Patent Publication Number: US-10785511-B1

Title: Catch-up pacing for video streaming

Description:
BACKGROUND 
     Video data may be sent between computing devices over a network. In some examples, videos may be encoded by an encoding computing device, separated into packets, sent to a recipient computing device, decoded and played back while subsequent portions of the video are still being transmitted to the client computing device by the encoding computing device. Such video transmission and playback is often referred to as “streaming”. In some other examples, videos data may be encoded by a server and sent to one or more remote computing devices for further processing. Network conditions can change during transmission of video for various reasons, and may sometimes deteriorate to an extent causing delays in streaming of video data. Conversely, in some examples, network conditions may ameliorate leading to additional link capacity beyond current usage. In some examples, computing devices may adjust characteristics of the video stream in order to compensate for changing network conditions. For example, encoding computing devices may adjust the bitrate of the video stream to account for a change in bandwidth. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  depicts a system effective to perform catch-up pacing for video streaming, in accordance with various embodiments of the present disclosure. 
         FIG. 2  depicts an example of a technique for performing catch-up pacing for video streaming, in accordance with various aspects of the present disclosure. 
         FIG. 3  depicts an example technique for dynamically adjusting a pacer buffer multiplier in order to perform catch-up pacing for video streaming, in accordance with embodiments of the present disclosure. 
         FIG. 4  is a block diagram depicting an example architecture of a computing device that may be used in accordance with various aspects of the present disclosure. 
         FIG. 5  depicts a flowchart illustrating an example process for performing catch-up pacing for video streaming, in accordance with various embodiments of the present disclosure. 
         FIG. 6  depicts a flowchart illustrating another example process for catch-up pacing for video streaming, in accordance with embodiments of the present disclosure. 
         FIG. 7  depicts an example system for sending and providing data over a network, in accordance with various embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description, reference is made to the accompanying drawings, which illustrate several embodiments of the present invention. It is understood that other embodiments may be utilized and mechanical, compositional, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present disclosure. The following detailed description is not to be taken in a limiting sense, and the scope of the embodiments of the present invention is defined only by the claims of the issued patent. 
     Video may be encoded with various transmission attributes (e.g., bitrates, resolutions, profiles, frame rates, etc.) prior to sending the video over a network to a remote computing device. Web Real-Time Communication (“WebRTC”) comprises a number of communication protocols and application programming interfaces (“APIs”) that enable real-time communication over peer-to-peer connections. WebRTC may use Real-time Transport Protocol (“RTP”) to transmit audio and/or video over a network. 
     Techniques for WebRTC and video streaming generally are described herein. In digital video technology, a video may be represented by a number of video frames that may be displayed in sequence during playback. A video frame is comprised of rows and columns of pixels. The resolution of a particular video frame is described by the width of the frame, in terms of a first number of pixels, and by the height of the frame, in terms of a second number of pixels. Video frames may be compressed using different picture types or frame types, such as intra-coded picture frames (“I-frames”), predicted picture frames (“P-frames”), and/or bi-directional predictive frames (“B-frames”). The term “frame” can refer to an entire image captured during a time interval (e.g., all rows and columns of pixels comprising the particular image). The term “picture” can refer to either a frame or a field. A “field” is a partial image of a frame, which can be represented by either the odd-numbered or even-numbered scanning lines of the frame. Reference frames are frames of a compressed video that are used to define future or past frames. A compressed video may comprise one or more frames that do not include all of the pixel data within the frames themselves, but rather reference pixel values of other frames (e.g., reference frames). I-frames include detailed pixel data in order to be self-decodable and to provide reference pixel values for other I-frames. As a result, I-frames do not require other video frames in order to be decoded, but provide the lowest amount of data compression and accordingly, typically require more to send over a network relative to other frame types. P-frames contain only the changes in the pixel values from previous frames, and therefore P-frames use data from previous frames to decompress and decode the P-frame. As a result, P-frames are more compressible than I-frames and require less bandwidth to transmit. B-frames can be decoded using both previous and forward frames for data reference. 
     As used herein, the “size” of a frame may refer to the amount of memory needed to store a particular compressed frame and/or the amount of available bandwidth required to transmit the compressed frame. In at least some examples, frames with higher resolution (e.g., more pixels in the two-dimensional grid of the frame) may be larger in size relative to a lower resolution frame. In some further examples, source video content with higher complexity (e.g., content with higher spatial complexity and/or higher motion content (e.g., temporal complexity)) may be encoded into frames of larger size as the frames may require more bits to encode relative to a less complex frame. In various examples, the complexity of a frame or group of frames may refer to the amount of bits required to encode the frame. As such, the frame size may be an indicator of the complexity of a frame. Frame complexity may be estimated using various methods and may be estimated prior to encoding a frame to generate a compressed frame. For example, raw, uncompressed frames of video data may be high-pass filtered in order to determine a spatial complexity of the frame. Generally, the spatial complexity may refer to an amount of entropy of transformed pixel data included within a frame. Higher spatial complexity generally indicates that more detailed and complex pixel data is present in the frame. The spatial complexity may be correlated to the compressed size of the frame. After the spatial complexity of a frame is determined, an estimated compressed size of the frame may be determined for a given quantization parameter based on the spatial complexity prior to compression of the frame. Accordingly, if the estimated frame size is smaller or larger than desired the quantization parameter used to compress the frame may be adjusted accordingly prior to encoding the frame. In various examples, the spatial complexity may be used as a proxy for estimated frame size. In other words, the spatial complexity value of a particular frame (e.g., an I-frame) may be compared with a spatial complexity threshold value (or tolerance) for a particular quantization parameter to determine if the current quantization parameter will result in a compressed frame that is either too large or too small. Adjustment of the quantization parameter may, in turn, affect the compressed frame size with higher quantization parameters resulting in smaller compressed frame sizes and lower quantization parameters resulting in larger compressed frame sizes. In various other examples, the complexity of raw, uncompressed frames of video data may be estimated using a linear regression. In various other examples, decreasing and/or increasing quantization parameters due to rate control may provide an indication of changing in-scene complexity. 
     Video streams of encoded pictures and/or frames may be encoded into groups of pictures (“GOPs”), and each GOP may begin with an intra-coded frame (I-frame) followed by one or more P-frames and/or B-frames. An I-frame may be referenced by subsequent inter-coded frames of the GOP, as described in further detail below. In at least some examples, I-frames may cause all reference pictures in the DPB (decoded picture buffer) to be flushed, so that no subsequent video frames can reference any frame of image data prior to the I-frame. This means that each GOP is self-decodable (i.e., doesn&#39;t depend on reference frames in previous GOPs). A GOP may set forth the length (in terms of a number of frames) and ordering of frames of a video. An average GOP size may refer to the average number of frames in GOPs encoded by the encoder during a particular period of time. An I-frame typically indicates the beginning of a GOP, followed by one or more P-frames and/or one or more B-frames. Image data representing frames and GOPs may be separated into packets according to RTP for transmission over a network to one or more other computing devices. 
     In various examples described herein, an electronic device including a camera, such as an indoor monitoring system, may be effective to capture video representing a physical environment. The device may continually store a small amount of the captured video (e.g., 2 seconds, 1.5 seconds, 4 seconds, or any suitable time period of video) in a retrospect buffer. The device may monitor the video data stored in the retrospect buffer for indications of motion or other triggering events in the physical environment. If no motion is detected, the contents of the retrospect buffer may be continually deleted (e.g., “flushed”) in favor of newly recorded video data, such that the contents of the retrospect buffer represent the most recent video captured by the device at a given point in time. In various examples, if motion is detected, the device may establish a WebRTC connection (or other suitable connection) with one or more remote computing devices. In some examples, while the network connection is being established, the device may store incoming video captured by the camera in a latency buffer. While video is being stored in the latency buffer during network connection, the contents of the retrospect buffer may be kept. In other words, upon detection of motion, the device may keep the current contents of the retrospect buffer and may begin storing incoming video data captured by the camera in the latency buffer. After the network connection is established with one or more remote computing devices the contents of the retrospect buffer and the contents of the latency buffer may be sent to the one or more remote computing devices. In various examples described below, various acceleration techniques may be used to accelerate the transmission of the contents of the retrospect buffer and the latency buffer to “catch up” the video stream so that a real-time video stream may be provided by the device to the remote computing devices. Thereafter, the device may continue to transmit video data captured by the camera to the one or more remote computing devices in order to provide a “live stream” of the environment monitored by the device. Although typically termed a “live stream” it will be appreciated that various delays due to network congestion, latency, packet loss, etc. may still occur. 
       FIG. 1  is a diagram showing an example system  100 , arranged in accordance with various aspects of the present disclosure. In various examples, system  100  may comprise an electronic device including a camera  101 , one or more processing elements  102 , and a memory  103 . In various examples, memory  103  may comprise the various buffers described herein, including the retrospect buffer, latency buffer, pacer buffer, etc., as well as other types of memory effective to store executable instructions and/or other data. In some further examples, system  100  may include a premotion estimator (PME)  122 . PME  122  may be effective to determine motion data in frames of video data. For example, PME  122  may be effective to match corresponding blocks of pixels between two or more frames of a video  106 . Additionally, in some examples, PME  122  may be effective to determine motion vectors between matching blocks and/or to determine the sum of absolute differences (SAD) and/or the sum of squared differences (SSD) between matching blocks of pixels. In some embodiments, the system  100  can be utilized for surveillance or home security. 
     Camera  101  may include, for example, a digital camera module. The digital camera module may comprise any suitable type of image sensor device or devices, such as a charge coupled device (CCD) and/or a complementary metal-oxide semiconductor (CMOS) sensor effective to capture image data from a local environment of camera  101 . For example, camera  101  may include one or more lenses and may be positioned so as to capture images of a portion of the environment disposed along an optical axis (e.g., a light path) of camera  101 . In the example depicted in  FIG. 1 , camera  101  may be positioned so as to capture video  106  (e.g., frames of image data) representing an in-door environment (e.g., scene  190 —a portion of an interior of the user&#39;s home). Camera  101  may be a dual mode camera device effective to operate in a day mode and a night mode. During day mode operation (sometimes referred to as “RGB mode” operation), an IR cut filter may be interposed in the light path of camera  101  to block infrared light from reaching an image sensor of camera  101 . While in day mode, an image signal processor (ISP) of the camera  101  may adjust various parameters of the camera  101  in order to optimize image quality for image data captured in day mode. For example, the frame rate of a video capture mode of camera  101  may be increased when switching from night mode to day mode. 
     During night mode operation (e.g., IR mode), the IR cut filter may be removed from the light path of camera  101 . Accordingly, camera  101  may detect infrared wavelength light in the infrared portion of the spectrum as well as other portions of the electromagnetic spectrum. In some examples, camera  101  may comprise an infrared light source effective to emit infrared light to illuminate the scene  190  while in night mode. In some other examples, camera  101  may be configured in communication with an external infrared light source. In various examples, camera  101  and/or system  100  may cause an infrared light source to emit infrared light when camera  101  operates in night mode. Similarly, in various examples, when camera  101  is operated in day mode, infrared light emission by an infrared light source may be discontinued. In some examples, system  100  may be effective to determine an ambient light level of the environment and may switch between day mode and night mode operation based on the ambient light level. Various parameters may be adjusted as system  100  transitions between day mode and night mode. Additionally, the automatic exposure (AE) of camera  101  may change in response to different detected ambient light levels. 
     In various examples, one or more of the image processing techniques described herein may be performed by a processing element  102  included within a housing of system  100 , which may be positioned at the location where the images are being acquired by the camera  101 . In other examples, one or more of the image processing techniques described herein may be performed by a computing device accessible via a communications network, such as computing device  180  accessible over network  104 . Accordingly, as depicted in  FIG. 1 , in some examples, system  100  may send image data over network  104  to one or more computing devices  180  for image processing and/or for access by various computing devices such as user device  182  associated with user  184 . In other examples, system  100  may comprise one or more processors and/or a memory effective to perform the various image processing techniques described herein. In various examples, the techniques described herein may be used to catch-up video streaming to a real-time or “live” state. Catch-up video streaming, as described herein, may comprise using unused network channel bandwidth to send and thereby eliminate a backlog of video data stored in various buffers on system  100 . In various examples, after elimination of the backlog of buffered video data, data subsequently sent by system  100  to one or more computing devices  180  may represent the most recent video captured by camera  101  and encoded by an encoder of system  100 . Accordingly, after elimination of the backlog of buffered video data, video data streamed to one or more computing devices  180  may be described as “live” or “real-time”. Of course, there may still be some transmission delay, link latency, processing delay (e.g., compression, packetization) between the time at which video data is captured and the time at which the same video data is received by one or more remote computing devices  180 . Use of the terminology “live streaming” and/or “real-time” herein is intended to account for such delays. 
     In various examples, remote computing device(s)  180  may perform action recognition image processing, human detection, pet detection, and/or other image processing techniques. Additionally, in at least some examples, remote computing device(s)  180  may provide video data received from system  100  to user device  182 . In some other examples, remote computing device(s)  180  may make video data received from system  100  accessible by a user device  182  associated with system  100 . For example, user  184  may own system  100 . A companion application of system  100  may be executed by user device  182  of user  184 . In various examples, user  184  may access video data streamed to remote computing device(s)  180  via the companion application and/or via a web browser. 
     In various examples, video of scene changes in scene  190  and/or significant motion in scene  190  may be streamed to the remote computing device(s)  180  and may be available for viewing by user  184 . Scene  190  may represent a portion of a physical environment. For example, in  FIG. 1 , scene  190  is an interior of an apartment or other dwelling. In various examples, video may be made available to user  184  through a companion application to system  100  and/or through a browser-based system. Additionally, in at least some examples, scene discontinuity determined to be due to illumination changes, compression artifacts, and/or minor motion (e.g., curtains blowing in wind, ceiling fans, etc.) may be disregarded and may not trigger system  100  and/or computing devices  180  to stream video to remote computing device(s)  180 . In at least some examples, remote computing device(s)  180  and/or system  100  may send an alert to user device  182  upon detection of motion in scene  190 . In various examples, user  184  may receive the alert through the companion application of system  100 . 
     Network  104  may be, for example, the internet, an intranet, a wide area network, a local area network, or the like. In some examples, system  100  may be effective to send and receive data over network  104 . The one or more processing elements  102  of system  100  may be effective to execute one or more instructions stored in memory  103  to cause the one or more processing elements  102  to execute various methods as described in further detail below. In  FIG. 1 , examples of a process flow  192  that may be executed by the one or more processing elements  102  are depicted within a dashed box to indicate that actions in process flow  192  may be executed by one or more components of system  100 . 
     In some examples, process flow  192  may begin at action  170 , “Store video data in retrospect buffer”. While system  100  is powered on and operational, camera  101  may be programmed to continually capture video data. The most recently captured video data may be stored in a retrospect buffer. The retrospect buffer may store a comparatively small amount of video data. For example, the retrospect buffer may store 2 seconds of video data. In various other examples, retrospect buffer may store other amounts of video data, depending on the desired implementation. Similarly, in some examples, the retrospect buffer may store a certain amount of video data (e.g., 1 MB, 500 kB, etc.). After reaching capacity, the retrospect buffer may delete the oldest video data stored and replace it with the newest video data captured by camera  101 . Accordingly, in the example where the retrospect buffer stores 2 seconds of video, at any given time the contents of the retrospect buffer may represent the most recent 2 seconds of video data captured by camera  101 . In various examples, retrospect buffer may store compressed video data with relatively small average GOP size relative to video data stored in the latency buffer and video data sent as part of a video stream after establishment of a connection between system  100  and remote computing device(s)  180 . Accordingly, the video data stored in the retrospect buffer may have a high incidence of I-frames allowing for a granular selection of starting points for streaming video data stored in the retrospect buffer to a remote device (e.g., remote computing device(s)  180 ). 
     Process flow  192  may continue from action  170  to action  172  at which a determination may be made whether motion has been detected in the video stored in the retrospect buffer. Motion in the video may be detected in various ways using a motion detection module employed in some combination of hardware and software. For example, temporal and/or spatial differences may be detected between various frames of video data stored in the retrospect buffer. Various threshold may be employed to determine whether or not the differences in the image data between the various frames is significant enough to trigger the motion detection module to begin streaming video data to remote computing device(s)  180 . In various examples, video is continually captured while motion is detected in the retrospect buffer. Accordingly, video data may be continually stored in the retrospect buffer while camera  101  is recording video  106 . 
     If no motion is detected at action  172 , processing of process flow  192  may return to action  170  and camera  101  may continue to capture video of the scene  190  and store the video data in the retrospect buffer. Video data stored in the retrospect buffer may be recorded at a particular bitrate or may be recorded as uncompressed video data (e.g., uncompressed frames) depending on the implementation. Conversely, if motion is detected in the video data stored in the retrospect buffer, the one or more processors  102  may begin storing video data captured by camera  101  in a latency buffer at action  176 . Video data stored in the latency buffer may be recorded at a particular bitrate or may be recorded as uncompressed video data depending on the implementation. Additionally, in some examples, the bitrate of the video data stored in the latency buffer may be different from the bitrate of the video data stored in the retrospect buffer. The latency buffer may be used to store video data while a WebRTC connection is being established between system  100  and remote computing device(s)  180  over network  104  at action  174 . As motion has been detected in the video of the retrospect buffer, the video captured while establishing a connection between system  100  and remote computing device(s)  180  may represent motion of interest to the user, as the motion detected in the retrospect buffer may be likely to continue a short time later. Therefore, at action  178  the video data in the latency buffer may be sent to remote computing device(s)  180  for further processing (e.g., human detection, pet detection, etc.) and/or to make the video data accessible by user  184 . Additionally, at action  178 , system  100  may send the contents of the retrospect buffer to computing device  180 . The video data in the retrospect buffer may be important to show the start of the motion detected in scene  190  as well as to provide some context to a viewer of the video. Accordingly, after establishing the connection with remote computing device(s)  180  at action  174 , the contents of both the latency buffer and retrospect buffer may be sent to remote computing device(s)  180 . However, since, in various examples, it may take a significant amount of time to establish a connection between system  100  and remote computing device(s)  180  (e.g., between 2 and 7 seconds) video data received by remote computing device(s)  180  may be significantly delayed relative to the most recent video captured by camera  101 . For example, if it takes 5 seconds to establish the connection between system  100  and remote computing device(s)  180 , the video stream received by remote computing device(s)  180  may be delayed by a minimum of 7 seconds (e.g., 5 seconds for latency buffer+2 seconds for retrospect buffer). Additionally, using traditional streaming and encoding techniques, this delay may propagate for the duration of the stream. Accordingly, a viewer of the video (e.g., user  184 ) may be watching the video with a significant delay. Accordingly, various techniques described herein are used to accelerate streaming of video stored in the latency buffer and the retrospect buffer in order to eliminate the backlog of buffered video data, so that video data may be streamed in real-time. 
     In various examples, a persistent connection may be used between system  100  and remote computing device(s)  180 . In such examples, a latency buffer may be reduced and/or eliminated as there may be no delay introduced as a consequence of establishing a connection between system  100  and remote computing device(s)  180 . However, the various techniques described herein may still be of use when “catching up” streaming from an unexpected delay (e.g., a decrease in network throughput due to congestion) as well as to catch-up streaming after sending the contents of the retrospect buffer to remote computing device(s)  180 . Additionally, in various examples, the retrospect buffer and/or the latency buffer may be sent out-of-band in order to achieve rapid catch-up to the live video stream. 
       FIG. 2  depicts an example of a technique that may be used for catch-up video streaming, in accordance with various embodiments of the present disclosure. As depicted in  FIG. 2 , upon establishing a connection between system  100  and remote computing device(s)  180 , system  100  may begin sending video data through channel  204  to remote computing device(s)  180 . As previously described, there may be a backlog of several seconds of video data stored in the retrospect buffer and/or the latency buffer of system  100 . System  100  may eliminate the backlog of buffered video data in order to achieve a live-stream or real-time stream with a minimum amount of video delay. 
     Accordingly, in some examples, system  100  may comprise a network monitor  202 . Network monitor  202  may be programmed to monitor link capacity of channels between system  100  and remote computing device(s)  180 . In various examples, network monitor  202  may use historical data of the connection between system  100  and remote computing device(s)  180  to estimate a current channel capacity between system  100  and remote computing device(s)  180 . Historical data may include previous data from previous connections between system  100  and remote computing device(s)  180  and may incorporate peak congestion times, type of network environment (e.g., single family dwelling, multi-family dwelling with shared access points, etc.). Additionally, in some examples, network monitor  202  may monitor round trip time (RTT), jitter, packet loss, negative acknowledgements, etc. in order to determine a link capacity (e.g., available bandwidth) on channel  204 . The one or more processors  102  may receive an indication of the current channel capacity from network monitor  202 . In response, the one or more processors  102  may instruct an encoder of system  100  to generate a bitstream at a bitrate (e.g., encode video data at the bitrate) that is a percentage of the total channel capacity. For example, if the total channel capacity is 1 Mbps, the one or more processors  102  may instruct encoders to encode the video stream to be sent to remote computing device(s)  180  at 800 kbps. As a result, 20% of the capacity of channel  204  is unused and may be used for catch-up pacing. For example, packets representing frames of video data from the retrospect buffer and latency buffer may be streamed using the additional channel capacity. 
     In examples where the contents of the retrospect buffer and latency buffer are uncompressed, system  100  may use a faster-than-realtime encoder to encode the contents of the retrospect buffer and latency buffer. As described in further detail below, the contents of the retrospect buffer and latency buffer may be encoded at a bitrate that approximately represents the difference between the total estimated available bandwidth and a bitrate of the video data being captured by camera  101  (e.g., the currently captured video data transmitted to remote computing device(s) as a live stream). In the example above, a faster-than-realtime encoder may encode the contents of the retrospect buffer and latency buffer at 200 kbps (e.g., 1 Mbps-800 kbps). In some examples, a tolerance may be used to prevent the bit stream from exceeding the total available bandwidth in order to prevent the connection from being dropped. For example, instead of encoding the contents of the retrospect buffer and latency buffer at 200 kbps, the contents may instead be encoded at 180 kbps (a 10% reduction). A faster-than-realtime encoder may encode the uncompressed content and at the selected bitrate (e.g., ˜200 kbps). Additionally, the faster-than-realtime transcoder may be effective to encode the content at a rate that exceeds the frame rate. 
     In examples where the contents of the retrospect buffer and latency buffer are recorded at respective first and second bitrates prior to establishing the connection with channel  204 , a faster-than-realtime transrater or transcoder may be used to transcode the contents of the retrospect buffer and latency buffer at a bitrate that approximately represents the difference between the total estimated available bandwidth and a bitrate of the video data being captured by camera  101  (e.g., the currently captured video data transmitted to remote computing device(s) as a live stream). In the above example, a faster-than-realtime transcoder or transrater may encode the contents of the retrospect buffer and latency buffer at approximately 200 kbps (e.g., 1 Mbps-800 kbps). As described above, in some examples a tolerance band may be used to determine the bitrate at which to encode the contents of the retrospect and latency buffers to avoid exceeding the total channel capacity. In various examples, the tolerance band may reduce the bitrate of the retrospect and latency buffer content encoding by some percentage in order to avoid exceeding the total channel capacity. A faster-than-realtime transcoder may decompress the encoded content and recompress at a different bitrate. Additionally, the faster-than-realtime transcoder may be effective to transcode the content at a rate that exceeds the frame rate. A faster-than realtime transrater may reencode encoded content at a different bitrate by adjusting the quantization parameters of the content during rate control. Additionally, the faster-than-realtime transrater may be effective to transrate the content at a rate that exceeds the frame rate. 
     In various examples, when the contents of the retrospect buffer and/or latency buffer have been sent to remote computing device(s)  180 , the one or more processors  102  may instruct the encoder of system  100  to generate a bit stream at a bitrate that more closely resembles or matches the full channel capacity (e.g., 1.0 Mbps in the example above). Although a 0.2× reduction in the bitrate is used in the example above, any suitable percentage reduction (e.g., ×0.25, ×0.15, etc.) in bitrate may be used in accordance with the various embodiments described herein. 
     Additionally, in various examples, the bitrate of the bit stream may be gradually increased as the contents of the retrospect and/or latency buffer are sent to remote computing device(s)  180 . For example, the one or more processors  102  may receive an indication of the current channel capacity from network monitor  202 . In response, the one or more processors  102  may instruct an encoder of system  100  to generate a bitstream at a bitrate (e.g., encode video data at the bitrate) that is a percentage of the total channel capacity. For example, if the total channel capacity is 1 Mbps, the one or more processors  102  may instruct encoders to encode the video stream to be sent to remote computing device(s)  180  at 900 kbps. As a result, 10% of the capacity of channel  204  is unused and may be used for catch-up pacing. After sending a certain percentage of the video data stored in the retrospect buffer and/or latency buffer, the video stream may be encoded at an increased bitrate (e.g., 950 kbps). For example, after sending a percentage of the video data stored in the retrospect buffer (e.g., 50%, 100% or some other percentage used for the particular implementation) the bitrate of the bitstream may be increased to a value above the initial 900 kbps bitrate. In various examples, the bitrate may be increased in a linear or stepwise manner to close the gap between the total channel capacity (e.g., available bandwidth) and the current bitrate of the video stream (e.g., video data recorded by camera  101  that is not stored in the retrospect buffer and/or latency buffer). As previously explained, the excess bandwidth may be used to transmit the video data stored in the latency buffer and/or retrospect buffer. 
     Additionally, in some examples, prior to motion detection, camera  101  may record video data at a first frame rate (e.g., ˜15 frames-per-second). When motion is detected from video data stored in the retrospect buffer, the frame rate may be increased while the connection between system  100  and remote computing device(s)  180  is being established. For example, upon detection of motion and during the establishment of a connection, camera  101  may increase the frame rate to a second frame rate, higher than the first (e.g., ˜20 frames-per-second) and may store the video data in the latency buffer. Upon establishment of a connection between system  100  and remote computing device(s)  180 , camera  101  may continue to capture video data at a frame rate that is below a full-quality frame rate (e.g., 30 frames-per-second (“fps”) or higher). In various examples, recording and sending video data at a frame rate that is below the full quality frame rate of camera  101  may result in a reduced bitrate of the video stream. Accordingly, if the reduced bitrate of the video stream is less than the full channel capacity by some amount, the excess amount may be used for catch-up pacing for the video data stored in the retrospect buffer and latency buffer in order to eliminate the backlog of video data and to catch the stream up to real-time. Once the backlog of video data stored in the retrospect buffer and/or latency buffer has been sent to remote computing device(s)  180 , the frame rate may be increased to full quality (e.g., 30 fps in the example above). Advantageously, recording video data for the retrospect buffer and/or latency buffer at reduced frame rates may allow the size of the retrospect buffer and/or latency buffer to be minimized, which may be particularly desirable in memory constrained systems. 
     Similarly, in various examples, the encoder may use rate control and GOP size control to adjust the bitrate of the video stream in order to reserve a certain percentage of the bandwidth on channel  204  for catch-up pacing of video data stored in the retrospect buffer and/or the latency buffer. For examples, upon receiving an indication of current channel capacity of channel  204 , an encoder of system  100  may increase the quantization parameter to reduce the size of frames of video data and accordingly reduce the bitrate preserving a certain percentage of the channel capacity for catch-up streaming. Similarly, the encoder may increase the average GOP size which may, in turn, reduce the bitrate due to the less frequent transmission of large-sized I-frames. 
       FIG. 3  depicts an example technique for dynamically adjusting a pacer buffer multiplier in order to perform catch-up pacing for video streaming, in accordance with embodiments of the present disclosure. In various examples, network monitor  202  may determine an indication of current network conditions of channel  204 . Network monitor  202  may be programmed to monitor link capacity of channels between system  100  and remote computing device(s)  180 . In various examples, network monitor  202  may use historical data of the connection between system  100  and remote computing device(s)  180  to estimate a current channel capacity between system  100  and remote computing device(s)  180 . Historical data may include previous data from previous connections between system  100  and remote computing device(s)  180  and may incorporate peak congestion times, type of network environment (e.g., single family dwelling, multi-family dwelling with shared access points, etc.). Additionally, in some examples, network monitor  202  may monitor round trip time (RTT), jitter, packet loss, negative acknowledgements, etc. in order to determine a link capacity (e.g., available bandwidth) on channel  204 . The one or more processors  102  may receive an indication of the current channel capacity from network monitor  202 . 
     Pacer buffer  302  is a packet buffer effective to store packets of video data prior to transmission from system  100  to computing device(s)  180 . Pacer buffer  302  may comprise a programmable multiplier effective to multiply the rate at which packets stored in pacer buffer  302  are sent over channel  204  to computing device(s)  180  relative to a default rate of sending packets from pacer buffer  302 . 
     In various examples, the multiplier of pacer buffer  302  may be dynamically adjusted based on a current bandwidth estimation (e.g., as determined by network monitor  202 ) and/or the average bandwidth conditions typical for the system  100  and channel  204 . As depicted in  FIG. 3 , network monitor  202  may determine current network conditions  328 . Network monitor  202  may provide an indication of the current network conditions  328  (e.g., a current amount of available bandwidth) to the one or more processors  102 . The one or more processors  102  may determine historical network conditions of channel  204 . The one or more processors may determine that current network conditions and historical network conditions indicate that additional bandwidth is available for use beyond what is currently being used on channel  204 . Accordingly, in the example, the one or more processors  102  may increase the multiplier of the pacer buffer  302 . In various examples, the one or more processors  102  may conservatively increase the multiplier of pacer buffer  302  such that the increased traffic resulting from increasing the multiplier does not exceed the link capacity (e.g., available bandwidth) of channel  204 . 
     Similarly, the one or more processors may determine that current network conditions and/or historical network conditions indicate that the current multiplier of pacer buffer  302  is likely to cause network traffic from system  100  to exceed the link capacity of channel  204 . Accordingly, in such an example, the one or more processors  102  may decrease the multiplier of pacer buffer  302  in order to conserve bandwidth. 
     In various examples, internet service providers (ISP) offer so-called “boost” conditions which boost connection speed for the first few seconds upon establishment of a connection such as channel  204  between system  100  and remote computing device(s)  180 . Boost is traditionally used to buffer streaming video to avoid playback interruption. However, the boosted network conditions may be used to temporarily increase the multiplier of pacer buffer  302 . Thereafter, when the boost is finished, network monitor  202  may detect the decrease in available bandwidth and the multiplier of pacer buffer  302  may be decreased in order to avoid exceeding the capacity of channel  204 . 
     Various other techniques may be used to complement the different techniques described above. For example, quantization parameter adjustment may be used to dynamically alter the bitrate during the encoding process. In various examples, higher quantization parameters may be used to encode video data stored in the retrospect buffer and/or latency buffer in order to allow system  100  to catch-up to live streaming more quickly. Additionally, temporal scalable video coding (TSVC) may be used to drop frames of encoded video data in order to maintain a compliant bitstream in the event that network conditions deteriorate (e.g., throughput declines) or packet loss increases. In various examples, TSVC may be used to produce a compliant bitstream for the recipient device (e.g., remote computing device(s)  180 ) to avoid dropping the video stream from channel  204 . 
       FIG. 4  is a block diagram showing an example architecture  400  of a computing device, such as the system  100  and/or remote computing device(s)  180 , and/or other computing devices described herein. It will be appreciated that not all user devices will include all of the components of the architecture  400  and some user devices may include additional components not shown in the architecture  400 . The architecture  400  may include one or more processing elements  404  for executing instructions and retrieving data stored in a storage element  402 . The processing element  404  may comprise at least one processor. Any suitable processor or processors may be used. For example, the processing element  404  may comprise one or more digital signal processors (DSPs). In some examples, the processing element  404  may be effective to perform object segmentation techniques for image data, as described above. The storage element  402  can include one or more different types of memory, data storage, or computer-readable storage media devoted to different purposes within the architecture  400 . For example, the storage element  402  may comprise flash memory, random-access memory, disk-based storage, etc. Different portions of the storage element  402 , for example, may be used for program instructions for execution by the processing element  404 , storage of images or other digital works, and/or a removable storage for transferring data to other devices, etc. 
     The storage element  402  may also store software for execution by the processing element  404 . An operating system  422  may provide the user with an interface for operating the user device and may facilitate communications and commands between applications executing on the architecture  400  and various hardware thereof. A transfer application  424  may be configured to send and/or receive image and/or video data to and/or from other devices (e.g., a mobile device, remote device, image capture device, and/or display device). In some examples, the transfer application  424  may also be configured to upload the received images to another device that may perform processing as described herein (e.g., a mobile device or another computing device). 
     In various examples, catch-up pacing engine  485  may be effective to control the frame rate of image sensor  432  (e.g., camera  101 ) in order to perform the various catch-up pacing techniques described above. Additionally, in various examples, catch-up pacing engine  485  may receive indications of current network conditions (e.g., from network monitor  202 ) and may adjust the multiplier of pacer buffer  302 . Additionally, in some examples, catch-up pacing engine  485  may receive an indication of current network conditions and may encode video data so as to retain a percentage of available bandwidth for transmission of the retrospect buffer and/or latency buffer, as described above. 
     When implemented in some user devices, the architecture  400  may also comprise a display component  406 . The display component  406  may comprise one or more light-emitting diodes (LEDs) or other suitable display lamps. Also, in some examples, the display component  406  may comprise, for example, one or more devices such as cathode ray tubes (CRTs), liquid-crystal display (LCD) screens, gas plasma-based flat panel displays, LCD projectors, raster projectors, infrared projectors or other types of display devices, etc. 
     The architecture  400  may also include one or more input devices  408  operable to receive inputs from a user. The input devices  408  can include, for example, a push button, touch pad, touch screen, wheel, joystick, keyboard, mouse, trackball, keypad, light gun, game controller, or any other such device or element whereby a user can provide inputs to the architecture  400 . These input devices  408  may be incorporated into the architecture  400  or operably coupled to the architecture  400  via wired or wireless interface. In some examples, architecture  400  may include a microphone  470  for capturing sounds, such as voice commands. Voice recognition engine  480  may interpret audio signals of sound captured by microphone  470 . In some examples, voice recognition engine  480  may listen for a “wake word” to be received by microphone  470 . Upon receipt of the wake word, voice recognition engine  480  may stream audio to a voice recognition server for analysis. In various examples, voice recognition engine  480  may stream audio to external computing devices via communication interface  412 . 
     When the display component  406  includes a touch-sensitive display, the input devices  408  can include a touch sensor that operates in conjunction with the display component  406  to permit users to interact with the image displayed by the display component  406  using touch inputs (e.g., with a finger or stylus). The architecture  400  may also include a power supply  414 , such as a wired alternating current (AC) converter, a rechargeable battery operable to be recharged through conventional plug-in approaches, or through other approaches such as capacitive or inductive charging. 
     The communication interface  412  may comprise one or more wired or wireless components operable to communicate with one or more other user devices. For example, the communication interface  412  may comprise a wireless communication module  436  configured to communicate on a network, such as the network  104 , according to any suitable wireless protocol, such as IEEE 802.11 or another suitable wireless local area network (WLAN) protocol. A short range interface  434  may be configured to communicate using one or more short range wireless protocols such as, for example, near field communications (NFC), Bluetooth, Bluetooth LE, etc. A mobile interface  440  may be configured to communicate utilizing a cellular or other mobile protocol. A Global Positioning System (GPS) interface  438  may be in communication with one or more earth-orbiting satellites or other suitable position-determining systems to identify a position of the architecture  400 . A wired communication module  442  may be configured to communicate according to the USB protocol or any other suitable protocol. 
     The architecture  400  may also include one or more sensors  430  such as, for example, one or more position sensors, image sensors, and/or motion sensors (e.g., camera  101  depicted in  FIG. 1 ). An image sensor  432  is shown in  FIG. 4 . Some examples of the architecture  400  may include multiple image sensors  432 . For example, a panoramic camera system may comprise multiple image sensors  432  resulting in multiple images and/or video frames that may be stitched and may be blended to form a seamless panoramic output. 
     Motion sensors may include any sensors that sense motion of the architecture including, for example, gyro sensors  444  and accelerometers  446 . Motion sensors, in some examples, may be used to determine an orientation, such as a pitch angle and/or a roll angle of a camera. The gyro sensor  444  may be configured to generate a signal indicating rotational motion and/or changes in orientation of the architecture (e.g., a magnitude and/or direction of the motion or change in orientation). Any suitable gyro sensor may be used including, for example, ring laser gyros, fiber-optic gyros, fluid gyros, vibration gyros, etc. The accelerometer  446  may generate a signal indicating an acceleration (e.g., a magnitude and/or direction of acceleration). Any suitable accelerometer may be used including, for example, a piezoresistive accelerometer, a capacitive accelerometer, etc. In some examples, the GPS interface  438  may be utilized as a motion sensor. For example, changes in the position of the architecture  400 , as determined by the GPS interface  438 , may indicate the motion of the GPS interface  438 . 
     In some examples, architecture  400  may include a depth sensor  448 . Depth sensor  448  may be effective to determine a distance between image sensor  432  and a surface detected by depth sensor  448 . In some examples, the depth sensor  448  may determine the contours of the surface and may be capable of using computer vision techniques to recognize facial patterns or other markers within the field of view of the depth sensor  448 &#39;s infrared sensor. In some examples, the depth sensor  448  may include an infrared projector and camera. Processing element  404  may build a depth map based on detection by the infrared camera of a pattern of structured light displayed on a surface by the infrared projector. In some other examples, the depth sensor  448  may include a time of flight camera that may compute distance based on the speed of light by measuring the time of flight of a light signal between a camera of the depth sensor  448  and a surface of an environment. In some examples, processing element  404  may be effective to determine the location of various objects in the physical environment within the field of view of image sensor  432  based on the depth map created by the depth sensor  448 . As noted above, in some examples, non-infrared depth sensors, such as passive stereo camera pairs, or non-identical camera pairs, may be used in place of, or in addition to, infrared light sources of depth sensor  448 . 
       FIG. 5  is a flowchart  500  illustrating a first example process for performing catch-up pacing for video streaming that may be used in accordance with the present disclosure. In some examples, the process of  FIG. 5  may be performed by an indoor monitoring system (e.g., system  100 ) that sends video to one or more other computing devices (e.g., remote computing device(s)  180 ). In some examples, the requested video stream may be sent using a communications protocol that is commonly employed for adaptive bitrate streaming, such as hypertext transfer protocol (HTTP). 
     The process of  FIG. 5  may begin at operation  510 , “Capture first video data representing a physical environment.” At operation  510 , camera  101  may capture first video data representing a physical environment, such as scene  190  depicted in  FIG. 1 . In various examples, the first video data may be recorded at a relatively low frame rate (e.g., 15 frames-per-second, 10 frames-per-second, etc.). Additionally, in at least some examples, the first video data may be encoded using a relatively high quantization parameter, resulting in a reduced size of the compressed frames of the first video data. 
     The process of  FIG. 5  may continue from operation  510  to operation  520 , “Detect motion in the first video data.” At operation  520 , motion may be detected in the first video data. For example, various motion detection algorithms may detect changes (e.g., SAD, SSD, etc.) between sequential frames of image data of the first video data. The changes may be determined to exceed a threshold and may be deemed an indication of motion in the first video data. 
     The process of  FIG. 5  may continue from action  520  to action  530 , “Establish a communication channel with a remote computing device.” At action  530 , upon detection of motion of the first video data stored in the retrospect buffer, a communication channel may be established between the system  100  and remote computing device(s)  180 . 
     The process of  FIG. 5  may continue from action  530  to action  540 , “Capture second video data while the communication channel with the remote computing device is established.” In the example, second video data may be captured while the connection is being established with remote computing device(s)  180 . In some examples, the second video data may be recorded at a lower frame rate relative to a default streaming frame rate. In some further examples, the second video data may be recorded at a higher frame rate relative to the first video data, but at a frame rate that is still lower than a default frame rate for live streaming video from system  100  to remote computing device(s)  180 . 
     The process of  FIG. 5  may continue from action  540  to action  550 , “Determine an amount of available bandwidth of the communication channel, wherein the available bandwidth comprises a first bitrate.” At action  550  system  100  may determine an indication of available bandwidth and/or current network conditions on the communication channel established between system  100  and remote computing device(s)  180 . In various examples, network monitor  202  of system  100  may determine the current network conditions. In some examples, determining the current network conditions may comprise determining an available bandwidth comprising a bitrate at which data may be transmitted over the communication channel. The available amount of bandwidth may be determined using a remote estimated maximum bandwidth (REMB) message, based on historical conditions, based on acknowledgement time of sent data, etc. 
     The process of  FIG. 5  may continue from action  550  to action  560 , “Capture third video data.” At action  560  third video data may be captured by camera  101 . The third video data may be captured after the communication channel has been established between system  100  and remote computing device(s)  180 . In some examples, the third video data may be captured at the full default frame rate (e.g., 30 frames-per-second, 60 frames-per-second, etc.). 
     The process of  FIG. 5  may continue from action  560  to action  570 , “Encode the third video data at a second bitrate lower than the first bitrate.” At action  570 , the third video data may be encoded at a second bitrate lower than the first bitrate. In various examples, the third video data may be encoded at a bitrate that is lower than the available bandwidth so that the first video data stored in the retrospect buffer and the second video data stored in the latency buffer can be transmitted to the remote computing device(s)  180  to eliminate the lag in the live stream. 
     The process of  FIG. 5  may continue from action  570  to action  580 , “Send the first video data, the second video data, and the third video data to the remote computing device.” At action  580 , the first video data, the second video data and the third video data may be sent over the communication channel to the remote computing device(s)  180 . 
       FIG. 6  is a flowchart  600  illustrating a first example process for performing catch-up pacing for video streaming that may be used in accordance with the present disclosure. In some examples, the process of  FIG. 6  may be performed by an indoor monitoring system (e.g., system  100 ) that sends video to one or more other computing devices (e.g., remote computing device(s)  180 ). In some examples, the requested video stream may be sent using a communications protocol that is commonly employed for adaptive bitrate streaming, such as hypertext transfer protocol (HTTP). 
     The process of  FIG. 6  may begin at action  602 , “Record first video data at a first frame rate.” At action  602 , first video data may be recorded by camera  101  at a first frame rate. In some examples, the first frame rate may be relatively low (e.g., 15 frames-per-second, 20 frames-per-second, etc.) compared to a default frame rate for streaming video frame system  100 . 
     The process of  FIG. 6  may continue from action  602  to action  604 , “Store first video data in a retrospect buffer”. At action  604 , the first video data may be stored in a retrospect buffer of system  100 . In various examples, the retrospect buffer may be relatively small in terms of memory size. For example, the retrospect buffer may be sized so as to hold a small portion of video data (e.g., ˜60 frames of video data, ˜30 frames of video data, &lt;120 frames of video data, etc.). In some examples, the oldest frames of video data stored in the retrospect buffer may be replaced by newly captured frames of video data until motion is detected in the video data in the retrospect buffer at action  606 . If no motion is detected the camera may continue to capture the first video data at the first frame rate and may store the first video data in the retrospect buffer. 
     If, at action  606 , motion is detected in the first video data stored in the retrospect buffer, the process of  FIG. 6  may continue from action  606  to action  608 , “Record second video data at a second frame rate and store in latency buffer.” At action  608 , second video data may be recorded at a second frame rate higher than the first frame rate. In various examples, the second frame rate may be below a default video streaming frame rate for system  100 . For example, at action  608 , the frame rate of captured video data may be increased from 15 fps to 20 fps. The second video data recorded at the second frame rate may be stored in a latency buffer. 
     The process of  FIG. 6  may continue from action  608  to action  610 , “Establish connection with remote computing device.” At action  610 , system  100  may establish a communication channel with a remote computing device. For example, system  100  may establish communication channel  204  with remote computing device(s)  180 . 
     The process of  FIG. 6  may continue from action  610  to action  612 , “Send first video data in retrospect buffer and second video data to remote computing device.” At action  612 , first video data in the retrospect buffer and the second video data in the latency buffer may be sent to the remote computing device. In some examples, the first video data and the second video data may be sent out-of-band with respect to the rest of the video stream sent from system  100  to remote computing device(s)  180 . In other examples, at least one processor  102  of system  100  may encode the bitstream of the video sent to remote computing device(s)  180  with a bitrate that is less than the total channel capacity of the communication channel between system  100  and remote computing device(s)  180 . Accordingly, the unused channel capacity may be used to transmit the first video data from the retrospect buffer and the second video data from the latency buffer to eliminate lag in the live stream of video. In some further examples, a multiplier of a packet buffer such as a pacer buffer may be increased (if the current network conditions allow) in order to increase the rate at which packets are sent from system  100  to remote computing device(s)  180 . 
     The process of  FIG. 6  may continue from action  612  to action  614 , “Record third video data at a third frame rate higher than first frame rate and second frame rate.” At action  614 , system  100  may record third video data at a third frame that is higher than the first frame rate and the second frame rate. In some examples, the third frame rate may represent a default frame rate for video streamed between system  100  and remote computing device(s)  180 . 
     The process of  FIG. 6  may continue from action  614  to action  616 , “Send third video data to remote computing device.” At action  616 , the third video data may be streamed to the remote computing device. As previously described, in various examples, the third video data may be encoded at a bitrate that is less than the total available bandwidth of the communication channel in order to conserve available bandwidth for sending the contents of the retrospect buffer and/or latency buffer. 
     An example system for sending and providing data will now be described in detail. In particular,  FIG. 7  illustrates an example computing environment in which the embodiments described herein may be implemented.  FIG. 7  is a diagram schematically illustrating an example of a data center  85  that can provide computing resources to users  70   a  and  70   b  (which may be referred herein singularly as user  70  or in the plural as users  70 ) via user computers or other network-connected devices  72   a  and  72   b  (which may be referred herein singularly as computer  72  or in the plural as computers  72 ) via network  104 . In various examples, system  100  depicted in  FIG. 1  may be an example of a computer or other network-connected device  72   a  and/or  72   b . Data center  85  may be configured to provide computing resources for executing applications on a permanent or an as-needed basis. The computing resources provided by data center  85  may include various types of resources, such as gateway resources, load balancing resources, routing resources, networking resources, computing resources, volatile and non-volatile memory resources, content delivery resources, data processing resources, data storage resources, data communication resources and the like. Each type of computing resource may be available in a number of specific configurations. For example, data processing resources may be available as virtual machine instances that may be configured to provide various web services. In addition, combinations of resources may be made available via a network and may be configured as one or more web services. The instances may be configured to execute applications, including web services, such as application services, media services, database services, processing services, gateway services, storage services, routing services, security services, encryption services, load balancing services, application services and the like. 
     These services may be configurable with set or custom applications and may be configurable in size, execution, cost, latency, type, duration, accessibility and in any other dimension. These web services may be configured as available infrastructure for one or more clients and can include one or more applications configured as a platform or as software for one or more clients. These web services may be made available via one or more communications protocols. These communications protocols may include, for example, hypertext transfer protocol (HTTP) or non-HTTP protocols. These communications protocols may also include, for example, more reliable transport layer protocols, such as transmission control protocol (TCP), and less reliable transport layer protocols, such as user datagram protocol (UDP). Data storage resources may include file storage devices, block storage devices and the like. 
     Each type or configuration of computing resource may be available in different sizes, such as large resources—consisting of many processors, large amounts of memory, and/or large storage capacity—and small resources—consisting of fewer processors, smaller amounts of memory, and/or smaller storage capacity. Customers may choose to allocate a number of small processing resources as web servers and/or one large processing resource as a database server, for example. 
     Data center  85  may include servers  76   a  and  76   b  (which may be referred herein singularly as server  76  or in the plural as servers  76 ) that provide computing resources. These resources may be available as bare metal resources or as virtual machine instances  78   a - d  (which may be referred herein singularly as virtual machine instance  78  or in the plural as virtual machine instances  78 ). Virtual machine instances  78   c  and  78   d  may be rendition switching virtual machine (“RSVM”) instances. The RSVM virtual machine instances  78   c  and  78   d  may be configured to perform all, or any portion, of the techniques for rendition switching between different renditions of a video and/or any other of the disclosed techniques in accordance with the present disclosure and described in detail above. As should be appreciated, while the particular example illustrated in  FIG. 7  includes one RSVM virtual machine in each server, this is merely an example. A server may include more than one RSVM virtual machine or may not include any RSVM virtual machines. 
     The availability of virtualization technologies for computing hardware has afforded benefits for providing large scale computing resources for customers and allowing computing resources to be efficiently and securely shared between multiple customers. For example, virtualization technologies may allow a physical computing device to be shared among multiple users by providing each user with one or more virtual machine instances hosted by the physical computing device. A virtual machine instance may be a software emulation of a particular physical computing system that acts as a distinct logical computing system. Such a virtual machine instance provides isolation among multiple operating systems sharing a given physical computing resource. Furthermore, some virtualization technologies may provide virtual resources that span one or more physical resources, such as a single virtual machine instance with multiple virtual processors that span multiple distinct physical computing systems. 
     Referring to  FIG. 7 , network  104  may, for example, be a publicly accessible network of linked networks and possibly operated by various distinct parties, such as the Internet. In other embodiments, network  104  may be a private network, such as a corporate or university network that is wholly or partially inaccessible to non-privileged users. In still other embodiments, network  104  may include one or more private networks with access to and/or from the Internet. 
     Network  104  may provide access to computers  72 . User computers  72  may be computers utilized by users  70  or other customers of data center  85 . For instance, user computer  72   a  or  72   b  may be a server, a desktop or laptop personal computer, a tablet computer, a wireless telephone, a personal digital assistant (PDA), an e-book reader, a game console, a set-top box or any other computing device capable of accessing data center  85 . User computer  72   a  or  72   b  may connect directly to the Internet (e.g., via a cable modem or a Digital Subscriber Line (DSL)). Although only two user computers  72   a  and  72   b  are depicted, it should be appreciated that there may be multiple user computers. 
     User computers  72  may also be utilized to configure aspects of the computing resources provided by data center  85 . In this regard, data center  85  might provide a gateway or web interface through which aspects of its operation may be configured through the use of a web browser application program executing on user computer  72 . Alternately, a stand-alone application program executing on user computer  72  might access an application programming interface (API) exposed by data center  85  for performing the configuration operations. Other mechanisms for configuring the operation of various web services available at data center  85  might also be utilized. 
     Servers  76  shown in  FIG. 7  may be servers configured appropriately for providing the computing resources described above and may provide computing resources for executing one or more web services and/or applications. In one embodiment, the computing resources may be virtual machine instances  78 . In the example of virtual machine instances, each of the servers  76  may be configured to execute an instance manager  80   a  or  80   b  (which may be referred herein singularly as instance manager  80  or in the plural as instance managers  80 ) capable of executing the virtual machine instances  78 . The instance managers  80  may be a virtual machine monitor (VMM) or another type of program configured to enable the execution of virtual machine instances  78  on server  76 , for example. As discussed above, each of the virtual machine instances  78  may be configured to execute all or a portion of an application. 
     It should be appreciated that although the embodiments disclosed above discuss the context of virtual machine instances, other types of implementations can be utilized with the concepts and technologies disclosed herein. For example, the embodiments disclosed herein might also be utilized with computing systems that do not utilize virtual machine instances. 
     In the example data center  85  shown in  FIG. 7 , a router  71  may be utilized to interconnect the servers  76   a  and  76   b . Router  71  may also be connected to gateway  74 , which is connected to network  104 . Router  71  may be connected to one or more load balancers, and alone or in combination may manage communications within networks in data center  85 , for example, by forwarding packets or other data communications as appropriate based on characteristics of such communications (e.g., header information including source and/or destination addresses, protocol identifiers, size, processing requirements, etc.) and/or the characteristics of the private network (e.g., routes based on network topology, etc.). It will be appreciated that, for the sake of simplicity, various aspects of the computing systems and other devices of this example are illustrated without showing certain conventional details. Additional computing systems and other devices may be interconnected in other embodiments and may be interconnected in different ways. 
     In the example data center  85  shown in  FIG. 7 , a server manager  75  is also employed to at least in part direct various communications to, from and/or between servers  76   a  and  76   b . While  FIG. 7  depicts router  71  positioned between gateway  74  and server manager  75 , this is merely an exemplary configuration. In some cases, for example, server manager  75  may be positioned between gateway  74  and router  71 . Server manager  75  may, in some cases, examine portions of incoming communications from user computers  72  to determine one or more appropriate servers  76  to receive and/or process the incoming communications. Server manager  75  may determine appropriate servers to receive and/or process the incoming communications based on factors such as an identity, location or other attributes associated with user computers  72 , a nature of a task with which the communications are associated, a priority of a task with which the communications are associated, a duration of a task with which the communications are associated, a size and/or estimated resource usage of a task with which the communications are associated and many other factors. Server manager  75  may, for example, collect or otherwise have access to state information and other information associated with various tasks in order to, for example, assist in managing communications and other operations associated with such tasks. 
     It should be appreciated that the network topology illustrated in  FIG. 7  has been greatly simplified and that many more networks and networking devices may be utilized to interconnect the various computing systems disclosed herein. These network topologies and devices should be apparent to those skilled in the art. 
     It should also be appreciated that data center  85  described in  FIG. 7  is merely illustrative and that other implementations might be utilized. It should also be appreciated that a server, gateway or other computing device may comprise any combination of hardware or software that can interact and perform the described types of functionality, including without limitation: desktop or other computers, database servers, network storage devices and other network devices, PDAs, tablets, cellphones, wireless phones, pagers, electronic organizers, Internet appliances, television-based systems (e.g., using set top boxes and/or personal/digital video recorders) and various other consumer products that include appropriate communication capabilities. 
     A network set up by an entity, such as a company or a public sector organization, to provide one or more web services (such as various types of cloud-based computing or storage) accessible via the Internet and/or other networks to a distributed set of clients may be termed a provider network. Such a provider network may include numerous data centers hosting various resource pools, such as collections of physical and/or virtualized computer servers, storage devices, networking equipment and the like, needed to implement and distribute the infrastructure and web services offered by the provider network. The resources may in some embodiments be offered to clients in various units related to the web service, such as an amount of storage capacity for storage, processing capability for processing, as instances, as sets of related services and the like. A virtual computing instance may, for example, comprise one or more servers with a specified computational capacity (which may be specified by indicating the type and number of CPUs, the main memory size and so on) and a specified software stack (e.g., a particular version of an operating system, which may in turn run on top of a hypervisor). 
     A number of different types of computing devices may be used singly or in combination to implement the resources of the provider network in different embodiments, for example computer servers, storage devices, network devices and the like. In some embodiments a client or user may be provided direct access to a resource instance, e.g., by giving a user an administrator login and password. In other embodiments the provider network operator may allow clients to specify execution requirements for specified client applications and schedule execution of the applications on behalf of the client on execution platforms (such as application server instances, Java™ virtual machines (JVMs), general-purpose or special-purpose operating systems, platforms that support various interpreted or compiled programming languages such as Ruby, Perl, Python, C, C++ and the like or high-performance computing platforms) suitable for the applications, without, for example, requiring the client to access an instance or an execution platform directly. A given execution platform may utilize one or more resource instances in some implementations; in other implementations, multiple execution platforms may be mapped to a single resource instance. 
     In many environments, operators of provider networks that implement different types of virtualized computing, storage and/or other network-accessible functionality may allow customers to reserve or purchase access to resources in various resource acquisition modes. The computing resource provider may provide facilities for customers to select and launch the desired computing resources, deploy application components to the computing resources and maintain an application executing in the environment. In addition, the computing resource provider may provide further facilities for the customer to quickly and easily scale up or scale down the numbers and types of resources allocated to the application, either manually or through automatic scaling, as demand for or capacity requirements of the application change. The computing resources provided by the computing resource provider may be made available in discrete units, which may be referred to as instances. An instance may represent a physical server hardware platform, a virtual machine instance executing on a server or some combination of the two. Various types and configurations of instances may be made available, including different sizes of resources executing different operating systems (OS) and/or hypervisors, and with various installed software applications, runtimes and the like. Instances may further be available in specific availability zones, representing a logical region, a fault tolerant region, a data center or other geographic location of the underlying computing hardware, for example. Instances may be copied within an availability zone or across availability zones to improve the redundancy of the instance, and instances may be migrated within a particular availability zone or across availability zones. As one example, the latency for client communications with a particular server in an availability zone may be less than the latency for client communications with a different server. As such, an instance may be migrated from the higher latency server to the lower latency server to improve the overall client experience. 
     In some embodiments the provider network may be organized into a plurality of geographical regions, and each region may include one or more availability zones. An availability zone (which may also be referred to as an availability container) in turn may comprise one or more distinct locations or data centers, configured in such a way that the resources in a given availability zone may be isolated or insulated from failures in other availability zones. That is, a failure in one availability zone may not be expected to result in a failure in any other availability zone. Thus, the availability profile of a resource instance is intended to be independent of the availability profile of a resource instance in a different availability zone. Clients may be able to protect their applications from failures at a single location by launching multiple application instances in respective availability zones. At the same time, in some implementations inexpensive and low latency network connectivity may be provided between resource instances that reside within the same geographical region (and network transmissions between resources of the same availability zone may be even faster). 
     As set forth above, content may be provided by a content provider to one or more clients. The term content, as used herein, refers to any presentable information, and the term content item, as used herein, refers to any collection of any such presentable information. A content provider may, for example, provide one or more content providing services for providing content to clients. The content providing services may reside on one or more servers. The content providing services may be scalable to meet the demands of one or more customers and may increase or decrease in capability based on the number and type of incoming client requests. Portions of content providing services may also be migrated to be placed in positions of lower latency with requesting clients. For example, the content provider may determine an “edge” of a system or network associated with content providing services that is physically and/or logically closest to a particular client. The content provider may then, for example, “spin-up,” migrate resources or otherwise employ components associated with the determined edge for interacting with the particular client. Such an edge determination process may, in some cases, provide an efficient technique for identifying and employing components that are well suited to interact with a particular client, and may, in some embodiments, reduce the latency for communications between a content provider and one or more clients. 
     In addition, certain methods or process blocks may be omitted in some implementations. The methods and processes described herein are also not limited to any particular sequence, and the blocks or states relating thereto can be performed in other sequences that are appropriate. For example, described blocks or states may be performed in an order other than that specifically disclosed, or multiple blocks or states may be combined in a single block or state. The example blocks or states may be performed in serial, in parallel, or in some other manner. Blocks or states may be added to or removed from the disclosed example embodiments. 
     It will also be appreciated that various items are illustrated as being stored in memory or on storage while being used, and that these items or portions thereof may be transferred between memory and other storage devices for purposes of memory management and data integrity. Alternatively, in other embodiments some or all of the software modules and/or systems may execute in memory on another device and communicate with the illustrated computing systems via inter-computer communication. Furthermore, in some embodiments, some or all of the systems and/or modules may be implemented or provided in other ways, such as at least partially in firmware and/or hardware, including, but not limited to, one or more application-specific integrated circuits (ASICs), standard integrated circuits, controllers (e.g., by executing appropriate instructions, and including microcontrollers and/or embedded controllers), field-programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), etc. Some or all of the modules, systems and data structures may also be stored (e.g., as software instructions or structured data) on a computer-readable medium, such as a hard disk, a memory, a network or a portable media article to be read by an appropriate drive or via an appropriate connection. The systems, modules and data structures may also be sent as generated data signals (e.g., as part of a carrier wave or other analog or digital propagated signal) on a variety of computer-readable transmission media, including wireless-based and wired/cable-based media, and may take a variety of forms (e.g., as part of a single or multiplexed analog signal, or as multiple discrete digital packets or frames). Such computer program products may also take other forms in other embodiments. Accordingly, the present invention may be practiced with other computer system configurations. 
     Although the flowcharts and methods described herein may describe a specific order of execution, it is understood that the order of execution may differ from that which is described. For example, the order of execution of two or more blocks or steps may be scrambled relative to the order described. Also, two or more blocks or steps may be executed concurrently or with partial concurrence. Further, in some embodiments, one or more of the blocks or steps may be skipped or omitted. It is understood that all such variations are within the scope of the present disclosure. 
     It should be emphasized that the above-described embodiments of the present disclosure are merely possible examples of implementations set forth for a clear understanding of the principles of the disclosure. Many variations and modifications may be made to the above-described embodiment(s) without departing substantially from the spirit and principles of the disclosure. The various features and processes described above may be used independently of one another, or may be combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of this disclosure. 
     In addition, conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. 
     Although this disclosure has been described in terms of certain example embodiments and applications, other embodiments and applications that are apparent to those of ordinary skill in the art, including embodiments and applications that do not provide all of the benefits described herein, are also within the scope of this disclosure. The scope of the inventions is defined only by the claims, which are intended to be construed without reference to any definitions that may be explicitly or implicitly included in any incorporated-by-reference materials.