Dynamic Server Load Balancing via Duration Ranges
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Solution Overview
Problem
Content delivery networks face challenges in efficiently managing server resources to balance load distribution for streaming content, leading to either insufficient or excessive server usage, resulting in wasted resources and inefficiencies.
Innovation Solution
A dynamic load balancing approach where computing devices are assigned unique duration ranges for handling content requests, with adjustments made based on load status, allowing for redistribution of processing loads and potential shutdown of underutilized devices to conserve resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more computing devices are deployed to service user requests, then the ability to adequately service user requests is improved, but resource consumption (electricity and personnel maintenance) increases
Solution Approach 1:
The patent implements dynamic load balancing by continuously monitoring the load status of computing devices and adjusting the distribution of content requests in real-time. This allows the system to adapt to changing conditions, ensuring adequate service capacity while minimizing resource consumption by actively managing which devices are processing requests and which are in standby or hibernation states.
Solution Approach 2:
The system changes operational parameters by adjusting the load distribution across computing devices based on monitored performance metrics. By dynamically modifying which devices are active, in standby, or hibernating, the system optimizes the balance between service capability and resource consumption without requiring a fixed infrastructure configuration.
2Reliability
If computing devices operate continuously to ensure service availability, then user request handling is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic monitoring of load status across computing devices and periodically adjusts their operational states. Devices are cycled between active, standby, and hibernation states based on periodic load assessments, ensuring service availability when needed while minimizing energy consumption during low-demand periods through structured periodic state changes.
Solution Approach 2:
The load balancing system operates autonomously by automatically monitoring device load status and making real-time decisions about request distribution and device state management. This self-service capability ensures service availability is maintained dynamically without requiring continuous human intervention, while simultaneously optimizing energy usage by automatically placing underutilized devices in lower-power states.
3Loss of energy
If load balancing is implemented dynamically with frequent adjustments, then resource optimization is improved, but system complexity increases
Solution Approach 1:
The patent segments the computing device infrastructure into distinct operational states (active, standby, hibernation) and manages them separately through a hierarchical load balancing approach. This segmentation simplifies the control logic by treating each state category uniformly, reducing overall system complexity while enabling effective resource optimization through state-based management.
Solution Approach 2:
The system introduces a load balancing intermediary layer that sits between user requests and the computing devices. This intermediary monitors load status and makes intelligent routing decisions, simplifying the complexity by centralizing the decision-making logic in a dedicated component rather than distributing complex control logic across all devices, thereby enabling resource optimization without proportionally increasing overall system complexity.
Data Source
AI summary
A content providing service may employ a variety of streaming devices such as servers, and may associate or assign the servers to different content duration time ranges. Each server may then be responsible for servicing requests for content whose duration lies within the server's assigned content duration time range. In response to overload or underload status of a server, the server's time range may be adjusted. The time range of other servers in the system may also be adjusted to compensate.