Virtual Server Cluster Load Distribution and Power Management
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Solution Overview
Problem
Conventional server cluster load distribution and power management methods are inefficient, as they either fail to optimize power usage or compromise service performance, especially in cloud computing environments with virtualized servers, where physical and virtual machines differ significantly in resource allocation and consumption.
Innovation Solution
A device and method that monitor load distribution conditions and dynamic states of server nodes, using a monitoring unit, server node information storage, and policy determination units to control server nodes' active or inactive states based on load distribution and power management policies, optimizing the number of active servers and prioritizing their activation or deactivation to balance service performance and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If servers are kept in active state to handle service requests, then service response performance is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts server power states based on real-time load conditions. The load distributor monitors service request loads and converts servers between active and low power states according to current demand, rather than maintaining fixed states. This dynamic adaptation allows the system to optimize power consumption while ensuring sufficient active servers are available to meet service performance requirements.
Solution Approach 2:
The system changes the operational parameter (power state) of servers based on load conditions. When service request load is low, servers are converted to low power state; when load increases, servers are activated. This parameter change strategy enables the system to balance power consumption against service response performance by adjusting server states in response to varying operational conditions.
2Productivity
If load distribution is designed for maximum service request load, then service capacity is improved, but power consumption increases due to unnecessary servers standing by in active state
Solution Approach 1:
The load distribution system transitions from a static design (servers always active for maximum load) to a dynamic design where server activation is adjusted based on current load conditions. The load distributor continuously monitors service request loads and activates or deactivates servers accordingly, ensuring sufficient service capacity while avoiding unnecessary power consumption from idle active servers.
Solution Approach 2:
The system prepares servers for potential high load conditions by maintaining a pool of servers that can be quickly activated, rather than keeping all servers permanently active. When maximum load is anticipated or occurs, the system can rapidly activate additional servers from low power state, providing the necessary service capacity without continuous power consumption.
3Use of energy by stationary object
If time-based scheduling is used for power management, then power consumption is reduced, but service performance deteriorates when situations differ from manager's experience
Solution Approach 1:
The system implements feedback mechanisms where the load distributor continuously monitors actual service request loads and server performance metrics. This real-time feedback allows the system to adjust server activation decisions based on current conditions rather than relying solely on pre-defined schedules or manager experience, ensuring service performance requirements are met while optimizing power consumption.
Solution Approach 2:
The load distribution system autonomously monitors load conditions and makes decisions about server activation and deactivation without requiring manual intervention or relying entirely on pre-programmed schedules. The system serves itself by automatically adjusting its configuration based on real-time monitoring of service request patterns and server performance, adapting to situations that differ from historical experience.
Data Source
AI summary
A device for distributing a load and managing power of a virtual server cluster includes a monitoring unit configured to monitor a load distribution condition on server nodes included in a server cluster and a dynamic state of each of the server nodes, a server node information storage unit configured to store static state information of each of the server nodes, a policy determination unit configured to determine a load distribution policy and a power management policy for each of the server nodes using monitoring information and the static state information stored in the server node information storage unit, and a controller configured to control conversion of each of the server nodes into an active state or an inactive state according to the power management policy, and distribution of a load of a service request requested by a service client to activated server nodes according to the load distribution policy.