Cloud Streaming Pods for Low-Latency Demand Scaling
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Solution Overview
Problem
Existing live streaming systems lack the necessary flexibility to adapt to sharp changes in content demand, leading to inefficiencies in resource management and latency.
Innovation Solution
A live streaming system utilizing cloud-based reconfigurable service pods arranged in geographical zones, enabling dynamic scaling and reconfiguration to meet demand without adding or removing resources, combined with latency management and bitrate adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional approaches use a combination of cellular data and WiFi access points to handle high demand, then content delivery capability is improved, but infrastructure cost and complexity increase substantially
Solution Approach 1:
The patent creates virtual copies of server functionalities through containerized pods that can be deployed across multiple geographical locations. These software-based copies replicate streaming capabilities without requiring physical hardware replication, reducing infrastructure complexity while maintaining content delivery capability.
Solution Approach 2:
The patent replaces traditional mechanical/physical infrastructure (cellular towers, WiFi access points, physical servers) with software-based containerized pods that run on standard hardware. This substitution reduces infrastructure complexity by eliminating the need for specialized physical equipment while maintaining or improving content delivery capability.
2Loss of time
If multiple servers serve specific geographical regions with edge servers, then latency is reduced, but system flexibility to cope with demand variations deteriorates
Solution Approach 1:
The patent implements dynamic pod deployment where containerized pods can be automatically instantiated, moved, or scaled across geographical locations based on real-time demand. This dynamic approach maintains low latency by keeping pods close to users while simultaneously providing flexibility to adapt to demand variations without fixed regional constraints.
Solution Approach 2:
The patent creates universal pod instances that can serve multiple functions and multiple geographical regions simultaneously. These pods are not dedicated to specific regions but can dynamically serve any location based on demand, providing both low latency (by being close to any user) and high flexibility (by not being regionally constrained).
3Productivity
If system capacity is adjusted by increment and reduction of pods and nodes, then scalability is improved, but communication possibilities between pods are reduced resulting in lower system flexibility
Solution Approach 1:
The patent merges scaling and communication capabilities by maintaining a persistent mesh network among all pods regardless of their scaling status. When pods are incremented or reduced, they automatically integrate into or exit from the mesh network, ensuring continuous communication possibilities while maintaining scalability.
Solution Approach 2:
The patent implements feedback mechanisms where pods continuously monitor network conditions and demand patterns, automatically adjusting their communication routes and collaborations. This feedback loop ensures that as pods are scaled, the system dynamically optimizes communication paths to maintain or enhance system flexibility rather than reducing it.
4Productivity
If low-level network resources are added or subtracted to achieve scalable capacity, then system scalability is improved, but the ability to create a resource buffer that can cope with demand spikes deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-positioning containerized pods in a mesh network architecture before demand spikes occur. These pods can be quickly activated and integrated into the network when demand increases, providing an immediate resource buffer. The mesh structure is prepared in advance to accommodate rapid pod addition without requiring complex reconfiguration.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting pod replication factors, resource allocation parameters, and network routing parameters in response to demand conditions. This allows the system to maintain scalability while also creating resource buffers, as parameters can be tuned to either optimize for scale or for resilience against demand spikes depending on current conditions.
Data Source
AI summary
The current invention relates to a live broadcasting system comprising at least one media capture device in communication with an encoder, which encoder is in further communication with a plurality of cloud-based pods and a control module configured to manage said pods. Each pod is functionally reconfigurable and can function as a stream receiver, stream sender or transcoder. The system is also reached by a method of broadcasting a live stream.