phone via GSM Modem, receives the coded queries from users and sends packed results back. The software which communicates with the gateway system via SHORT MESSAGE, packs users requests, IDs and codes, and sends the package to the gateway; then interprets the packed data for the users to read on a page of GUI. Whenever and wherever they are, the customer can query the information by sending messages through the client device which may be mobile phone or PC. The mobile clients can get the appropriate services through the mobile business architecture in distributed environment. The messages are secured through the client side encoding mechanism to avoid the intruders. The gateway system is programmed by Java, while the software at clients by J2ME and the database is created by Oracle for reliable and interoperable services.
We assess the power consumption of network synchronisation protocols, particularly the energy required to synchronise all nodes across a network. We use the widely adopted approach of bio-inspired, pulse-coupled oscillators to achieve network-wide sy
nchronisation and provide an extended formal model of just such a protocol, enhanced with structures for recording energy usage. Exhaustive analysis is then carried out through formal verification, utilising the PRISM model checker to calculate the resources consumed on each possible system execution. This allows us to assess a range of parameter instantiations and to explore trade-offs between power consumption and time to synchronise. This provides a principled basis for the formal analysis of a much broader range of large-scale network protocols.
We model the mobility of mobile phone users to study the fundamental spreading patterns characterizing a mobile virus outbreak. We find that while Bluetooth viruses can reach all susceptible handsets with time, they spread slowly due to human mobilit
y, offering ample opportunities to deploy antiviral software. In contrast, viruses utilizing multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating systems market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
