The internet browser is the most important tool on a mobile device. It is the engine for browsing the internet. No longer just for websites but also now for new types of applications based on web technologies (progressive web app, games, etc.).

For this new edition of our ranking, carried out in 2018 and 2020, we have chosen to compare 16 mobile applications: Brave, DuckDuckGo, Chrome, Ecosia, Edge, Firefox, Firefox Focus, Firefox Nightly (formerly Firefox Preview), Kiwi, Mint, Opera, Opera Mini, Qwant, Samsung, Vivaldi et Yandex.

The objective of these measures is to see how the solutions stand in terms of environmental impact (Carbon) in relation to each other on common user scenarios but also to provide benchmarks on our uses of browsers.

For each of the 16 applications measured on a Galaxy S7 (Android 8) smartphone, the scenarios integrating the launch of the browser, browsing on 7 different websites, periods of inactivity, etc. were carried out through our Greenspector Test Runner, allowing the performance of automated tests.

Learn more about our methodology

Total energy consumption (in mAh)

The average power consumption is 49mAh (as a reminder, the 2020 ranking average was 47mAh or -4.2%).

Here is the evolution from last year.

	2021 Ranking	2020 Ranking	Évolution
Firefox Focus	1	10	9
Vivaldi	2	4	2
DuckDuckGo	3	5	2
Firefox Nighly	4	10	6
Yandex	5	3	-2
Kiwi	6	8	2
Opéra	7	2	-5
Brave	8	7	-1
Ecosia	9	1	-8
Chrome	10	6	-4
Samsung	11	9	-2
Firefox	12	13	1
Edge	13	11	-2
Qwant	14	13	-1
Opera Mini	15	14	-1
Mint	16	12	-4

Firefox Focus is the best solution in terms of energy consumption in our comparison. The version evaluated in 2020 was one of the first versions and it seems that Firefox teams have been working on optimizing the power consumption of their browser since. Ecosia loses its leading position on this indicator and finds itself in the middle of the ranking. On the side of the most energy-hungry browsers, we find Mint and Opera Mini. Note that the most popular browsers: Edge, Firefox, Chrome, and Samsung, are quite poorly classified.

This total energy consumption can be evaluated and analyzed in 2 ways: the energy consumption of pure navigation and the energy consumption related to the functionality of the browser.

Energy consumption of navigation (in mAh)

Navigation is the consumption only associated with viewing the page (no consideration of launching the browser, features, etc.).

Most browsers have a fairly similar power consumption on “pure” navigation. This is mainly due to the use of visualization engines. Most browsers use the Chromium view engine.

Compared to the 2020 ranking, it seems that the Firefox engine has improved. Qwant, using this engine too.

Energy consumption of features (in mAh)

The functionalities include browser states such as idle periods, launching the browser, writing URLs in the navigation bar.

By keeping the same classification as for the total energy, we see that the non-navigation functionalities (writing of URLs, inactivity of the browser, etc.) have a significant impact on total consumption.

Autonomy (hours)

Battery life is the number of hours the user can surf before the battery is completely discharged. The ranking does not change with respect to that of energy, as autonomy is directly related to energy.

We observe that the autonomy can double from 5h to 10h between the most consuming browser (Mint) and the least consuming (Firefox Focus).

Data (Volume of data exchanged) (MB)

Some applications do not manage the cache at all for reasons of data protection and privacy, use proxies that optimize data, have a difference in the implementation of cache management. In addition, if a browser is good, the downside is that a lot more data is potentially loaded in the background. In our methodology, we see it for the New York Times site, which is larger in terms of data.

Here is an example of the measurement iterations on the Amazon site (Amazon.com) that shows the difference in data processing between different browsers.

Memory consumption(RAM) by the browser process (MB)

Memory consumption is important to take into account in a digital service because even the variation in memory consumption does not influence the energy impact, it remains very important to integrate because of the effects of overconsumption on already congested devices. in memory, or older, less powerful, this can create instabilities or applications that cannot operate simultaneously because they compete. In ecological terms, this can of course provides a premature change of device on the user side for a more powerful model to satisfy good user comfort.

The variation goes from 400MB to 1.8GB (approximately half the RAM of the Samsung Galaxy S7).

Let us observe more precisely the behavior of the memory following the sequence:

• Launch browser
• Browser inactivity
• Navigation (Average memory consumption)
• Inactivity following navigation
• System after closing browser

At the launch of browsers, we have a median memory usage of 413MB. Edge consumes a lot more with 834MB.

If we leave the browser inactive, the memory consumption of most browsers remains fairly stable. Which is pretty good and normal. On the other hand, we see that Edge and Ecosia have a strong increase in memory.

Then, with navigation, the memory consumed increases significantly. This is due to the consumption of navigation engines to analyze and store items. The management of tabs will also play a role. If the browser offloads the memory for the non-active tabs, then the consumption will be lower.

We can note that Firefox Focus, Mint, Duck Duck go, Opera Mini and Qwant overall consume little memory.

When the browser is closed, almost all browsers are no longer in memory. Firefox remains however with 1, GB as well as Chrome and Mint with around 100MB. Probably a bug but it is annoying because elements still occupy the memory and processing operations can also exist: processing operations are confirmed on Firefox and Mint with the rate of CPU consumed by the browser process which remains high.

We can also look at the memory impact of consulting Wikipedia (the basic consumption of the browser is subtracted here).

We understand the difference in memory management between browsers and the potential entropy on heavier sites.

Performance

We measured the time it took to write the URL in the address bar.

This difference in performance can be explained by several factors: network exchanges during entry (auto-completions), processing during entry, search based on known addresses, etc. In the end, for the user, the time to access the site will be longer or shorter. For example on the Wikipedia URL entry on Duck Duck Go a lot of network traffic and CPU processing (peak at 22% CPU).

Unlike the faster Edge which has lower processing in terms of CPU.

By the way, we could have an optimization of all the browsers by limiting its treatments (for example by grouping and spacing the treatments).

Environmental impact

The environmental impact is calculated according to the Greenspector emission factors taking into account the energy consumed and the wear of the battery (impact on manufacturing). The impact of the network and the data center is taken into account with the internet intensity.

This impact is reduced to the consultation of a page.

Firefox Focus by its low consumption is first. Samsung, which has average power consumption, is in second place thanks to good data management.

The most impactful browsers (Ecosia, Edge, Mint and Opera Mini) have high power consumption and poor data management..

Introduction

This study was carried out by Greenspector, a company specializing in the impact of digital technology, and EVEA, specializing in analyzes of the environmental impact of products. This study is based on:

• a calculation methodology initiated as part of the CONVINcE project on the energy consumption of video. A project involving several players such as Orange, Sony …
• energy and resource consumption measurements carried out on the myCANAL application to support hypotheses
• collection of data on the use and infrastructure of Canal +
• a bibliographic study to identify and correlate emission factors and energy consumption

Study summary :
– Methodology
– Results : consumption, overall impact and projection
– Areas for improvement
– Conclusion – points to remember
– Chief Digital Officer – Canal+ testimony

Definition of visualization

Visualization quality influences end-to-end power consumption. We have taken the following 3 main definitions:

• SD (Simple Definition)
• HD (High Definition)
• UHD / 4K (Ultra High Definition)

The definition depends on 3 factors:

• compatible program availability
• material compatibility in terms of quality
• the quality of the connection (the quality of myCANAL videos is adapted according to the connection speed).

Greenspector’s exploratory measurements on myCanal show the impact of SD, HD, or UHD video consumption on smartphones, and then on laptops:

Bibliographic sources were used for the consumption of other platforms such as Consoles (Source 1), TV (Sources 1 and 2), Set-Top-Box (Sources 1 and 2). The consumption of Canal + decoders supplied by Canal + was also used.

Depending on the different equipment configurations, we obtain energy consumption which varies from 1.3 to 108 Wh / h, i.e. a ratio of 1 to 80:

Means of connection to the network

To access the services, the infrastructure considered takes into account: the user’s equipment (Box among others), access to networks (GSM, Fiber, etc.), and the heart of the IP network.

We used calculation methods that are widespread in the scientific literature and standardized by ETSI. The principle is to take an “energy / typical use” ratio in Wh/Go. Although the network infrastructure has a fairly fixed consumption and does not depend on the use, this calculation method makes it possible to assign a global impact to a use (here one hour of video). In addition, it allows to study the improvement of networks in terms of efficiency. Beyond the search for improved energy efficiency, it also makes it possible to assess pressure on the network and to take into account the improvement in the capacity of the infrastructure.

As explained in the CONVINcE report:

“As we are looking for an order of magnitude in energy saving, we suppose that decreasing by 30% the traffic volume in the core network induces a decrease of same ratio in network dimensioning and consequently a decrease of 30% in energy consumption in the core IP network.”

We have studied the literature and listed metrics ranging from 1.3Wh / Go (figure for FTTH fiber) to 600Wh/Go. These factors fluctuate depending on the infrastructure assessment date, method (Top Down or Bottom Up) and technology. It is clear, however, that the efficiency improves over the years.

We have taken:

• 13 Wh / Go for the core network (source CONVINcE)
• 30 to 40 Wh / Go for the fixed network
• 150 Wh / Go for the GSM network (source CONVINcE)

For TNT and satellite, there are few data. However, we based ourselves on a BBC study for TNT.

Content Delivery Network

Content Delivery Networks (CDNs) are servers used to limit the load on “Top of Head” servers (serving videos) and to provide a flow as close as possible to the user. Canal+ uses CDN providers on the market but also uses its own infrastructures.

The methodology for estimating the energy intensity per GB is to bring the estimated consumption of the data center down to throughput during peak periods. Canal+ indeed knows the number of physical servers, their types as well as their speeds. As the servers are hosted by a host, certain assumptions have been made to estimate the actual consumption: among other things, an assumption of PUE (Power Usage Effectiveness) of 2, consumption per server of 250W, and a server load of 50%. The consumption of routers and storage is considered negligible compared to the consumption of servers. (Sources 1, 2 , and 3)

The energy intensity obtained is 0.13 Wh / Go, with a different value between VOD and Live. Note that this value is calculated in the event of a peak (football match for example). It can be lower (use of the total capacity of the data center) or higher (during periods of low traffic).

For lack of data, the hypothesis of the same energy intensity (Wh / Go) was taken for CDNs outside Canal + (50%). For comparison and verification, the studies listed display values from 0.04 to 1 Wh / GB. These differences can be explained by various factors:

– Improving the efficiency of data centers, old studies, therefore, lead to higher figures,

– Top-Down approaches that have a higher estimate than Bottom-Up studies (like this estimate on CDNs).

AWS application servers Excluding video: using Mycanal (catalog presentation, authentication, etc.) and watching videos involve requesting services hosted on servers (rights management, etc.). The APIs used are hosted on AWS instances.

Canal+ rents AWS instances and knows the number of VMs. A part of these VMs is purely dedicated to providing ancillary services to video.

It is difficult to know the power consumption of AWS instances because no communication or information is provided by Amazon. According to an expert, we took a value of 20W (taking into account a PUE of 2) (Source: Interview of experts on virtualization from the company Easyvirt).

We have assumed a uniform distribution of consumption concerning the number of hours visualized and we obtain a value of 0.14 Wh / h.

Video encoding servers

The “Headend” servers allow you to format videos, “package” them to the user’s format … For the OTT, up to 150 packages may be available for a single video. Here is the workflow for the OTT.

The most consuming parts are video encoding and decoding. The workflow is distributed over specific servers (for encoding) and classic servers (for formatting and packaging).

We took the figures from the CONVINcE project (considering Harmony servers identical to those used by Canal +) to estimate the energy, as well as the Canal + server data:

• For IPTV: 0.09 Wh for one hour of video
• For the OTT: 0.30 Wh for one hour of video

This difference is explained by the fact that OTT is encoded in several formats, unlike IPTV which is encoded in a high definition format.

Results – global projection

The supply of renewable energy to AWS infrastructures and Canal + CDNs hosted by Interxion has not been taken into account.

In one hour, on average, here are the flows that pass through the network:

500 000 hours of video

900 TB of data

3.6 GB / hr average throughput

The number of viewing hours for Canal+ subscribers has been broken down according to the parameters listed above.

The unit data obtained previously are then projected on these uses to obtain the overall consumption. By taking these results, we can obtain the usage intensities of each part (Terminal, Network, Server) to check the consistency of the overall consumption.

Intensity analysis

The usage intensities obtained can be compared to the Shift Project and IEA studies. This intensity is calculated by taking the distribution of devices, the use of Canal +, and keeping only the IP transfer part (without Satellite or TNT).

It is clear (and shared by the IEA) that the Shift Project study overestimates grid consumption. For servers, we have a fairly low value but are quite confident considering that it is based on data from a known infrastructure (with the uncertainty from Amazon servers and third-party CDNs). The estimate of the terminal part of the Shift Project seems to us to have been underestimated (shared by IEA). It seems that the IEA also underestimated many parameters and seems not to have taken into account the influence of the definition on the consumption of the terminal, certain elements such as boxes, and the consumption of new TVs that consume more. The CONVINcE study and the Sauber/Koomey analysis also validate the consistency of our study.

Impact of playing an hour of video

Across the Canal+ fleet, the average end-to-end consumption is 214 Wh per hour of video. For comparison, the IEA study announces consumption between 120 and 240Wh per hour. The breakdown is as follows:

The impact in average CO2 equivalent by type of access is as follows (with the assumptions specified in the paragraph CO2 emission factors where the manufacture of Satellite, DTT, network and server hosting infrastructures has not been taken. into account)

By taking the type of connection:

The impact ranges from 20 to 66 g CO2 eq, it depends on several parameters:

• the more or less energy consumption of the device (for example Smartphone vs TV),
• embodied energy and material life,
• the means of access to the network (for example GSM access has a greater impact than wired access),
• the viewing quality which will influence above all the share of the network (depending on a cost per Wh / Go),
• the number of materials to access the service.

By taking real uses (see the end of the document), the average is 28g CO2eq. If we take only the IP part, the average value is 37g CO2eq.

For comparison, the IEA study (2020) announces 8g CO2eq for France (for the use phase only). Another study for the US (2014) announces 360g CO2eq on the use phase (and 420g CO2eq with manufacturing). If we take a US energy mix, we get 202g which brings us closer to this study. The lower value can be explained by the differences in assumptions, in particular on the energy intensity of the network. For example, if we take for our study a TV with 4K reception, IEA announces 20g CO2eq while we rather estimate 14g (37g with the manufacturing phase).

If we look at the usage / manufacture ratio, in some cases the use has more impact (UHD in particular), while in others it is the manufacturing (IP TV or PC in HD for example).

In this same study, the estimate of the purchase of a DVD is 400g EqCO2, which therefore leads to the impact of watching a 2-hour video. 5 times less than that of buying a DVD in France and equivalent in the US.

Consumption and overall impact

The result of the total energy consumption of viewing Canal+ videos over IP is 900 GWh per year with a greenhouse gas impact of 159,000 tonnes CO2eq.

For comparison, annual French consumption is 473 TWh per year (Source RTE) and France’s 2017 carbon footprint (national emissions + imports) is 749 Mt CO2 eq (source: Haut Conseil pour le Climat – 2019 report). The consumption of the Canal + fleet by IP is therefore 0.18% of energy consumption and 0.016% of the French carbon footprint.

The end-to-end distribution is as follows:

Most of the consumption is on the user’s premises (terminal and part of the network access). Indeed, it is necessary to have the equipment (TV, Box, Smartphone …) which is not shared like the servers.

To validate the consistency of this projection, we took the consumption of CDNs specific to CANAL as well as to suppliers. We have a consumption of Canal + CDNs of 2.6 GWh (and estimated at 7 GWh for suppliers) excluding video head-ends which are not at Interxion. We get 12 GWh with the projection, which validates the model.

If we look at the distribution of the impact in greenhouse gases, we have the following distribution:

A large part of the impact comes from the manufacture of user terminals. On the network part, the manufacture of Boxes (FAI, Satellite …) also has a significant impact.

Areas for improvement to limit the impact of services

Strengthen bitrate downsizing

To date, except in Africa, or on a cellular network (so as not to empty the customer’s subscription), the quality of the video is adequate . On PC, quality adaptation is possible but access is not necessarily easy.

Making the possibility of reducing the size more accessible by different means (improvement of the interface, communication, etc.) would make it possible to redirect some of the users to a lower but sufficient quality.

Taking into account the increase in video quality and that of network performance, quality caping by users of Canal + services should represent in 3 years a gain of 20% in average speed compared to that generated by uncapped use.

In this axis, several elements have not been included in the gain projection but are possible to help the user in his impact. For example, the Greenspector mobile measurements show that it is better (under favorable conditions such as wifi) to use downloading rather than streaming. Indeed, here is the comparison for a 45mn video (with 5mn download):

This is partly explained by the fact that when viewing the downloaded video, the radio cell is not used while it is much more during streaming.

Improve the interface and the software layer

Part of the impact of viewing an hour of a video comes from the interface. Indeed, viewing the catalog, managing subscriptions (via APIs), processing playlists … are necessary functions. Greenspector measurements showed that this could represent 10% of terminal consumption:

Improving the interface on all platforms (smartphone, PC, etc.) would therefore make it possible to obtain significant gains. It would also allow, beyond reducing the impact, to limit the exclusion of certain people as well as the obsolescence of platforms.

Among the actions identified:

• Switch to the dark mode
• Reduce the overall impact of the software layer
• Improve UX
• Limit the integration of third-party libraries

Results

Here is the projection of the various energy gains:

The improvements compensate for the increase in energy consumption and even allow a gain of 14% compared to the current situation. For the greenhouse gas impact, we obtain a gain of 8%.

There are many ways to reduce the carbon impact of streaming activities for Canal + by 30%, and the actions put in place will make it possible to make a gain of 26% on the environmental footprint of services and in particular -31% for the consumption in OTT only.

Pierre-Emmanuel Ferrand, Chief Digital Officer at CANAL+

Testimony

– How does this assessment and improvement process fit into the Group’s strategy?

CANAL+ is anchored in its time. We have decided to become more involved in a major issue of our time, dear to our subscribers and users of myCANAL: the protection of our environment. CANAL+ was very early on as a pioneer in eco-responsible approaches. first. In addition to the rental model of decoders, which is very virtuous from the point of view of the circular economy, Canal+ organized in 1988 the recovery of old decoders to ensure their return to service or their recycling. Moreover, as a publisher, We have produced eco-responsible productions including series that have been exemplary on this subject, Baron Noir, L’Effondrement, and more recently OVNI (S).

-What main lessons/contributions do we draw from this work (on the design of services)?

This work allows us first of all to identify the technical projects to prioritize to minimize the carbon footprint of myCANAL video consumption as much as possible. At the same time, the lessons guide us on the awareness messages to relay to our users, throughout our future developments. This commitment to cooperation between our technical developments and our users is the key to consumption that has less impact on the environment. 

– What role do users play?

Protecting the environment is a priority for them. Their role is central to our approach. Our challenge is to offer them a platform offering the best content and the best video quality adapted to their equipment and their reception capacities to reduce the effects on the environment. By raising their awareness and supporting them in responsible actions, they too will be able to get involved, as they do in other areas for a more eco-responsible society.

The 2021 edition of this ranking is available! Read the study

The web browser is a main tool on a mobile device. Not only for websites but also for new applications based on web technologies (progressive web app, games, …).

In our 30 most popular mobile apps ranking, among the mails, direct messaging, social networks, browsers categories, web browsing and social networks are on average more consuming than games or multimedia applications. The ratio would be 1 to 4 between the least and most energy consuming applications.

Decreasing the environmental impact of the digital life and increasing the autonomy of phones go in part through the choice of a good browser. Just as if you want to reduce the impact of your mode of transport, it is important to take the most efficient vehicle.

Last year we published the 2018 ranking of the least energy-consuming browsers, we made a new edition for 2020, more complete, made with our GREENSPECTOR App Mark.

Overall Ranking

The average rating is 36/100 which is pretty mediocre. It can be explained by low notes for each of the metrics.
The three least energy-consuming browsers are: Vivaldi, Firefox Preview, Duck Duck Go.

Overall energy consumption (in mAh)

The median is 47 mAh and a large part of the browsers are in this consumption level (8/18 are in the 2nd quartile).
Note that the last 3 browsers in the ranking are recognized by a consumption 75% higher than the median. Firefox, Qwant and Opera Mini are indeed very energy intensive.

Energy consumption of navigation (in mAh)

The last 3 browsers of the global ranking (Opera Mini, Firefox and Qwant) as well as Mint consume much more than the average (between 20 and 35 mAh against 16 mAh).

It is sufficient to say that for most browsers (apart from the previous exceptions), pure navigation is not going to be the reason for the difference in overall consumption. This is mainly due to the use of visualization engines. Most browsers use the Chromium engine. For Opera Mini, the specificity is that a proxy is used and can compress the size of the sites. It seems that this proxy is not good for the energy, in fact the decompression on the user’s phone consumes a lot of energy.

For the Firefox app, over-consumption of energy is a known and shared thing, this is one of the reasons why Mozilla is under development of a new browser. Internal code name is Fenix ​​and public one is Preview. The measures in this ranking are rather encouraging on consumption (in the average).
For Qwant, this is due to the use of the Firefox engine! The measurements between Qwant and Firefox are indeed very close.

Power consumption of features (in mAh)

The main feature that is browsing the web also requires other important features: new tab opening, enter an address in the taskbar … Indeed, when we open a new tab, each browser offers different features: mainly used websites, latest news, …

On pure navigation, browsers differ little, there are significant differences in energy consumption on other features with a ratio of more than 3 (between 4 mAh and 12 mAh).

Note that the first 3 (Firefox Focus, Firefox Preview and Duck Duck Go) have a simple homepage. The consumption of the browser in Idle (inactivity) is then very low. Functional sobriety pays the consequences!

When launching browsers, the energy consumptions are quite similar to each other. Note, however, that opening a tab and writing a URL are actions that are performed several times. If we take a daily projection of 30 new tabs and 10 URL entries, we can still see the difference between browsers and the large advance of Firefox Preview and Focus!

The basic features are not insignificant in the overall consumption.

Projection of autonomy (in number of hours)

If we take this energy data and project it for a navigation of several websites, we identify the maximum time that the user can navigate to the complete discharge of his battery:

Data consumption (in MB)

The difference in data consumption between browsers (8 MB difference) is explained by the pure navigation and the different features.

On the navigation, we explain this difference:

• some applications do not manage the cache at all for reasons of data protection and confidentiality (Firefox Focus)
• proxy usage that optimizes data (Opera Mini)
• a difference in the implementation of cache management. It is possible that some browsers invalidate the cache and that data is loaded while they are cached.
• additional data consumption continues in the background (idle tabs, background data not blocked …)
• download performance differences that increase the duration of the measurement. Indeed, if a browser is powerful, the counterpart is that many more data are potentially loaded in the background.

The difference in overall consumption can also be explained by the data consumption of the basic functionalities:

Many browsers are very consuming. We note the 3 MB of Qwant that seem abnormal!
It can be considered that for browsers, this consumption should be close to 0. Indeed, the main feature of a browser is to display a website, any feature (and associated consumption) can be considered as “over-consumption”.
In this context, many browsers consume data when writing the URL. This is mainly explained by the URL proposal features. There is indeed exchange between the mobile and the servers, either directly by the browser or by the associated search engine.

For example, for the Yandex browser below, the details of data exchanges when writing a URL show more than 400 KB of data exchanged.

In contrast, below, trading for Brave is frugal with less than 2 KB.

Browser performance (in seconds)

The measures allow us to evaluate the performance of the key features:

• Launching the browser
• Adding a tab
• Writing a URL
• Removing the cache
• Mozilla Kraken Bench

NB: This study does not evaluate the display performance of websites. However, the Mozilla Kraken benchmark allows this in part by evaluating the functionality of browsers.

Efficiency of browsers (in mAh/s)

We can evaluate the efficiency of browsers by taking the performance of the Mozilla Kraken benchmark and the associated energy. Efficiency is the energy consumption per unit of time:

Samsung, Opera Mini and Opera are the most efficient browsers. This ranking is different from that of overall energy consumption. For Samsung Internet, this first place in terms of efficiency on a Samsung hardware can be explained by the optimized link that can have the manufacturer with a pre-installed software. The Opera browser has a good positioning (2nd for overall consumption and 3rd for efficiency).

Track of improvements

It is possible to improve the consumption of navigation.

For the user :

• Choosing an efficient browser
• Use bookmarks or favorites to avoid going through the entry bar
• Configure the energy saving options of browsers (mode or dark theme, data server …)

For developers of sites:

• Eco-design their site
• Test and measure on different browsers to identify different behaviors and take them into account

For browser editors:

• Measure energy consumption and efficiency
• Eco-design features
• Reduce resource consumption of recurring features (url write, new tab …)
• Make the homepage as simple as possible.

Measurement protocol

The measurements were carried out by the laboratory GREENSPECTOR App Mark on the basis of a protocol Standardized: Samsung S7 Smartphone, Android 8, Wi-Fi, 50% brightness. Between 4 and 8 iterations were carried out and the value used is the average of these measurements. Measurement campaigns follow a scenario that evaluates browsers in different situations.

Evaluation of features

• Launching the browser
• Adding a tab
• Writing a URL in the search bar
• Remove tabs and clean the cache

Navigation

• Launch of 6 sites and wait for 20 seconds to be representative of a user journey

Benchmark browser

• The Mozilla Kraken tests JavaScript performance

Evaluation of browser inactivity periods

• At launch (this allows to evaluate the homepage of the browser)
• After navigation
• After closing the browser (to identify closing problems)

For each iteration, the following tests are performed:

• Deleting the cache and tabs (without measurement)
• First measure
• Second measure to measure the behavior with cache
• Remove cache and tabs (with measure)
• System shutdown of the browser (and not only a closure by the user to ensure a real closing of the browser)

The average measurement therefore takes into account a navigation with and without cache.

The main metrics analyzed are: display performance, power consumption, data exchange. Other metrics such as CPU consumption, memory consumption, system data … are measured but will not be displayed in this report. Contact GREENSPECTOR for more information.

In order to improve the stability of the measurements, the protocol is completely automated. We use an abstract GREENSPECTOR test description language that allows us to fully automate this protocol. Browser configurations are the default ones. We have not changed any settings of the browser or its search engine.

Rating

A notation out of 100 makes it possible to classify the browsers between them. It is based on the notation of 3 main metrics:

A weighting ratio is applied to the 5 step levels (from 5 for dark green to -1 for dark red) as described in the following example table:

The score of this application is then calculated at 61/100 for the energy metric.
Once the score of each of the three metrics obtained on 100 points, the total score of the application is calculated with equal weighting of the three metrics:
Total Score = (Performance Score + Energy Score + Score Data) / 3

Browsers evaluated

Some browsers were discarded because they did not allow the tests automation. For instance, UC Browser and Dolphin browsers could not be measured. Beyond automation, this is a symptom of a accessibility issue of the application. To improve the accessibility of applications for people with visual impairments (among others), it is necessary to set up buttons labels. The automation that we realized is based on this information. In the end, these browsers do not appear in the ranking, but we can consider that accessibility problems are in all cases a crippling problem.

Note : The 2020 ranking is hardly comparable to that of 2018. Indeed, our protocol having completely evolved, the tests are thus more advanced and automated.

Discover our lastest study: the 2019 Playstore Efficiency Report!

In a previous article on this blog, we introduced you the 5 keys to success of a mobile application. We present today the 12 rules by business indicator to respect that will make the success of your application.

Inclusion

• The application must be usable in degraded network conditions
• The application should not require a recent OS version like Android to be used. Some users do not follow updates, either voluntarily or because of their platform that does not allow them. According to our “PlayStore Efficiency Report 2019“, only 70% of apps on the store are compatible with all versions of Android.
• The application must comply with the accessibility rules and must not exclude users with disabilities.
• The app should work well on older phones too only on recent and latest models. This criterion will be degraded if you do not respect that of sobriety. 1/4 of the Google PlayStore applications are 10% of the oldest mobiles. (Source: PlayStore Efficiency Report 2019)

Sobriety

• The application must limit its energy consumption so as not to empty the user’s battery. Moreover, in case of excessive consumption, the system notifies the user of anapplication as a consumer. Some energy-intensive applications can reduce battery life to less than 3 hours. (Source: PlayStore Efficiency Report 2019)
• The application must limit its resource consumption (number of CPUs, memory occupied, data exchanged) in order to avoid any slowness or pollution of the other applications (for instance because of the memory leak). 50% of Google PlayStore apps continue to process after the app closes. (Source: PlayStore Efficiency Report 2019)
• The application must limit its network consumption in order to not involve any load on the data centers and thus avoid the additional costs related to the unnecessary congestion of the servers.

Performance

• The first launch of the application must be fast: otherwise, it is possible that your users won’t go further, the inclusion criterion will not be respected either.
• The loading times of the application must be acceptable in all network situations.

Discretion

• The application requires few or no permission. Do you really need to consult the list of contacts of your user? It’s all the more important to optimize this since the more permissions there are, the more the application consumes resources. This will therefore negatively influence the performance criterion.
• The application has little or no tracker. The integration of a large amount of trackers implies a greater consumption of resources but can also cause bugs. This observation is even more true that the connection is degraded. On average, adding a tracker causes an over-consumption of resources of 8.5%.(Source : PlayStore Efficiency Report 2019)

According to our “PlayStore Efficiency Report 2019“, trackers, analytics and permissions are ubiquitous (44% applications have more than 5).

Ecology

• The application must respect the sobriety criterion, the CO2 impact linked to the use is lower as well as the pressure of the resources on the components of the equipment of the user (battery obsolescence, loss of performance). As a result, the user is less likely to renew their equipment, which reduces the risk of obsolescence of his material. Our latest study shows that mobile apps contribute at least 6% of CO2 emissions digital.

Some tracks for the improvement of its GREENSPECTOR App Mark score

Directly improve the application

Several metrics are evaluated by the GREENSPECTOR App Mark and can be directly improved.

• Minimum SDK version: Allow Android older versions to avoid the exclusion of users using older generation platforms.
• Number of trackers: the fewer trackers the application has, the more it will respect the user’s data as well as the protection of his privacy. In addition, trackers via processing and data exchange increase the consumption of the application.
• APK size: the bigger the binary of the application, the more the network is solicited and the less efficient the application. In addition, a large application size will use the limited storage space of some users.
• Loaded data: number of loaded data throughout the test run. Limiting this data will reduce the consumption of resources on both the smartphone and the network.
• Data loaded in the background: when the application is not used, it must limit its impact and send or receive as less data as possible.

More global metrics

Some metrics are directly related to the impact of the application and its efficiency. It is possible to act on it via the previous metrics, see by other axes (functional optimization, improvement of the source code …)

• CO2: the more the application consumes energy, the more the battery is solicited and become obsolete. This may lead to a premature renewal of the battery or even the smartphone and therefore to a higher environmental impact. Let’s not forget that most of the environmental impact of a smartphone is predominant in its manufacturing phase than in its use phase: keeping it longer reduces its overall impact.
• Energy Overconsumption: if the application overconsumes, it increases the environmental impact but also creates discomfort for the user especially on the loss of autonomy and generates an additional stress factor.
• Performance after the first installation: applications sometimes perform additional treatments during the first launch, so the launch time is sometimes increased. It is necessary to limit its treatments because this loss of performance can be inconvenient for the user.
• Performance: the launch time of the application is an important data for the user. It is necessary to reduce it to the maximum while consuming the least possible resources.
• 3G Performance: in poor network conditions, it is necessary to master the performance to maintain a good user experience. It is even possible that some users do not have access to the application in the case of degraded performance. Having a frugal service that takes into account the constraints of mobility is therefore a key to success.

What about now?

You are certainly wondering how your application is doing on these 5 indicators. Is it rather virtuous? Is there any risk? How is it ranked against its competitors? Do you have quick progress actions? If you ask us, we will tell you! Contact-us, and we will introduce you to your own inclusive, sober, fast, ecological and discreet evaluation – just like your application very soon.

During the Mobile One event, GREENSPECTOR announces a survey of the major mobile consumer trends of the Google Play Store. More than 1000 applications were sifted through for Performance, Sobriety and Inclusion by the measurement tools developed by GREENSPECTOR.