Gong Su

A highly available transaction processing system with non-disruptive failure handling

We present a highly available system for environments such as stock trading, where high request rates and low latency requirements dictate that service disruption on the order of seconds in length can be unacceptable. After a node failure, our system avoids delays in processing due to detecting the failure or transferring control to a back-up node. We achieve this by using multiple primary nodes which process transactions concurrently as peers. If a primary node fails, the remaining primaries continue executing without being delayed at all by the failed primary. Nodes agree on a total ordering for processing requests with a novel low overhead wait-free algorithm that utilizes a small amount of shared memory accessible to the nodes and a simple compare-and-swap like protocol which allows the system to progress at the speed of the fastest node. We have implemented our system and show experimentally that it performs well and can transparently handle node failures without causing delays to transaction processing. The efficient implementation of our algorithm for ordering transactions is a critically important factor in achieving good performance.

iBalloon: Efficient VM Memory Balancing as a Service.

Dynamic VM memory management via the balloon driver is a common strategy to manage the memory resources of VMs under changing workloads. However, current approaches rely on kernel instrumentation to estimate the VM working set size, which usually result in high run-time overhead. Thus system administrators have to tradeoff between the estimation accuracy and the system performance. This paper presents iBalloon, a light-weight, accurate and transparent prediction based mechanism to enable more customizable and efficient ballooning policies for rebalancing memory resources among VMs. Experiment results from well known benchmarks such as Dacapo and SPECjvm show that iBalloon is able to quickly react to the VM memory demands, provide up to 54% performance speedup for memory intensive applications running in the VMs, while incurring less than 5% CPU overhead on the host machine as well as the VMs.

MemFlex: A Shared Memory Swapper for High Performance VM Execution

Ballooning is a popular solution for dynamic memory balancing. However, existing solutions may perform poorly in the presence of heavy guest swapping. Furthermore, when the host has sufficient free memory, guest virtual machines (VMs) under memory pressure is not be able to use it in a timely fashion. Even after the guest VM has been recharged with sufficient memory via ballooning, the applications running on the VM are unable to utilize the free memory in guest VM to quickly recover from the severe performance degradation. To address these problems, we present MemFlex , a shared memory swapper for improving guest swapping performance in virtualized environment with three novel features: (1) MemFlex effectively utilizes host idle memory by redirecting the VM swapping traffic to the host-guest shared memory area. (2) MemFlex provides a hybrid memory swapping model, which treats a fast but small shared memory swap partition as the primary swap area whenever it is possible, and smoothly transits to the conventional disk-based VM swapping on demand. (3) Upon ballooned with sufficient VM memory, MemFlex provides a fast swap-in optimization, which enables the VM to proactively swap in the pages from the shared memory using an efficient batch implementation. Instead of relying on costly page faults, this optimization offers just-in-time performance recovery by enabling the memory intensive applications to quickly regain their runtime momentum. Performance evaluation results are presented to demonstrate the effectiveness of MemFlex when compared with existing swapping approaches.

Avoiding disruptive failovers in transaction processing systems with multiple active nodes

We present a highly available system for environments such as stock trading, where high request rates and low latency requirements dictate that service disruption on the order of seconds in length can be unacceptable. After a node failure, our system avoids delays in processing due to detecting the failure or transferring control to a back-up node. We achieve this by using multiple primary nodes which process transactions concurrently as peers. If a primary node fails, the remaining primaries continue executing without being delayed at all by the failed primary. Nodes agree on a total ordering for processing requests with a novel low overhead wait-free algorithm that utilizes a small amount of shared memory accessible to the nodes and a simple compare-and-swap like protocol which allows the system to progress at the speed of the fastest node. We have implemented our system on an IBM z990 zSeries eServer mainframe and show experimentally that our system performs well and can transparently handle node failures without causing delays to transaction processing. The efficient implementation of our algorithm for ordering transactions is a critically important factor in achieving good performance.