Abstract-Geographically dispersed deployments of large and complex multitier enterprise applications introduce many challenges, including those involved in predicting the impact of network latency on end-to-end transaction response times. Here, a measurement-based approach to quantifying this impact using a new metric called the link gradient is presented. A non-intrusive technique for measuring the link gradient in running systems using delay injection and spectral analysis is presented, along with experimental results on PlanetLab that demonstrate that the link gradient can be used to predict end-to-end responsiveness, even in new and untested application configurations. The emergence of a global network infrastructure, innetwork services such as cloud computing, and software paradigms such as service-oriented architectures (SOAs) has led to applications that are geographically distributed across data centers around the world. While offering many benefits, such distributed applications introduce significant challenges, not the least of which is the management of end-to-end responsiveness in a highly dynamic environment. In fact, even quantifying the effects of changing network characteristics on end-to-end performance is not easy. For a given deployment of a multitier enterprise application, for example, this relationship depends both on application factors such as execution logic, workloads, configuration settings, and transaction types, and on network factors such as latency, bandwidth, and loss rate. Here, we focus on the impact of logical link latency-that is, the network latency from one application component to another, possibly across multiple physical links-on the endto-end performance of application transactions in multitier applications. While this link latency, as noted above, is not the only factor, it is a significant element in many kinds of distributed applications, especially those deployed across wide geographical areas, as enterprise applications or crossenterprise SOAs often are (e.g., [3] , [9] ). Our specific goal is to be able to predict accurately the impact of changes in logical link latencies on transaction performance, such as might occur when a distributed application is reconfigured (e.g., a component is moved) or when network routes change. To illustrate the difficulty of this task, consider a 3-tier deployment of the RUBiS web service benchmark [8] on
Link Gradients REF predicts the impact of network latency in multi-tier systems by doing delay injection and performing spectral analysis.
Link Gradients: Predicting the Impact of Network Latency on Multitier Applications
IEEE INFOCOM 2009
IEEE INFOCOM 2009
Computer Science