Abstract:
Cloud VMs are susceptible to performance issues due to colocated tenants’ unpredictable contention for shared physical resources. In public clouds, provider-centric solutions like careful co-scheduling and VM migration require customer VM profiling, which is impossible.
Such solutions may not know the user’s SLO requirements or application bottlenecks. DIAL, an interference-aware load balancing framework, can be used by cloud users without provider assistance. DIAL infers physical host demand for contended resources, which users cannot see.
Colocated load estimates are used to dynamically shift load away from compromised VMs without violating the application’s tail latency SLOs. DIAL reduces tail latencies by 70% compared to existing solutions for web and online analytical processing applications.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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