Decentralized computing networks, architectures and techniques for processing events across multiple channels
This disclosure relates to decentralized computing networks, architectures and techniques for collecting, analyzing, and processing data over multiple channels. A decentralized computing network comprises a plurality of computing nodes, each of which is dedicated to analyzing and processing events for a particular channel corresponding to a geographic region. Each node of the decentralized computing network can operate independently to process channel analysis data for a corresponding channel. The decentralized configuration of the nodes enables efficient processing of data collected over large geographic areas, increases the reliability of the system, and facilitates easy scaling of the system. Other embodiments are disclosed herein as well.
1. A computerized method for processing data across multiple channels, comprising:
providing a decentralized computing network comprising a plurality of nodes, wherein the plurality of nodes included in the decentralized computing network are arranged in a geographical hierarchy that defines parent-child relationships based on geographic associations;
associating each node of the decentralized computing network with a separate channel corresponding to a geographic region;
configuring each node of the decentralized computing network to receive and analyze channel events for the channel associated with the node;
generating, by each node of the decentralized computing network, channel analysis data corresponding to the channel associated with the node, wherein the channel analysis data for the channel is generated based, at least in part, on an analysis of the channel events corresponding to the channel associated with the node;
detecting, by at least one of the plurality of nodes, a demand surge in one or more channels based on the channel analysis data; and
in response to detecting the demand surge, executing a demand adjustment function that adjusts the price of one or more inventory items based, at least in part, on a demand for the one or more inventory items in the one or more channels or adjust allocations of the one or more inventory items based, at least in part, on the demand for the one or more inventory items in the one or more channels.
2. The computerized method of claim 1 , wherein a node communication protocol enables exchange of data among the plurality of nodes based, at least in part, on the parent-child relationships included in the geographical hierarchy.
3. The computerized method of claim 2 , wherein:
the node communication protocol enables a parent node to obtain the channel analysis data generated by one or more child nodes; and
the channel analysis data generated by the one or more child nodes is utilized by the parent node to generate the channel analysis data for the channel associated with the parent node.
4. The computerized method of claim 2 , wherein the node communication protocol utilizes a blockchain protocol to facilitate the exchange of data among the plurality of nodes.
5. The computerized method of claim 1 , wherein the method further comprises:
executing one or more deployment functions that enable the channel analysis data to be accessed by one or more client systems, wherein the one or more deployment functions facilitate interfacing with the one or more client systems and enable the channel analysis data to be provided directly to the one or more client systems.
6. The computerized method of claim 1 , wherein the method further comprises:
executing one or more deployment functions that enable transmission of notifications to the one or more client systems, wherein the notifications include at least a portion of the channel analysis data.
7. The computerized method of claim 1 , wherein the channel analysis data generated by each node comprises predictive metrics pertaining to future conditions for the channel associated with the node.
8. The computerized method of claim 1 , wherein the channel analysis data generated by each node comprises metrics pertaining to actual or current conditions for the channel associated with the node.
9. The computerized method of claim 1 , wherein the channel analysis data generated by each node comprises:
population metrics predicting or indicating population fluctuations in the channel associated with the node;
movement tracking metrics predicting or indicating movements of individuals within the channel associated with the node; and
demand metrics predicting or indicating a demand for one or more inventory items in the channel associated with the node.
10. The computerized method of claim 1 , wherein the demand adjustment function includes at least one of:
a surge pricing function that is configured to dynamically adjust pricing for one or more inventory items based, at least in part, on a supply or demand for the inventory items; or
an inventory management function that adjusts allocations of the inventory items based, at least in part, on a supply or demand for the inventory items.
11. The computerized method of claim 1 , wherein the demand surge indicates an upward or downward fluctuation in the demand for the one or more inventory items.
12. A system for processing data across multiple channels, comprising:
a decentralized computing network comprising one or more processing devices and one or more non-transitory computer storage devices storing computing instructions configured to be executed on the one or more processors and cause the one or more processors to process data for a plurality of nodes wherein:
the plurality of nodes included in the decentralized computing network are arranged in a geographical hierarchy that defines parent-child relationships based on geographic associations;
each node in the decentralized computing network is dedicated to a separate channel corresponding to a geographic region;
each node in the decentralized computing network receives channel events corresponding to the channel associated with the node;
each node in the decentralized computing network is configured to generate channel analysis data based, at least in part, on an analysis of the channel events corresponding to the channel associated with the node;
based on the channel analysis data, each node in the decentralized computing network is configured to determine whether a demand surge is occurring in the channel associated with the node; and
in response to detecting the demand surge, a demand adjustment function is executed to adjust the price of one or more inventory items based, at least in part, on a demand for the one or more inventory items in the channel associated with the node or adjust allocations of the one or more inventory items based, at least in part, on the demand for the one or more inventory items.
13. The system of claim 12 , wherein a node communication protocol enables exchange of data among the plurality of nodes based, at least in part, on the parent-child relationships included in the geographical hierarchy.
14. The system of claim 13 , wherein:
the node communication protocol enables a parent node to obtain the channel analysis data generated by one or more child nodes; and
the channel analysis data generated by the one or more child nodes is utilized by the parent node to generate the channel analysis data for the channel associated with the parent node.
15. The system of claim 13 , wherein the node communication protocol utilizes a blockchain protocol to facilitate the exchange of data among the plurality of nodes.
16. The system of claim 12 , wherein one or more deployment functions allow for interfacing with one or more client systems and enable the channel analysis data to be provided directly to the one or more client systems.
17. The system of claim 12 , wherein one or more deployment functions enable transmission of notifications to the one or more client systems, and the notifications include at least a portion of the channel analysis data.
18. The system of claim 12 , wherein the channel analysis data generated by each node comprises predictive metrics pertaining to future conditions for the channel associated with the node.
19. The system of claim 12 , wherein the channel analysis data generated by each node comprises metrics pertaining to actual or current conditions for the channel associated with the node.
20. The system of claim 12 , wherein the channel analysis data generated by each node comprises:
population metrics predicting or indicating population fluctuations in the channel associated with the node;
movement tracking metrics predicting or indicating movements of individuals within the channel associated with the node; and
demand metrics predicting or indicating a demand for one or more inventory items in the channel associated with the node.
21. The system of claim 12 , wherein the demand adjustment functions comprises:
a surge pricing function that is configured to dynamically adjust pricing for one or more inventory items based, at least in part, on a supply or demand for the inventory items; or
an inventory management function that adjusts allocations of the inventory items based, at least in part, on a supply or demand for the inventory items.
22. The system of claim 12 , wherein the demand surge indicates an upward or downward fluctuation in the demand for the one or more inventory items.
23. A computerized method for processing data across multiple channels, comprising:
providing a decentralized computing network comprising a plurality of nodes;
associating each node of the decentralized computing network with a separate channel corresponding to a geographic region;
configuring each node of the decentralized computing network to receive and analyze channel events for the channel associated with the node;
generating, by each node of the decentralized computing network, channel analysis data corresponding to the channel associated with the node, wherein the channel analysis data for the channel is generated based, at least in part, on an analysis of the channel events corresponding to the channel associated with the node, and the channel analysis data generated by each node comprises:
population metrics predicting or indicating population fluctuations in the channel associated with the node;
movement tracking metrics predicting or indicating movements of individuals within the channel associated with the node; and
demand metrics predicting or indicating a demand for one or more inventory items in the channel associated with the node;
detecting, by at least one of the plurality of nodes, a demand surge in one or more channels based on the channel analysis data; and
in response to detecting the demand surge, executing a demand adjustment function that adjusts the price of one or more inventory items based, at least in part, on the demand for the one or more inventory items in the one or more channels or adjust allocations of the one or more inventory items based, at least in part, on the demand for the one or more inventory items in the one or more channels.
24. A system for processing data across multiple channels, comprising:
a decentralized computing network comprising one or more processing devices and one or more non-transitory computer storage devices storing computing instructions configured to be executed on the one or more processors and cause the one or more processors to process data for a plurality of nodes wherein:
each node in the decentralized computing network is dedicated to a separate channel corresponding to a geographic region;
each node in the decentralized computing network receives channel events corresponding to the channel associated with the node;
each node in the decentralized computing network is configured to generate channel analysis data based, at least in part, on an analysis of the channel events corresponding to the channel associated with the node, and the channel analysis data generated by each node comprises:
population metrics predicting or indicating population fluctuations in the channel associated with the node;
movement tracking metrics predicting or indicating movements of individuals within the channel associated with the node; and
demand metrics predicting or indicating a demand for one or more inventory items in the channel associated with the node;
based on the channel analysis data, each node in the decentralized computing network is configured to determine whether a demand surge is occurring in the channel associated with the node; and
in response to detecting the demand surge, a demand adjustment function is executed to adjust the price of one or more inventory items based, at least in part, on the demand for the one or more inventory items in the channel associated with the node or adjust allocations of the one or more inventory items based, at least in part, on the demand for the one or more inventory items.