Cold-Start Service Placement for Time-Varying Cloud Demand
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Solution Overview
Problem
Existing technologies struggle to efficiently manage resource allocation for cloud-based applications with varying performance requirements over time, leading to performance inefficiencies and increased costs due to oversizing or under-sizing of cloud resources.
Innovation Solution
A method for cold-start service placement over on-demand resources involves jointly scheduling computing nodes and service incarnations to meet performance requirements while minimizing costs, considering varying resource demands and node capacities, using a dual scheduling process that accounts for node and incarnation costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud resources are oversized to meet peak performance requirements, then performance requirements are satisfied, but resource waste and costs increase
Solution Approach 1:
The system dynamically adjusts cloud resource allocation by creating multiple service incarnations with different resource requirements and scheduling them based on time-varying performance requirements. This allows the system to adapt resource usage to actual demand rather than maintaining static oversized resources, resolving the contradiction between meeting performance requirements and avoiding resource waste.
Solution Approach 2:
The service is divided into multiple service incarnations, each with specific resource requirements and performance levels. By segmenting the service and selectively scheduling different incarnations based on current performance needs, the system can satisfy performance requirements without allocating excessive resources continuously, thus reducing resource waste while maintaining reliability.
2Loss of energy
If cloud resources are undersized to reduce costs, then resource waste decreases, but performance requirements are not met and downtime increases
Solution Approach 1:
The system performs preliminary scheduling of service incarnations based on predicted performance requirements. By pre-planning which service incarnations to execute and when, the system ensures that adequate resources are allocated in advance to meet performance requirements, preventing downtime while optimizing resource costs through careful advance planning rather than continuous oversizing.
3Adaptability or versatility
If multiple service incarnations are scheduled to meet varying performance requirements, then performance flexibility improves, but scheduling complexity increases
Solution Approach 1:
The system manages scheduling complexity by focusing on key parameter changes - specifically, the performance requirements profile and resource capacities - rather than attempting to optimize all possible scheduling variables. Service incarnations are selected and scheduled based on these changing parameters, providing performance flexibility while keeping the scheduling mechanism manageable through parameter-driven decision making.
Data Source
AI summary
Methods, systems, and computer program products for cold-start service placement over on-demand resources are provided herein. A computer-implemented method includes obtaining a performance requirement profile comprising performance requirements of a service that vary over time; determining a plurality of incarnations for the service, wherein each incarnation is associated with a level of performance provided by the incarnation for the service, resource requirements of the incarnation, and a type of computing node the incarnation is configured to execute on; identifying computing nodes having different types and different resource capacities; jointly scheduling (i) the computing nodes and (ii) one or more of the incarnations on the computing nodes over a time interval such that a cumulative level of performance of the incarnations scheduled at each timepoint in the time interval satisfies the performance requirement profile of the service.