Android downloading keep-alive

We are proud to serve your working mirrors This has to be done only the first time you are installing an unknown APK file. It is most commonly located in the Downloads folder. I strongly recommend Keep It Alive as good social software. Note that the APK file can run on every popular android emulator. You can also send DMCA reports here. Version 1. Here is what changed: - Posts and comments now show "coined by" users - Privacy view settings have been updated - Navigating between screens is now much faster - Notifications, conversations, and highlights now load in background - Other bug fixes and improvements.

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Process input events. Support game controllers. Achieve proper frame pacing. Frame pacing in Vulkan. It's also important to ensure that prefetching doesn't delay application startup while the app waits for the prefetch to complete. In practical terms that might mean processing data progressively, or initiating consecutive transfers prioritized such that the data required for application startup is downloaded and processed first. How aggressively you prefetch depends on the size of the data being downloaded and the likelihood of it being used.

Generally speaking, it's good practice to prefetch data such that you will only need to initiate another download every 2 to 5 minutes, and in the order of 1 to 5 megabytes. Following this principle, large downloads—such as video files—should be downloaded in chunks at regular intervals every 2 to 5 minutes , effectively prefetching only the video data likely to be viewed in the next few minutes.

Note that further downloads should be bundled, as described in the next section, Batch transfers and connections , and that these approximations will vary based on the connection type and speed, as discussed in Modify your download patterns based on the connectivity type.

You could choose to prefetch an entire album, however should the user stop listening after the first song, you've wasted a significant amount of bandwidth and battery life. A better approach would be to maintain a buffer of one song in addition to the one being played. For streaming music, rather than maintaining a continuous stream that keeps the radio active at all times, consider using HTTP live-streaming to transmit the audio stream in bursts, simulating the prefetching approach described above.

Many news apps attempt to reduce bandwidth by downloading headlines only after a category has been selected, full articles only when the user wants to read them, and thumbnails just as they scroll into view. Using this approach, the radio will be forced to remain active for the majority of users' news-reading session as they scroll headlines, change categories, and read articles.

Not only that, but the constant switching between energy states will result in significant latency when switching categories or reading articles. A better approach would be to prefetch a reasonable amount of data at startup, beginning with the first set of news headlines and thumbnails—ensuring a low latency startup time—and continuing with the remaining headlines and thumbnails, as well as the article text for each article available from at least the primary headline list.

Another alternative is to prefetch every headline, thumbnail, article text, and possibly even full article pictures—typically in the background on a predetermined schedule. This approach risks spending significant bandwidth and battery life downloading content that's never used, so it should be implemented with caution. One solution is to schedule the full download to occur only when connected to Wi-Fi, and possibly only when the device is charging.

This is investigated in more detail in Modify your download patterns based on the connectivity type. Every time you initiate a connection—irrespective of the size of the associated data transfer—you potentially cause the radio to draw power for nearly 20 seconds when using a typical 3G wireless radio. An app that pings the server every 20 seconds, just to acknowledge that the app is running and visible to the user, will keep the radio powered on indefinitely, resulting in a significant battery cost for almost no actual data transfer.

With that in mind it's important to bundle your data transfers and create a pending transfer queue. Done correctly, you can effectively phase-shift transfers that are due to occur within a similar time window, to make them all happen simultaneously—ensuring that the radio draws power for as short a duration as possible.

The underlying philosophy of this approach is to transfer as much data as possible during each transfer session in an effort to limit the number of sessions you require. That means you should batch your transfers by queuing delay tolerant transfers, and preempting scheduled updates and prefetches, so that they are all executed when time-sensitive transfers are required.

Similarly, your scheduled updates and regular prefetching should initiate the execution of your pending transfer queue. For a practical example, let's return to the earlier examples from Prefetch data. Take a news application that uses the prefetching routine described above. The news reader collects analytics information to understand the reading patterns of its users and to rank the most popular stories. To keep the news fresh, it checks for updates every hour.

To conserve bandwidth, rather than download full photos for each article, it prefetches only thumbnails and downloads the full photos when they are selected. In this example, all the analytics information collected within the app should be bundled together and queued for download, rather than being transmitted as it's collected.

The resulting bundle should be transferred when either a full-sized photo is being downloaded, or when an hourly update is being performed. Any time-sensitive or on-demand transfer—such as downloading a full-sized image—should preempt regularly scheduled updates.

The planned update should be executed at the same time as the on-demand transfer, with the next update scheduled to occur after the set interval. This approach mitigates the cost of performing a regular update by piggy-backing on the necessary time-sensitive photo download.

It's generally more efficient to reuse existing network connections than to initiate new ones. Reusing connections also allows the network to more intelligently react to congestion and related network data issues. Rather than creating multiple simultaneous connections to download data, or chaining multiple consecutive GET requests, where possible you should bundle those requests into a single GET.

That said, closing a connection too early can prevent it from being reused, which then requires additional overhead for establishing a new connection.

A useful compromise is not to close the connection immediately, but to still close it before the inherent timeout expires. Use Network Profiler to track when your application makes network requests. You can monitor how and when your app transfers data and optimize the underlying code appropriately. Figure 3 shows a pattern of transferring small amounts of data roughly 15 seconds apart, suggesting that efficiency could be dramatically improved by prefetching each request or bundling the uploads.

Figure 3. Tracking network usage. By monitoring the frequency of your data transfers, and the amount of data transferred during each connection, you can identify areas of your application that can be made more battery-efficient.

Generally, you will be looking for short spikes that can be delayed, or that should cause a later transfer to be preempted. To better identify the cause of transfer spikes, the Traffic Stats API allows you to tag the data transfers occurring within a thread using the TrafficStats. For example:. The library also tags and untags sockets when recycled through keep-alive pools. Socket tagging is supported in Android 4.

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