Learn More
Flow-based programmable networks must continuously monitor performance metrics, such as link utilization, in order to quickly adapt forwarding rules in response to changes in workload. However, existing monitoring solutions either require special instrumentation of the network or impose significant measurement overhead. In this paper, we propose a(More)
We introduce FlowComb, a network management framework that helps Big Data processing applications, such as Hadoop, achieve high utilization and low data processing times. FlowComb predicts application network transfers, sometimes before they start, by using software agents installed on application servers and while remaining completely transparent to the(More)
—Modern cloud and data center platforms suffer failures and performance degradation from large traffic surges caused by both external (e.g., DDoS attacks) or internal (e.g., workload changes, operator errors, routing misconfigurations) factors. If not mitigated, traffic overload could have significant financial and availability implications for cloud(More)
—Network tomography has been proposed to ascertain internal network performances from end-to-end measurements. In this work, we present priority probing, an optimal probing scheme for unicast network delay tomography that is proven to provide the most accurate estimation. We first demonstrate that the Fisher information matrix in unicast network delay(More)
Multi-tenant data centers are complex environments, running thousands of applications that compete for the same infrastructure resources and whose behavior is guided by (sometimes) divergent configurations. Small workload changes or simple operator tasks may yield unpredictable results and lead to expensive failures and performance degradation. In this(More)
Driven by the large-scale growth of applications deployment in data centers and complicated interactions between service components, automated application dependency discovery becomes essential to daily system management and operation. In this paper, we present ADD, which extracts dependency paths for each application by decomposing the application-layer(More)
An Automatic Fingerprint Recognition system is dependent in many ways on the segmentation of the input fingerprint images because it improves the images so that features can be efficiently extracted from these images by the system. A noisy image tends to give a lot of false features to the feature extraction algorithm, hence segmentation is needed. Gabor(More)
—In the recent years, a progressively growing number of computing and communication services have undertaken the migration from their conventional media to the new unified platform, IP networks. As a consequence, business success of service providers becomes largely determined by the effectiveness of their service management schemes, which require rapid(More)
With the ever-increasing number and complexity of applications deployed in data centers, the underlying network infrastructure can no longer sustain such a trend and exhibits several problems, such as resource fragmentation and low bisection bandwidth. In pursuit of a real-world applicable data center network (DCN) optimization approach that continuously(More)