| 12 | 16 | Downtime is the primary factor for estimating the high availability of a system, since any long downtime experience for clients may result in loss of client loyalty and thus revenue loss. Under the Primary-Backup model (Figure 1), there are two types of downtime: I) the time from when the primary host crashes until the VM resumes from the last checkpointed state on the backup host and starts to handle client requests (D,,1,, = T,,3,, - T,,1,,); and II) the time from when the VM pauses on the primary (to save for the checkpoint) until it resumes (D,,2,,). From the [wiki:Publications SSS'10] paper, we observe that for memory-intensive workloads running on guest VMs (such as the highSys workload), [wiki:LLM LLM] endures much longer type I downtime than [http://nss.cs.ubc.ca/remus/ Remus]. This is because, such workloads update the guest memory at high frequency. In contrast, [wiki:LLM LLM] migrates the guest VM image update (mostly from memory) at low frequency, but uses input replay as an auxiliary. Thus, when a failure happens, a significant number of memory updates are needed in order to ensure synchronization between the primary and backup hosts. Therefore, [wiki:LLM LLM] needs significantly more time for the input replay process in order to resume the VM on the backup host and begin handling client requests. |
