Patent Publication Number: US-2018035305-A1

Title: Distributed Channel Sampling Across a Mesh Network

Description:
RELATED APPLICATION 
     This application is a continuation of and claims priority to U.S. patent application Ser. No. 15/157,149 filed May 17, 2016 entitled “Distributed Channel Sampling Across a Mesh Network”, the disclosure of which is incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Wireless mesh networking used to connect devices to each other, and to cloud-based services, is increasingly popular for sensing environmental conditions, controlling equipment, and providing information and alerts to users. These wireless mesh networks may share radio spectrum with other wireless radio systems, and operate in radio bands under unlicensed or license-free regulatory regimes. For example wireless local area network (WLAN) technologies, such as Wi-Fi, share radio spectrum with wireless personal area network (WPAN) technologies, such as IEEE 802.15.4. The various radio systems that share spectrum are designed to accept interference from each other, as specified in the various regulatory regimes. Some wireless systems and standards are designed to evaluate noise, energy, and/or interference in radio channels, in order to determine the best frequency or frequencies on which to start a mesh network. However a mesh network device, such as a ZigBee coordinator, may only scan radio channels when starting a network, and is only able to measure energy within the operating range of its receiver. However a mesh network may cover a much larger area than the coordinator can evaluate by itself, and other radio signals may appear and disappear in the operating area of the mesh network over time that were not be present when the coordinator started the network. 
     SUMMARY 
     This summary is provided to introduce simplified concepts of distributed channel sampling across a mesh network. The simplified concepts are further described below in the Detailed Description. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter. 
     Distributed channel sampling across a mesh network is described, as generally related to evaluating energy in radio channels across a mesh network. In embodiments, a commissioning device can propagate a scanning request, which includes a number of scanning parameters, to nodes in a mesh network, causing the nodes to perform energy detection scans using the scanning parameters. The commissioning device receives energy measurements in scanning reports from the nodes and analyzes the measurements to determine an operating channel for the mesh network. The commissioning device updates the operating channel in network configuration information that is sent to a leader device in the mesh network, for propagation to the mesh network. 
     In aspects of distributed channel sampling across a mesh network, a mesh networking device receives a scanning request, which includes a number of scanning parameters. The mesh networking device performs an energy detection scan according to the received scanning parameters and transmits a scanning report that includes the energy measurements made during the energy detection scan. In other aspects, mesh network nodes can perform channel scans and a commissioning device propagates a scanning request, which includes a number of scanning parameters, to the mesh network nodes, causing the mesh network nodes to perform energy detection scans using the scanning parameters. The commissioning device receives energy measurements in scanning reports from the mesh network nodes and analyzes the measurements to determine an operating channel for the mesh network. The commissioning device updates the operating channel in network configuration information that is sent to a leader device in the mesh network, for propagation to the mesh network nodes. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments of distributed channel sampling across a mesh network are described with reference to the following drawings. The same numbers are used throughout the drawings to reference like features and components: 
         FIG. 1  illustrates an example mesh network system in which various embodiments of the distributed channel sampling across a mesh network can be implemented. 
         FIG. 2  illustrates an example environment in which various embodiments of the distributed channel sampling across a mesh network can be implemented. 
         FIG. 3  illustrates various radio propagation characteristics that affect scanning and selection of radio channels for a mesh network. 
         FIG. 4  illustrates an example embodiment in accordance with embodiments of the distributed channel sampling across a mesh network. 
         FIG. 5  illustrates an example method of distributed channel sampling across a mesh network as generally related to evaluating energy in radio channels across the mesh network in accordance with embodiments of the techniques described herein. 
         FIG. 6  illustrates another example method of distributed channel sampling across a mesh network as generally related to evaluating energy in radio channels across the mesh network in accordance with embodiments of the techniques described herein. 
         FIG. 7  illustrates an example environment in which a mesh network can be implemented in accordance with embodiments of the techniques described herein. 
         FIG. 8  illustrates an example mesh network device that can be implemented in a mesh network environment in accordance with one or more embodiments of the techniques described herein. 
         FIG. 9  illustrates an example system with an example device that can implement embodiments of distributed channel sampling across a mesh network. 
     
    
    
     DETAILED DESCRIPTION 
     While features and concepts of the described systems and methods for the distributed channel sampling across a mesh network can be implemented in any number of different environments, systems, devices, and/or various configurations, embodiments of the distributed channel sampling across a mesh network are described in the context of the following example devices, systems, and configurations. Further, although examples of distributed channel sampling across a mesh network are described with respect to IEEE 802.15.4, the techniques described herein apply equally to any radio system and/or wireless network. 
     Mesh networks are often implemented using Wireless Personal Area Network (WPAN) technologies, such as IEEE 802.15.4, that operate using radio spectrum shared by other WPANs, as well as other radio systems. When a new WPAN is formed by a device implemented as a coordinator of the network, the coordinator performs an energy detection scan of the available radio channels to determine a channel on which to start the WPAN. The energy detection scan measures the amount of energy detected on each radio channel and the coordinator chooses a radio channel for the WPAN. Typically, the coordinator chooses the channel with the lowest detected energy from the energy detection scan. All the nodes in the mesh network then communicate on the channel selected by the coordinator. 
     One advantage of mesh networks is that a mesh network can use low power radios in multiple mesh network nodes to cover an area larger than the area covered by a single radio link, by routing messages through multiple nodes between a source node and a destination node. However, when a WPAN coordinator performs an energy detection scan, the energy that is detected is limited by the sensitivity of the radio in the coordinator. The energy detection scan provides the coordinator information about its immediate environment, but not about the entire area the mesh network covers. There may be mesh network nodes that are exposed to different radio conditions than the coordinator experiences during or after the energy detection scan. For example, a mesh network node may be several hops away from the coordinator and adjacent to a Wi-Fi access point in a home. If the coordinator chooses a channel that overlaps, or is adjacent to, the radio spectrum used by the Wi-Fi access point, the mesh network nodes close to the Wi-Fi access point may experience channel impairments, such as receiver desensitization, packet loss, excessive retries, and so forth. 
     Distributed channel sampling across a mesh network provides a flexible framework for a network coordinator configuring nodes in a mesh network to assess the quality of available radio channels for the mesh network, across the entire coverage area of the mesh network. Each mesh network node receives a scan request message that includes scanning parameters. The scanning parameters include a channel mask that indicates which channels to scan, and parameters indicating how many times, how long, and/or when to scan the channels indicated in the channel mask. By configuring multiple nodes in the mesh network to perform channel scans, a better, global selection of a channel for the mesh network can be made than by simply basing the channel selection on localized conditions at the coordinator. 
     Additionally, a commissioning device can send the scan request to the mesh network nodes using efficient multicast and/or broadcast communications in the mesh network. The mesh network nodes can respond with scanning reports when the scans are completed according to the scanning parameters. By using efficient distribution techniques, network overhead for channel scanning is reduced over individual command and response requests to individual nodes, to perform on-demand channel scans. 
     Further, the commissioning device can configure nodes in the mesh network for periodic scanning over time to assess changing conditions that affect the mesh network over time. The one-time energy detection scan by a coordinator, when a mesh network is formed, is only reflective of radio conditions at a single instant in time. Parameters distributed to the mesh network nodes can schedule periodic scanning of the radio channels to assess on-going radio conditions across the mesh network. This periodic scanning enables the mesh network to adjust its operating channel and/or frequency band to maintain optimal radio conditions over the life of the mesh network. 
     Distributed channel sampling across a mesh network can also reduce the complexity of managing radio configurations for a user by forwarding the results of channel scans from the commissioning device to a cloud service that analyses the scanning reports and recommends configuration changes to the user who manages the mesh network. The cloud service can provide network configuration changes, as well as scanning parameter changes to optimize the distributed channel sampling. The cloud service can provide configuration information directly to the user via the user&#39;s commissioning device and/or directly to mesh network nodes to configure the mesh network. 
       FIG. 1  illustrates an example mesh network system  100  in which various embodiments of the distributed channel sampling across a mesh network can be implemented. The mesh network  100  is a wireless mesh network that includes routers  102 , a router-eligible end device  104 , and end devices  106 . The routers  102 , the router-eligible end device  104 , and the end devices  106 , each include a mesh network interface for communication over the mesh network. The routers  102  receive and transmit packet data over the mesh network interface. The routers  102  also route traffic across the mesh network  100 . The routers  102  and the router-eligible end devices  104  can assume various roles, and combinations of roles, within the mesh network  100 , as discussed below. 
     The router-eligible end devices  104  are located at leaf nodes of the mesh network topology and are not actively routing traffic to other nodes in the mesh network  100 . The router-eligible device  104  is capable of becoming a router  102  when the router-eligible device  104  is connected to additional devices. The end devices  106  are devices that can communicate using the mesh network  100 , but lack the capability, beyond simply forwarding to its parent router  102 , to route traffic in the mesh network  100 . For example, a battery-powered sensor is one type of end device  106 . 
     The routers  102 , the router-eligible end device  104 , and the end devices  106  include network credentials that are used to authenticate the identity of these devices as being a member of the mesh network  100 . The routers  102 , the router-eligible end device  104 , and the end devices  106  also use the network credentials to encrypt communications in the mesh network. 
       FIG. 2  illustrates an example environment  200  in which various embodiments of the distributed channel sampling across a mesh network can be implemented. The environment  200  includes the mesh network  100 , in which some routers  102  are performing specific roles in the mesh network  100 . The devices within the mesh network  100 , as illustrated by the dashed line, are communicating securely over the mesh network  100 , using the network credentials. 
     A border router  202  (also known as a gateway and/or an edge router) is one of the routers  102 . The border router  202  includes a second interface for communication with an external network, outside the mesh network  100 . The border router  202  connects to an access point  204  over the external network. For example, the access point  204  may be an Ethernet router, a Wi-Fi access point, or any other suitable device for bridging different types of networks. The access point  204  connects to a communication network  206 , such as the Internet. A cloud service  208 , which is connected via the communication network  206 , provides services related to and/or using the devices within the mesh network  100 . By way of example, and not limitation, the cloud service  208  provides applications that include connecting end user devices, such as smart phones, tablets, and the like, to devices in the mesh network  100 , processing and presenting data acquired in the mesh network  100  to end users, linking devices in one or more mesh networks  100  to user accounts of the cloud service  208 , provisioning and updating devices in the mesh network  100 , and so forth. 
     A user choosing to commission and/or configure devices in the mesh network  100  uses a commissioning device  210 , which connects to the border router  202  via the external network technology of the access point  204 , to commission and/or configure the devices. The commissioning device  210  may be any computing device, such as a smart phone, tablet, notebook computer, and so forth, with a suitable user interface and communication capabilities to execute applications that control devices to the mesh network  100 . Only a single commissioning device  210  may be active (i.e., an active commissioner) on the mesh network  100  at time. The commissioning of mesh network devices is described in U.S. patent application Ser. No. 14/749,616 entitled “Mesh Network Commissioning” filed Jun. 24, 2015, the disclosure of which is incorporated by reference herein in its entirety. 
     One of the routers  102  performs the role of a leader  216  for the mesh network  100 . The leader  216  manages router identifier assignment and the leader  216  is the central arbiter of network configuration information for the mesh network  100 . The leader  216  propagates the network configuration information to the other devices in the mesh network  100 . The leader  216  also controls which commissioning device is accepted as a sole, active commissioner for the mesh network  100 , at any given time. 
       FIG. 3  illustrates various radio propagation characteristics that affect the mesh network  100  in general, and the scanning and selection of radio channels for the mesh network  100 , in particular. Generally, the environment  300  includes the mesh network  100  implemented as part of a smart-home or other type of structure with any number of mesh network devices that are configured for communication in a mesh network. For example, the mesh network devices can include a thermostat  302 , hazard detectors  304  (e.g., for smoke and/or carbon monoxide), cameras  306   a - 306   c  (e.g., indoor and outdoor), lighting units  308   a - 308   d  (e.g., indoor and outdoor), and any other types of mesh network devices that are implemented inside and/or outside of a structure  310  (e.g., in a smart-home environment). In this example, the mesh network devices can also include any of the previously described devices, such as the border router  202 , the commissioning device  210 , and leader device  216 , as well as any of the devices implemented as a router  102 , and/or an end device  106 . 
     When the mesh network  100  was established, the leader device  216  may have acted as an IEEE 802.15.4 coordinator and performed an energy detection scan to choose an operating channel for the mesh network  100 . Over time, a user may add more mesh network devices to automate a number of new functions within the structure  310 . Each of the various devices inside and outside the structure  310  will experience different radio frequency (RF) environmental characteristics based on the location of the device, other devices located around the device, and/or characteristics of the structure  310 . Some of the RF characteristics that affect the RF environment may be relatively static, such as the attenuation of RF signals by walls in the structure  310 . Other RF characteristics may vary over time due to the intermittent operation of radio devices in and around the structure  310 , fast or slow fading of RF signals, the addition, and/or relocation of mesh network or other radio devices within the structure  310 , and other sources of RF energy. For example, non-communication sources of RF energy, such as arc welding or industrial use of an Industrial, Scientific, and Medical (ISM) device, produce RF energy in the frequency bands used by WPANs and other unlicensed devices. 
     By way of example, the leader device  216  is located inside the structure  310  and is several rooms away from the access point  204 . An energy detection scan performed by the leader device  216  may show some energy on channels that are occupied by Wi-Fi signals from the access point  204 , but the energy detection scan results may also show a low enough energy level that the leader device  216  might choose to operate on a channel within, or near, the occupied bandwidth of the Wi-Fi signals. By way of contrast, the thermostat  302  is located on a wall just above a table, where the access point  204  is located. The camera  306   b  is also in the same room as the access point  204 . Energy detection scans performed by the thermostat  302  and camera  306   b  will show significantly higher energy levels in mesh network channels within the occupied bandwidth of the Wi-Fi signal from the access point  204 . Using the energy measurements from the thermostat  302  and camera  306   b  may lead to a different choice of a channel for the mesh network  100 . 
     In another example, the location of a mesh network device inside or outside the structure  310  affects the RF environmental characteristics experienced by those devices. As discussed above, the camera  306   b  will show high energy levels in mesh network channels within the occupied bandwidth of the Wi-Fi signal from the access point  204 . By way of contrast, the signals in an energy detection scan performed by camera  306   a  will be lower due to path loss attenuation as the Wi-Fi signal from the access point  204  travels through the building materials (sheathing, siding, sheetrock, etc.) that make up the exterior wall of the structure  310 . 
     In another example, elevation affects the RF environmental characteristics experienced by the devices outside the structure  310 . The lighting unit  308   a  is located high on the exterior of the structure  310  and is exposed to more RF signals and/or RF signals at a higher level than the camera  306   a , which is mounted lower on the exterior, and may benefit from shielding and signal attenuation provided by adjacent structures and vegetation. The lighting unit  308   a  may also measure higher energy detection scan energy levels on some channels, than devices inside the structure  310 . Selecting a channel based solely on energy detection scans of a device inside the structure  310  may result in the selection of a radio channel that may not be optimal or usable for the lighting unit  308   a.    
     In another example, the use of wireless devices within a portion of the structure  310  may affect energy detection scans only in that portion of the structure  310  or only during periods of time when the wireless devices are in use. A user may be streaming movies from a wireless device  312  to a connected television  314 . This activity may affect the energy levels of channels in a portion of the structure during the activity, such as at lighting unit  308   c . If an energy detection scan is performed when the user is away at work or school, and the wireless device  312  and the television  314  are not is use, the energy that would be detected during the energy detection scan would be lower. By way of contrast, if the energy detection scan is performed when the user is home, and the wireless device  312  and the television  314  are in use, the detected energy would be higher on the channels that share the spectrum used for streaming. This energy detection scan may indicate that some mesh network channels, which appeared usable when the wireless device  312  and the television  314  were not is use, are not always usable for the mesh network  100 . 
     These examples are not meant to be a compressive list of the RF environmental conditions that are addressed by distributed channel sampling across a mesh network and should not be taken as a limitation of the claimed invention. There are many other examples of effects that affect RF propagation, such as slow fading, fast fading, varying atmospheric conditions, intermodulation interference, and so forth. 
     To communicate available channels and identify an individual channel, a channel page identifier (e.g., a Channel Type-Length-Value (TLV)) encodes an identifier of a channel page and an identifier of a channel, for propagation within the mesh network  100 . For example, IEEE 802.15.4 defines a number of channel pages that include channel numbers. IEEE 802.15.4 channel page zero includes twenty seven channels, sixteen channels that are available in the 2450 MHz band, ten channels that are available in the 915 MHz band, and one channel that is available in the 868 MHz band. Channel page zero defines the channels, as follows: 
         F   c =868.3 in megahertz, for  k= 0 
         F   c =906+2( k− 1) in megahertz, for  k= 1,2, . . . ,10, and 
         F   c =2405+5( k− 11) in megahertz, for  k= 11,12, . . . ,26, 
     where F c  is the center frequency of a channel and k is the channel number. 
     In any given mesh network  100 , devices may only support operation in a single frequency band or may be configurable to operate in multiple frequency bands. When scanning to select an operating channel for the mesh network  100 , it may be desirable to identify the frequency bands each mesh network device supports. For example, each mesh network device includes a channel pages identifier (e.g., a Channel Pages TLV) that can be read to identify the set of channel page identifiers supported by the mesh network device. Identifying the available channel pages restricts scanning to only available channels within a band, or enables scanning across frequency bands outside the current operating frequency band to determine if communication conditions are better in another frequency band. 
     With the available channels known, energy detection scans may be configured for any number of the available channels in any of the available channel pages with a channel mask. For example, the channel mask (e.g., a Channel Mask TLV) includes channel mask entries that specify a channel page, a mask length, and a channel mask, for the channels that are to be scanned. The channel mask is a variable length bit mask that indicates the channels within the channel page that are selected for energy detection scans. 
     While a single energy detection scan can be requested each time that an energy detection scan is desired, a user may not have a commissioning device connected to the network constantly to request multiple energy detection scans over a period of time. Also, requesting every energy detection scan separately generates mesh network traffic that reduces the throughput of the mesh network  100  for other traffic and may reduce battery life for battery-powered mesh network devices. 
     A scan request message (e.g., a MGMT_ED_SCAN.ntf message) may be used to request that mesh network devices measure and report energy measurements on one or more channels. The scan request message includes the channel mask to specify channels for energy detection scans. The mesh network device receiving the scan request message performs energy detection scans on the specified channels. 
     The scan request message can include additional parameters to specify how to perform the energy detection scans. As an example, and not a limitation, the additional parameters include a scan count (e.g., a Count TLV), a delay period (e.g., a Period TLV), and/or a scan duration (e.g., a Scan Duration TLV). The scan count indicates the number of the energy detection scans to perform for each selected channel in the channel mask. The delay period indicates an amount of time to delay before beginning energy detection scans and/or to delay between successive energy detection scans. The scan duration identifies an amount of time over which to measure the energy on each channel in the energy detection scan. 
     In embodiments, other parameters in the scan request message are contemplated, such as parameters that indicate whether energy detection scans should be coordinated between mesh network devices or be uncoordinated, if energy detection scans should be triggered from an event, such as a router advertisement message or a localization beacon message, and/or that configure reporting options, such as reporting energy detection scan results to provide an initial scan result before all scans are complete, to report scan results immediately if an energy detection scan results in an interesting event (e.g., an unusually high energy on the channel currently used by the mesh network  100 ), and so forth. 
     For example, when servicing the scan request message, a mesh network device performs IEEE 802.15.4 energy detection scans using a single channel at a time. The number of the energy detection scans indicated in the scan count specifies the number of energy detection scan rounds. Each energy detection scan round consists of performing one energy detection scan for each channel, separated by the delay period. 
     In an embodiment, the scan request message is received from the commissioning device  210 , when the commissioning device  210  is the active commissioner on the mesh network. If the mesh network device determines that, while performing energy detection scans to service the scan request message, the commissioner is no longer active on the network, which is indicated in the commissioner dataset, the mesh network device may stop servicing the scan request message. 
     The mesh network device reports the results of its energy detection (ED) scan in a scan report message (e.g., a MGMT_ED_REPORT.ntf message). The scan report message is unicast to the source of the scan request message that triggered the scan. Alternatively, the scan request message may include a destination address for the scan report message. For example, the scan report messages may be sent to a cloud-based service instead of the commissioning device  210  that sent the scan request message. 
     The scan report message includes the channel mask and an energy list (e.g., an Energy List TLV). The channel mask indicates the channels that have energy measurements reported in the energy list. The energy list includes a list of energy measurement values corresponding to the channels selected in the channel mask. With N selected channels in the channel mask, the first N entries in the energy list represent the first energy measurement values for the N channels from the first energy detection scan. The next N entries in the energy list represent the second energy measurement values for the N channels from the second energy detection scan, and so forth. 
     In embodiments, the scan report message may include metadata that is useful in interpreting the energy measurements. For example, configuration information for a mesh network device, such as antenna gain, antenna type, antenna beamwidth, antenna diversity, device orientation, measurement resolution, an indication of smoothing or averaging used for the measurements, energy detector type (e.g., peak detector, root-mean-square (RMS) detector), and so forth. 
     In embodiments, a mesh network device may not wait until all energy detection scans in the scan request message are complete before reporting the results of one or more of the energy detection scans. For example, a mesh network device with a limited amount of buffer capacity may report fewer energy measurements, more frequently, to avoid overflowing its limited buffer capacity by attempting to store all the results for the energy detection scans specified in the scan request message. In another example, a mesh network device may report energy measurements before completing all the results for the energy detection scans specified in the scan request message, such as to provide an earlier initial report of one or more of the first energy detection scans that are performed, to report an interesting or anomalous event such as a high energy level detected (e.g., an energy measurement that exceeds a threshold) on the current operating channel of the mesh network  100 , and so forth. 
     The energy measurement values may be expressed in any appropriate units. For example, the energy measurement values may be expressed directly in any suitable measurement unit, for example dBm, dBμV, milliwatts, and so forth. Alternatively, the result of an energy detection scan measurement may be encoded to reduce the size of the payload required to report the energy measurement values. For example, an energy measurement value is evaluated to determine one of a set of measurement ranges into which the energy measurement value falls. The expected range of energy measurement values is divided into a number of bins that each covers a portion of the expected range. For example, bins may represent a 2 dB portion of the expected range for the energy measurements. Each bin is numbered using a value, such as an unsigned or integer value, which occupies less space in the energy list than the corresponding measurement value. 
     Alternatively, energy measurement values for the N channels may be represented statistically. For example, instead of returning the N sets of measurements, a statistical value of the multiple measurements may be returned. The statistical values may include any of minimum value, a maximum value, a mean value, a media value, a standard deviation, a count of energy detection scans performed, and so forth. 
     In embodiments, energy detection scans may be coordinated between mesh network devices or may be uncoordinated. For example, energy detection scans that are coordinated between the mesh network devices in the mesh network  100  (i.e., synchronized to occur at the same time) provide sets of energy measurements that are correlated in time across the physical, operational space of the mesh network  100 . In another example, energy detection scans that are uncoordinated between devices in the mesh network  100  provide energy measurements at a greater number of different points in time, than coordinated measurements, and provide a more detailed temporal picture of the RF environment. 
     In embodiments, energy detection scans may be coordinated using various techniques. For example, energy detection scans may be scheduled to be performed at specific times by the mesh network devices in the mesh network  100 . In another example, energy detection scans are coordinated by a triggering event. The triggering event can be a router advertisement message, a broadcast message, a localization beacon signal or message, a special transmission signal for triggering energy detection scans, and so forth. 
     In embodiments, coordinating energy detection scans with the triggering event enables energy detection scans to be used in various network analysis and troubleshooting applications. For example, a mobile device transmits one or more timestamped beacon messages that trigger energy detection scans. The devices in the mesh network  100 , which receive a timestamped beacon message, perform an energy detection scan in response to receiving the timestamped beacon message. The mesh network devices that are triggered may include metadata with the energy measurements from the triggered energy detection scan, such as metadata identifying the timestamped beacon that triggered the energy detection scan and/or a received signal strength of the received beacon. 
     In an example application, a user moves the mobile device around to various locations (e.g., a grid of locations, various rooms in a building, etc.) to survey the RF environment by transmitting a beacon message to trigger an energy detection scan for each of the various locations that determines which mesh network devices received the beacon message and the energy measurements that were triggered by the beacon. In another example, the user may use the mobile device to transmit a number of beacon messages to trigger energy detection scans to troubleshoot variations in operating conditions or configurations of the mesh network  100  and/or other nearby wireless equipment. The user triggers an energy scan for each troubleshooting scenario, such as operating the other wireless equipment, disabling the other wireless equipment, moving one or more mesh network devices and/or the other wireless equipment, and so forth, to evaluate the cause and solution to the operational variance. 
       FIG. 4  illustrates example embodiments of the distributed channel sampling across a mesh network. In an embodiment, the commissioning device  210  is the active commissioner for the mesh network  100 . The commissioning device  210  includes a channel manager application  402 . When it is determined that energy detection scans should be performed in the mesh network  100 , the channel manager application  402  sends the scan request message to mesh network devices in the mesh network  100 . The mesh network devices perform energy detection scans as defined in the scan request message. The determination to initiate the energy detection scans may be initiated by the user, scheduled periodically, triggered by connectivity or performance issues, and/or done as part of joining a new mesh network device to the mesh network  100 . 
     Each of the mesh network devices sends the results for completed energy detection scans to the commissioning device  210  in the scan report messages. The channel manager application  402  may directly analyze the results of the energy detection scans to determine if a change to a new channel and/or frequency band would improve performance for the mesh network  100 . If a channel and/or frequency band change is indicated, the commissioning device  210  updates the network configuration information to indicate the change and sends the updated network information to the leader  216  in the mesh network  100 . The leader  216  propagates the updated network information to the rest of the mesh network  100 . 
     Alternatively, the channel manager application  402  may send the results of the energy detection scans to a channel analysis application  404  at the cloud service  208 . The channel analysis application  404  analyzes the energy detection scans and sends a recommendation for the operating channel to the channel manager application  402 . If a channel and/or frequency band change is indicated, the commissioning device  210  updates the network configuration information to indicate the change and sends the updated network information to the leader  216  in the mesh network  100 . The leader  216  propagates the updated network information to the rest of the mesh network  100 . 
     The channel manager application  402  and/or the channel analysis application  404  may maintain history from previous energy detection scans to improve analyzing the current energy detection scan to determine if a channel and/or frequency band change is appropriate. The channel analysis application  404  may also receive and aggregate energy detection scans performed by any number of other mesh networks, which can be used to refine the analysis of the current energy detection scan. 
     In an embodiment, configuration information about the devices in the mesh network  100  may be incorporated into analyzing energy detection scans. Known characteristics of different models of mesh network devices may be factored into the analysis, such as the type of radio chip in the device, antenna characteristics of the device, the manufacturer of the device, the version of radio firmware, and so forth. 
     Alternatively, the devices in the mesh network  100  may be configured to receive energy detection scan requests from the channel analysis application  404  at the cloud service  208  and report energy detection scan results to the channel analysis application  404 . In this configuration, periodic monitoring can be provided to a user even when the user does not have the commissioning device  210  connected to the mesh network  100 . 
     Although aspects of distributed channel sampling across a mesh network are described as being associated with the channel manager application  402  at the commissioning device  210 , and/or the channel analysis application  404  at the cloud service  208 , the described functions may be distributed in any suitable fashion, including distributing some or all of these functions to other devices in the mesh network  100 . For example, the border router  202  or the leader device  216  may be configured as a proxy for the commissioning device  210 . The border router  202  or the leader device  216  may be configured to initiate scan request messages on behalf of the channel manager application  402  at times the commissioning device  210  is not active on the network. The border router  202  or the leader device  216  may store the scanning reports until the commissioning device  210  is once again active on the mesh network  100 . 
     Alternatively, the border router  202  or the leader device  216  may be configured to schedule transmission of scan request messages on a periodic basis to sample RF environmental characteristics over time. For example, the border router  202  or the leader device  216  are configured to schedule scan requests at fixed intervals of time, randomized times, and/or with a schedule that scans more frequently immediately after the mesh network  100  is formed and at a reduced frequency over time. 
     Alternatively, the border router  202  or the leader device  216  may be configured to initiate scan request messages based on performance changes in the mesh network  100 . For example, the border router  202  or the leader device  216  are configured to initiate scan requests based on a trigger condition, such as detecting that retries for packet transmissions exceed a threshold value. 
     Example methods  500  and  600  are described with reference to respective  FIGS. 5 and 6  in accordance with one or more embodiments of the distributed channel sampling across a mesh network. Generally, any of the components, modules, methods, and operations described herein can be implemented using software, firmware, hardware (e.g., fixed logic circuitry), manual processing, or any combination thereof. Some operations of the example methods may be described in the general context of executable instructions stored on computer-readable storage memory that is local and/or remote to a computer processing system, and implementations can include software applications, programs, functions, and the like. Alternatively or in addition, any of the functionality described herein can be performed, at least in part, by one or more hardware logic components, such as, and without limitation, Field-programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (ASICs), Application-specific Standard Products (ASSPs), System-on-a-chip systems (SoCs), Complex Programmable Logic Devices (CPLDs), and the like. 
       FIG. 5  illustrates example method(s)  500  of the distributed channel sampling across a mesh network as generally related to evaluating energy in radio channels across the mesh network. The order in which the method blocks are described are not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement a method, or an alternate method. 
     At block  502 , a mesh network device receives a scan request message specifying a number of energy detection scans to perform. For example, a mesh network device receives a scan request message, over the mesh network  100  from the commissioning device  210 , which includes scanning parameters for the requested energy detection scans. 
     At block  504 , the mesh network device performs an energy detection scan as specified in the scan request message. For example, the mesh network device uses the scanning parameters in the scan request message to perform an energy detection scan. The mesh network device performs the energy detection scan on the channels indicated in a channel mask, for a specified scan duration. 
     At block  506 , a determination is made as to whether more energy detection scans are to be performed. For example, the mesh network device determines whether more energy detection scans are to be performed based on a comparison of the number of energy detection scans that have been performed to the scan count in the scan request message. 
     At block  508 , if there are more scans to be performed, the mesh network device waits for a delay period specified in the scan request message before performing the next energy detection scan. For example, if the mesh network device determines that there are additional energy detection scans to be performed (i.e., “Yes” from  506 ), then the mesh network device starts a timer based on the delay period in the scan request message and performs the next energy detection scan after the timer indicates that the delay period time has elapsed. 
     At block  510 , if there are no more scans to be performed, the mesh network device reports the results of the energy detection scan. For example, the mesh network device determines that the number of energy detection scans specified in the scan count has been completed (i.e., “No” from  506 ), and the mesh network device reports the results of the energy detection scans to the commissioning device  210  in a scan result message. 
       FIG. 6  illustrates example method(s)  600  of the distributed channel sampling across a mesh network as generally related to evaluating energy in radio channels across the mesh network. The order in which the method blocks are described are not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement a method, or an alternate method. 
     At block  602 , a commissioning device sends a scan request message to mesh network devices in a mesh network. For example the channel manager application  402  sends a scan request message from the commissioning device  210  to the mesh network devices in the mesh network  100 . 
     At block  604 , the commissioning device receives scan report messages from mesh network devices in the mesh network. For example the channel manager application  402  receives scan report messages that include the results of energy detection scans performed by mesh network devices in the mesh network  100 . 
     At block  606 , the commissioning device evaluates the received energy detection scan results, and at block  608  determines whether to change the operating channel and/or frequency band of the mesh network. If the determination indicates there is no need to change the channel (i.e., “No” from  608 ), the commissioning device leaves the channel unchanged and sends another scan request message at a later time. For example, the channel manager application  402  evaluates the energy measurements in the received energy detection scan messages to determine if a change in the operating channel and/or frequency band would improve communication in the mesh network  100 . 
     Optionally at block  606 , the commissioning device sends the received energy detection scan results to a channel analysis application resident at a cloud service and receives a recommendation from the channel analysis application that indicates whether to change the operating channel and/or frequency band of the mesh network. For example, the channel manager application  402  sends the results of the energy detection scans over the communication network  206  to the channel analysis application  404  at the cloud service  208 . The channel analysis application  404  evaluates the energy measurements in the received energy detection scan messages to determine if a change in the operating channel and/or frequency band would improve the communication in the mesh network  100 . The channel analysis application  404  sends a recommendation to the channel manager application  402  over the communication network  206  indicating if a change in the operating channel and/or frequency band would improve communication in the mesh network  100 . 
     At block  610 , in response to determining to change the channel (i.e., “Yes” from  608 ), the commissioning device sends updated network configuration data to the leader of the mesh network to propagate the channel and/or frequency band change to the mesh network. For example, the commissioning device  210  sends updated network configuration data to the leader  216  using a management message. The leader  216  then propagates the network data, which includes the channel and/or frequency band change to the other devices in the mesh network  100 . 
       FIG. 7  illustrates an example environment  700  in which the mesh network  100  (as described with reference to  FIG. 1 ), and embodiments of distributed channel sampling across a mesh network can be implemented. Generally, the environment  700  includes the mesh network  100  implemented as part of a smart-home or other type of structure with any number of mesh network devices that are configured for communication in a mesh network. For example, the mesh network devices can include a thermostat  702 , hazard detectors  704  (e.g., for smoke and/or carbon monoxide), cameras  706  (e.g., indoor and outdoor), lighting units  708  (e.g., indoor and outdoor), and any other types of mesh network devices  710  that are implemented inside and/or outside of a structure  712  (e.g., in a smart-home environment). In this example, the mesh network devices can also include any of the previously described devices, such as a border router  202 , a leader device  216 , a commissioning device  210 , as well as any of the devices implemented as a router  102 , and/or an end device  106 . 
     In the environment  700 , any number of the mesh network devices can be implemented for wireless interconnection to wirelessly communicate and interact with each other. The mesh network devices are modular, intelligent, multi-sensing, network-connected devices that can integrate seamlessly with each other and/or with a central server or a cloud-computing system to provide any of a variety of useful smart-home objectives and implementations. An example of a mesh network device that can be implemented as any of the devices described herein is shown and described with reference to  FIG. 8 . 
     In implementations, the thermostat  702  may include a Nest® Learning Thermostat that detects ambient climate characteristics (e.g., temperature and/or humidity) and controls a HVAC system  714  in the smart-home environment. The learning thermostat  702  and other smart devices “learn” by capturing occupant settings to the devices. For example, the thermostat learns preferred temperature set-points for mornings and evenings, and when the occupants of the structure are asleep or awake, as well as when the occupants are typically away or at home. 
     A hazard detector  704  can be implemented to detect the presence of a hazardous substance or a substance indicative of a hazardous substance (e.g., smoke, fire, or carbon monoxide). In examples of wireless interconnection, a hazard detector  704  may detect the presence of smoke, indicating a fire in the structure, in which case the hazard detector that first detects the smoke can broadcast a low-power wake-up signal to all of the connected mesh network devices. The other hazard detectors  704  can then receive the broadcast wake-up signal and initiate a high-power state for hazard detection and to receive wireless communications of alert messages. Further, the lighting units  708  can receive the broadcast wake-up signal and activate in the region of the detected hazard to illuminate and identify the problem area. In another example, the lighting units  708  may activate in one illumination color to indicate a problem area or region in the structure, such as for a detected fire or break-in, and activate in a different illumination color to indicate safe regions and/or escape routes out of the structure. 
     In various configurations, the mesh network devices  710  can include an entryway interface device  716  that functions in coordination with a network-connected door lock system  718 , and that detects and responds to a person&#39;s approach to or departure from a location, such as an outer door of the structure  712 . The entryway interface device  716  can interact with the other mesh network devices based on whether someone has approached or entered the smart-home environment. An entryway interface device  716  can control doorbell functionality, announce the approach or departure of a person via audio or visual means, and control settings on a security system, such as to activate or deactivate the security system when occupants come and go. The mesh network devices  710  can also include other sensors and detectors, such as to detect ambient lighting conditions, detect room-occupancy states (e.g., with an occupancy sensor  720 ), and control a power and/or dim state of one or more lights. In some instances, the sensors and/or detectors may also control a power state or speed of a fan, such as a ceiling fan  722 . Further, the sensors and/or detectors may detect occupancy in a room or enclosure, and control the supply of power to electrical outlets or devices  724 , such as if a room or the structure is unoccupied. 
     The mesh network devices  710  may also include connected appliances and/or controlled systems  726 , such as refrigerators, stoves and ovens, washers, dryers, air conditioners, pool heaters  728 , irrigation systems  730 , security systems  732 , and so forth, as well as other electronic and computing devices, such as televisions, entertainment systems, computers, intercom systems, garage-door openers  734 , ceiling fans  722 , control panels  736 , and the like. When plugged in, an appliance, device, or system can announce itself to the mesh network as described above, and can be automatically integrated with the controls and devices of the mesh network, such as in the smart-home. It should be noted that the mesh network devices  710  may include devices physically located outside of the structure, but within wireless communication range, such as a device controlling a swimming pool heater  728  or an irrigation system  730 . 
     As described above, the mesh network  100  includes a border router  202  that interfaces for communication with an external network, outside the mesh network  100 . The border router  202  connects to an access point  204 , which connects to the communication network  206 , such as the Internet. A cloud service  208 , which is connected via the communication network  206 , provides services related to and/or using the devices within the mesh network  100 . By way of example, the cloud service  208  can include applications for the commissioning device  210 , such as smart phones, tablets, and the like, to devices in the mesh network, processing and presenting data acquired in the mesh network  100  to end users, linking devices in one or more mesh networks  100  to user accounts of the cloud service  208 , provisioning and updating devices in the mesh network  100 , and so forth. For example, a user can control the thermostat  702  and other mesh network devices in the smart-home environment using a network-connected computer or portable device, such as a mobile phone or tablet device. Further, the mesh network devices can communicate information to any central server or cloud-computing system via the border router  202  and the access point  204 . The data communications can be carried out using any of a variety of custom or standard wireless protocols (e.g., Wi-Fi, ZigBee for low power, 6LoWPAN, etc.) and/or by using any of a variety of custom or standard wired protocols (CAT6 Ethernet, HomePlug, etc.). 
     Any of the mesh network devices in the mesh network  100  can serve as low-power and communication nodes to create the mesh network  100  in the smart-home environment. Individual low-power nodes of the network can regularly send out messages regarding what they are sensing, and the other low-powered nodes in the environment—in addition to sending out their own messages—can repeat the messages, thereby communicating the messages from node to node (i.e., from device to device) throughout the mesh network. The mesh network devices can be implemented to conserve power, particularly when battery-powered, utilizing low-powered communication protocols to receive the messages, translate the messages to other communication protocols, and send the translated messages to other nodes and/or to a central server or cloud-computing system. For example, an occupancy and/or ambient light sensor can detect an occupant in a room as well as measure the ambient light, and activate the light source when the ambient light sensor  738  detects that the room is dark and when the occupancy sensor  720  detects that someone is in the room. Further, the sensor can include a low-power wireless communication chip (e.g., a ZigBee chip) that regularly sends out messages regarding the occupancy of the room and the amount of light in the room, including instantaneous messages coincident with the occupancy sensor detecting the presence of a person in the room. As mentioned above, these messages may be sent wirelessly, using the mesh network, from node to node (i.e., smart device to smart device) within the smart-home environment as well as over the Internet to a central server or cloud-computing system. 
     In other configurations, various ones of the mesh network devices can function as “tripwires” for an alarm system in the smart-home environment. For example, in the event a perpetrator circumvents detection by alarm sensors located at windows, doors, and other entry points of the structure or environment, the alarm could still be triggered by receiving an occupancy, motion, heat, sound, etc. message from one or more of the low-powered mesh nodes in the mesh network. In other implementations, the mesh network can be used to automatically turn on and off the lighting units  708  as a person transitions from room to room in the structure. For example, the mesh network devices can detect the person&#39;s movement through the structure and communicate corresponding messages via the nodes of the mesh network. Using the messages that indicate which rooms are occupied, other mesh network devices that receive the messages can activate and/or deactivate accordingly. As referred to above, the mesh network can also be utilized to provide exit lighting in the event of an emergency, such as by turning on the appropriate lighting units  708  that lead to a safe exit. The light units  708  may also be turned-on to indicate the direction along an exit route that a person should travel to safely exit the structure. 
     The various mesh network devices may also be implemented to integrate and communicate with wearable computing devices  740 , such as may be used to identify and locate an occupant of the structure, and adjust the temperature, lighting, sound system, and the like accordingly. In other implementations, RFID sensing (e.g., a person having an RFID bracelet, necklace, or key fob), synthetic vision techniques (e.g., video cameras and face recognition processors), audio techniques (e.g., voice, sound pattern, vibration pattern recognition), ultrasound sensing/imaging techniques, and infrared or near-field communication (NFC) techniques (e.g., a person wearing an infrared or NFC-capable smartphone), along with rules-based inference engines or artificial intelligence techniques that draw useful conclusions from the sensed information as to the location of an occupant in the structure or environment. 
     In other implementations, personal comfort-area networks, personal health-area networks, personal safety-area networks, and/or other such human-facing functionalities of service robots can be enhanced by logical integration with other mesh network devices and sensors in the environment according to rules-based inferencing techniques or artificial intelligence techniques for achieving better performance of these functionalities. In an example relating to a personal health-area, the system can detect whether a household pet is moving toward the current location of an occupant (e.g., using any of the mesh network devices and sensors), along with rules-based inferencing and artificial intelligence techniques. Similarly, a hazard detector service robot can be notified that the temperature and humidity levels are rising in a kitchen, and temporarily raise a hazard detection threshold, such as a smoke detection threshold, under an inference that any small increases in ambient smoke levels will most likely be due to cooking activity and not due to a genuinely hazardous condition. Any service robot that is configured for any type of monitoring, detecting, and/or servicing can be implemented as a mesh node device on the mesh network, conforming to the wireless interconnection protocols for communicating on the mesh network. 
     The mesh network devices  710  may also include a smart alarm clock  744  for each of the individual occupants of the structure in the smart-home environment. For example, an occupant can customize and set an alarm device for a wake time, such as for the next day or week. Artificial intelligence can be used to consider occupant responses to the alarms when they go off and make inferences about preferred sleep patterns over time. An individual occupant can then be tracked in the mesh network based on a unique signature of the person, which is determined based on data obtained from sensors located in the mesh network devices, such as sensors that include ultrasonic sensors, passive IR sensors, and the like. The unique signature of an occupant can be based on a combination of patterns of movement, voice, height, size, etc., as well as using facial recognition techniques. 
     In an example of wireless interconnection, the wake time for an individual can be associated with the thermostat  702  to control the HVAC system in an efficient manner so as to pre-heat or cool the structure to desired sleeping and awake temperature settings. The preferred settings can be learned over time, such as by capturing the temperatures set in the thermostat before the person goes to sleep and upon waking up. Collected data may also include biometric indications of a person, such as breathing patterns, heart rate, movement, etc., from which inferences are made based on this data in combination with data that indicates when the person actually wakes up. Other mesh network devices can use the data to provide other smart-home objectives, such as adjusting the thermostat  702  so as to pre-heat or cool the environment to a desired setting, and turning-on or turning-off the lights  708 . 
     In implementations, the mesh network devices can also be utilized for sound, vibration, and/or motion sensing such as to detect running water and determine inferences about water usage in a smart-home environment based on algorithms and mapping of the water usage and consumption. This can be used to determine a signature or fingerprint of each water source in the home, and is also referred to as “audio fingerprinting water usage.” Similarly, the mesh network devices can be utilized to detect the subtle sound, vibration, and/or motion of unwanted pests, such as mice and other rodents, as well as by termites, cockroaches, and other insects. The system can then notify an occupant of the suspected pests in the environment, such as with warning messages to help facilitate early detection and prevention. 
       FIG. 8  illustrates an example mesh network device  800  that can be implemented as any of the mesh network devices in a mesh network in accordance with one or more embodiments of distributed channel sampling across a mesh network as described herein. The device  800  can be integrated with electronic circuitry, microprocessors, memory, input output (I/O) logic control, communication interfaces and components, as well as other hardware, firmware, and/or software to implement the device in a mesh network. Further, the mesh network device  800  can be implemented with various components, such as with any number and combination of different components as further described with reference to the example device shown in  FIG. 9 . 
     In this example, the mesh network device  800  includes a low-power microprocessor  802  and a high-power microprocessor  804  (e.g., microcontrollers or digital signal processors) that process executable instructions. The device also includes an input-output (I/O) logic control  806  (e.g., to include electronic circuitry). The microprocessors can include components of an integrated circuit, programmable logic device, a logic device formed using one or more semiconductors, and other implementations in silicon and/or hardware, such as a processor and memory system implemented as a system-on-chip (SoC). Alternatively or in addition, the device can be implemented with any one or combination of software, hardware, firmware, or fixed logic circuitry that may be implemented with processing and control circuits. The low-power microprocessor  802  and the high-power microprocessor  804  can also support one or more different device functionalities of the device. For example, the high-power microprocessor  804  may execute computationally intensive operations, whereas the low-power microprocessor  802  may manage less complex processes such as detecting a hazard or temperature from one or more sensors  808 . The low-power processor  802  may also wake or initialize the high-power processor  804  for computationally intensive processes. 
     The one or more sensors  808  can be implemented to detect various properties such as acceleration, temperature, humidity, water, supplied power, proximity, external motion, device motion, sound signals, ultrasound signals, light signals, fire, smoke, carbon monoxide, global-positioning-satellite (GPS) signals, radio-frequency (RF), other electromagnetic signals or fields, or the like. As such, the sensors  808  may include any one or a combination of temperature sensors, humidity sensors, hazard-related sensors, other environmental sensors, accelerometers, microphones, optical sensors up to and including cameras (e.g., charged coupled-device or video cameras, active or passive radiation sensors, GPS receivers, and radio frequency identification detectors. In implementations, the mesh network device  800  may include one or more primary sensors, as well as one or more secondary sensors, such as primary sensors that sense data central to the core operation of the device (e.g., sensing a temperature in a thermostat or sensing smoke in a smoke detector), while the secondary sensors may sense other types of data (e.g., motion, light or sound), which can be used for energy-efficiency objectives or smart-operation objectives. 
     The mesh network device  800  includes a memory device controller  810  and a memory device  812 , such as any type of a nonvolatile memory and/or other suitable electronic data storage device. The mesh network device  800  can also include various firmware and/or software, such as an operating system  814  that is maintained as computer executable instructions by the memory and executed by a microprocessor. The device software may also include a channel scanning application  816  that implements embodiments of distributed channel sampling across a mesh network. The mesh network device  800  also includes a device interface  818  to interface with another device or peripheral component, and includes an integrated data bus  820  that couples the various components of the mesh network device for data communication between the components. The data bus in the mesh network device may also be implemented as any one or a combination of different bus structures and/or bus architectures. 
     The device interface  818  may receive input from a user and/or provide information to the user (e.g., as a user interface), and a received input can be used to determine a setting. The device interface  818  may also include mechanical or virtual components that respond to a user input. For example, the user can mechanically move a sliding or rotatable component, or the motion along a touchpad may be detected, and such motions may correspond to a setting adjustment of the device. Physical and virtual movable user-interface components can allow the user to set a setting along a portion of an apparent continuum. The device interface  818  may also receive inputs from any number of peripherals, such as buttons, a keypad, a switch, a microphone, and an imager (e.g., a camera device). 
     The mesh network device  800  can include network interfaces  822 , such as a mesh network interface for communication with other mesh network devices in a mesh network, and an external network interface for network communication, such as via the Internet. The mesh network device  800  also includes wireless radio systems  824  for wireless communication with other mesh network devices via the mesh network interface and for multiple, different wireless communications systems. The wireless radio systems  824  may include Wi-Fi, Bluetooth™, Mobile Broadband, and/or point-to-point IEEE 802.15.4. Each of the different radio systems can include a radio device, antenna, and chipset that is implemented for a particular wireless communications technology. The mesh network device  800  also includes a power source  826 , such as a battery and/or to connect the device to line voltage. An AC power source may also be used to charge the battery of the device. 
       FIG. 9  illustrates an example system  900  that includes an example device  902 , which can be implemented as any of the mesh network devices that implement embodiments of distributed channel sampling across a mesh network as described with reference to the previous  FIGS. 1-8 . The example device  902  may be any type of computing device, client device, mobile phone, tablet, communication, entertainment, gaming, media playback, and/or other type of device. Further, the example device  902  may be implemented as any other type of mesh network device that is configured for communication on a mesh network, such as a thermostat, hazard detector, camera, light unit, commissioning device, router, border router, joiner router, joining device, end device, leader, access point, and/or other mesh network devices. 
     The device  902  includes communication devices  904  that enable wired and/or wireless communication of device data  906 , such as data that is communicated between the devices in a mesh network, data that is being received, data scheduled for broadcast, data packets of the data, data that is synched between the devices, etc. The device data can include any type of communication data, as well as audio, video, and/or image data that is generated by applications executing on the device. The communication devices  904  can also include transceivers for cellular phone communication and/or for network data communication. 
     The device  902  also includes input/output (I/O) interfaces  908 , such as data network interfaces that provide connection and/or communication links between the device, data networks (e.g., a mesh network, external network, etc.), and other devices. The I/O interfaces can be used to couple the device to any type of components, peripherals, and/or accessory devices. The I/O interfaces also include data input ports via which any type of data, media content, and/or inputs can be received, such as user inputs to the device, as well as any type of communication data, as well as audio, video, and/or image data received from any content and/or data source. 
     The device  902  includes a processing system  910  that may be implemented at least partially in hardware, such as with any type of microprocessors, controllers, and the like that process executable instructions. The processing system can include components of an integrated circuit, programmable logic device, a logic device formed using one or more semiconductors, and other implementations in silicon and/or hardware, such as a processor and memory system implemented as a system-on-chip (SoC). Alternatively or in addition, the device can be implemented with any one or combination of software, hardware, firmware, or fixed logic circuitry that may be implemented with processing and control circuits. The device  902  may further include any type of a system bus or other data and command transfer system that couples the various components within the device. A system bus can include any one or combination of different bus structures and architectures, as well as control and data lines. 
     The device  902  also includes computer-readable storage memory  912 , such as data storage devices that can be accessed by a computing device, and that provide persistent storage of data and executable instructions (e.g., software applications, modules, programs, functions, and the like). The computer-readable storage memory described herein excludes propagating signals. Examples of computer-readable storage memory include volatile memory and non-volatile memory, fixed and removable media devices, and any suitable memory device or electronic data storage that maintains data for computing device access. The computer-readable storage memory can include various implementations of random access memory (RAM), read-only memory (ROM), flash memory, and other types of storage memory in various memory device configurations. 
     The computer-readable storage memory  912  provides storage of the device data  906  and various device applications  914 , such as an operating system that is maintained as a software application with the computer-readable storage memory and executed by the processing system  910 . The device applications may also include a device manager, such as any form of a control application, software application, signal processing and control module, code that is native to a particular device, a hardware abstraction layer for a particular device, and so on. In this example, the device applications also include a channel scanning application  916  that implements embodiments of distributed channel sampling across a mesh network, such as when the example device  902  is implemented as any of the mesh network devices described herein. 
     The device  902  also includes an audio and/or video system  918  that generates audio data for an audio device  920  and/or generates display data for a display device  922 . The audio device and/or the display device include any devices that process, display, and/or otherwise render audio, video, display, and/or image data, such as the image content of a digital photo. In implementations, the audio device and/or the display device are integrated components of the example device  902 . Alternatively, the audio device and/or the display device are external, peripheral components to the example device. In embodiments, at least part of the techniques described for distributed channel sampling across a mesh network may be implemented in a distributed system, such as over a “cloud”  924  in a platform  926 . The cloud  924  includes and/or is representative of the platform  926  for services  928  and/or resources  930 . 
     The platform  926  abstracts underlying functionality of hardware, such as server devices (e.g., included in the services  928 ) and/or software resources (e.g., included as the resources  930 ), and connects the example device  902  with other devices, servers, etc. The resources  930  may also include applications and/or data that can be utilized while computer processing is executed on servers that are remote from the example device  902 . Additionally, the services  928  and/or the resources  930  may facilitate subscriber network services, such as over the Internet, a cellular network, or Wi-Fi network. The platform  926  may also serve to abstract and scale resources to service a demand for the resources  930  that are implemented via the platform, such as in an interconnected device embodiment with functionality distributed throughout the system  900 . For example, the functionality may be implemented in part at the example device  902  as well as via the platform  926  that abstracts the functionality of the cloud  924 . 
     Although embodiments of distributed channel sampling across a mesh network have been described in language specific to features and/or methods, the subject of the appended claims is not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as example implementations of distributed channel sampling across a mesh network, and other equivalent features and methods are intended to be within the scope of the appended claims. Further, various different embodiments are described and it is to be appreciated that each described embodiment can be implemented independently or in connection with one or more other described embodiments.