Abstract: Described is a method for performance estimation of a communication device. The method comprises: executing active probing to determine active probing data; reading operational data which includes data related to channel and its noise condition, latency and counter values related to user data traffic between the communication device and another communication device, wherein the operational data is relevant to the current settings of the communication device; and training a performance estimation algorithm for the communication device according to the active probing data and the operational data.

Abstract: Described is a method performed by a computing device for generating policies for improving network system performance, the method comprising: receiving operational data from a network device; processing the operational data from the network device to generate a Wi-Fi management policy; merging the Wi-Fi management policy, a mobile device policy, and a user preference or user policy to generate a unified policy; and sending the unified policy to the network device for network management.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for traffic aggregation on multiple Wide Area Network (WAN) backhauls and multiple distinct Local Area Network (LAN) networks; for traffic load balancing on multiple WAN backhauls and multiple distinct LAN networks; and for performing self-healing operations utilizing multiple WAN backhauls serving multiple distinct LAN networks.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a power control server system receives an emissions rate forecast for a predefined future time period. Using the emissions rate forecast, an emissions rate event is identified during the predefined future time period. Based on the plurality of emissions rate event, an emissions demand response event is generated during the predefined future time period. The power control server system then causes a power controller to modify an energy consumption by an electronic device in accordance with the generated emissions demand response event.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system obtains a history of emissions rates. Based on the history of emissions rates, a future time period of predicted high emissions is identified. An emission demand response event participation level of an account mapped to a thermostat is determined for the future time period of predicted high emissions. The emissions demand response event participation level may be one of a plurality of emissions demand response event participation levels. based on the emissions demand response event participation level of the account, an emissions demand response event is generated during the future time period of predicted high emissions. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Techniques for instantiating energy saving setpoint adjustments are described. In an example, a heating, ventilation, and air conditioning (HVAC) system is controlled via a thermostat during a first time period according to a first temperature setpoint schedule including one or more temperature setpoints and a first usage amount of the HVAC system is monitored during the first time period. After it is determined that the first usage amount of the HVAC system during the first time period has met a first predefined HVAC runtime threshold criterion, a second temperature setpoint schedule is generated with at least one of the one or more temperature setpoints being adjusted to decrease energy usage by the HVAC system compared to the first temperature setpoint schedule. The HVAC system is then controlled via the thermostat during a second time period according to the second temperature setpoint schedule.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for traffic aggregation on multiple Wide Area Network (WAN) backhauls and multiple distinct Local Area Network (LAN) networks; for traffic load balancing on multiple WAN backhauls and multiple distinct LAN networks; and for performing self-healing operations utilizing multiple WAN backhauls serving multiple distinct LAN networks.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system receives an emissions rate forecast for a predefined future time period. Using the emissions rate forecast, a plurality of emissions differential values are created for a plurality of points in time during the predefined future time period. The emissions differential values represent a change in predicted emissions over time. Based on the plurality of emissions differential values and a predefined maximum number of emissions demand response events, an emissions demand response event is generated during the predefined future time period. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system obtains an emissions rate forecast for a predefined future time period. Using the emissions rate forecast, a future emissions rate event during the predefined future time period is identified. The future emissions rate event comprises an indication of predicted magnitude and a time period when a predicted emissions rate will be at an increased or decreased level. A confidence value indicating a certainty of the future emissions rate event occurring as predicted is determined. Based on the identified future emissions rate event and the confidence value, an emissions demand response event having a start time and an end time during the future emissions rate event is generated. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Described is a method and system for connectivity diagnostics in communication systems. The method comprises: querying a first communication device at a first time and a second time to determine whether a second communication device is connected to the first communication device and to determine a value of an operational parameter at the first and second times; and determining the second communication device disconnected from the first communication device based on detecting the second communication device was connected to the first communication device at both the first time and the second time, and detecting the value of the operational parameter at the second time is inside a range of threshold values. In one embodiment, the method comprises determining a link is unstable for connectivity based on connection duration, number and/or pattern of connection and/or disconnection events, and/or traffic activity during connection and/or disconnection events.

Abstract: Techniques for instantiating energy saving setpoint adjustments are described. In an example, a heating, ventilation, and air conditioning (HVAC) system is controlled via a thermostat during a first time period according to a first temperature setpoint schedule including one or more temperature setpoints and a first usage amount of the HVAC system is monitored during the first time period. After it is determined that the first usage amount of the HVAC system during the first time period has met a first predefined HVAC runtime threshold criterion, a second temperature setpoint schedule is generated with at least one of the one or more temperature setpoints being adjusted to decrease energy usage by the HVAC system compared to the first temperature setpoint schedule. The HVAC system is then controlled via the thermostat during a second time period according to the second temperature setpoint schedule.

Abstract: Described is a method and system for connectivity diagnostics in communication systems. The method comprises: querying a first communication device at a first time and a second time to determine whether a second communication device is connected to the first communication device and to determine a value of an operational parameter at the first and second times; and determining the second communication device disconnected from the first communication device based on detecting the second communication device was connected to the first communication device at both the first time and the second time, and detecting the value of the operational parameter at the second time is inside a range of threshold values. In one embodiment, the method comprises determining a link is unstable for connectivity based on connection duration, number and/or pattern of connection and/or disconnection events, and/or traffic activity during connection and/or disconnection events.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system obtains a history of emissions rates. Based on the history of emissions rates, a future time period of predicted high emissions is identified. An emission demand response event participation level of an account mapped to a thermostat is determined for the future time period of predicted high emissions. The emissions demand response event participation level may be one of a plurality of emissions demand response event participation levels. based on the emissions demand response event participation level of the account, an emissions demand response event is generated during the future time period of predicted high emissions. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system receives an emissions rate forecast for a predefined future time period. Using the emissions rate forecast, a plurality of emissions differential values are created for a plurality of points in time during the predefined future time period. The emissions differential values represent a change in predicted emissions over time. Based on the plurality of emissions differential values and a predefined maximum number of emissions demand response events, an emissions demand response event is generated during the predefined future time period. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Techniques for performing an emissions demand response event are described. In an example, a cloud-based HVAC control server system obtains an emissions rate forecast for a predefined future time period. Using the emissions rate forecast, a future emissions rate event during the predefined future time period is identified. The future emissions rate event comprises an indication of predicted magnitude and a time period when a predicted emissions rate will be at an increased or decreased level. A confidence value indicating a certainty of the future emissions rate event occurring as predicted is determined. Based on the identified future emissions rate event and the confidence value, an emissions demand response event having a start time and an end time during the future emissions rate event is generated. The cloud-based HVAC control server system then causes a thermostat to control an HVAC system in accordance with the generated emissions demand response event.

Abstract: Techniques for performing an emissions demand response (EDR) event are described. In an example, a cloud-based HVAC control system may obtain a first emissions rate forecast and generate an EDR event with a start time and end time based on the first emissions rate forecast. The EDR event may then be transmitted to a thermostat and stored in a memory of the thermostat. At the start time, the thermostat may commence controlling an HVAC system according to the EDR event. After the start time and prior to the end time, the cloud-based HVAC control system may obtain a second emissions rate forecast and generate a modified EDR event with a modified end time. The modified EDR event may be transmitted to the thermostat before the end time and/or the modified end time whereupon the thermostat may control the HVAC system accordingly until the modified end time is reached.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for traffic aggregation on multiple WAN backhauls and multiple distinct LAN networks; for traffic load balancing on multiple WAN backhauls and multiple distinct LAN networks; and for performing self-healing operations utilizing multiple WAN backhauls serving multiple distinct LAN networks. For example, in one embodiment, a first Local Area Network (LAN) access device is to establish a first LAN; a second LAN access device is to establish a second LAN; a first Wide Area Network (WAN) backhaul connection is to provide the first LAN access device with WAN connectivity; a second WAN backhaul connection is to provide the second LAN access device with WAN connectivity; and a traffic aggregation unit is to form a logically bonded WAN interface over the first WAN backhaul and the second WAN backhaul. In some embodiments an optional traffic de-aggregation unit may be used.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for traffic aggregation on multiple WAN backhauls and multiple distinct LAN networks; for traffic load balancing on multiple WAN backhauls and multiple distinct LAN networks; and for performing self-healing operations utilizing multiple WAN backhauls serving multiple distinct LAN networks. For example, in one embodiment, a first Local Area Network (LAN) access device is to establish a first LAN; a second LAN access device is to establish a second LAN; a first Wide Area Network (WAN) backhaul connection is to provide the first LAN access device with WAN connectivity; a second WAN backhaul connection is to provide the second LAN access device with WAN connectivity; and a traffic aggregation unit is to form a logically bonded WAN interface over the first WAN backhaul and the second WAN backhaul. In some embodiments an optional traffic de-aggregation unit may be used.

Abstract: Described is a method for performance estimation of a communication device. The method comprises: executing active probing to determine active probing data; reading operational data which includes data related to channel and its noise condition, latency and counter values related to user data traffic between the communication device and another communication device, wherein the operational data is relevant to the current settings of the communication device; and training a performance estimation algorithm for the communication device according to the active probing data and the operational data.

Abstract: Described is a method performed by a computing device for controlling home network system associated with a plurality of Wi-Fi communicating devices, the method comprising: analyzing operational data associated with the plurality of Wi-Fi communicating devices, the operational data collected from plurality of Wi-Fi communicating devices; providing (or generating) recommendations for improving performance of the home network system according to the analyzed operational data; correlating the recommendations into groups; and aggregating the recommendations from the groups to generate unified recommendations for improving the home network system.