We present a new mechanism for detecting shared bottlenecks between end-to-end paths in a network. Our mechanism, which only needs one-way delays from endpoints as an input, is based on the well-known linear algebraic approach: singular value decomposition (SVD). Clusters of flows which share a bottleneck are extracted from SVD results by applying an outlier detection method. Simulations with v...

For complex perceptual tasks that are characterized by object occlusion and non stationarity recognition systems with adaptive signal processing front ends have been developed These systems rely on hand crafted symbolic object models which constitutes a knowledge acquisition bottleneck We propose an approach to automate object model acquisition that relies on the detection of signal processing ...

TCP Sidecar is a network measurement platform for injecting probes transparently into externally generated TCP streams. By coupling measurement probes with nonmeasurement traffic, we are able to obtain measurements behind NATs and firewalls without alerting intrusion detection systems. In this paper, we discuss Sidecar’s design and our deployment experience on PlanetLab. We present preliminary ...

Describing service quality from the end-users' point of view is fulfilled by using Quality of Experience (QoE) metrics. In a networking environment QoE metrics are very close to Quality of Service (QoS), but – because of the subjective nature of QoE – they could not be derived directly from QoS. Collection and analysis of QoS and SLS (Service Level Specification) properties of networking servic...

With the advent and explosive growth of the global Internet adaptive/automatic network intrusion and anomaly detection in wide area data networks is fast gaining critical research and practical importance. In order to detect intrusions in a network, need efficient IDS. Deep packet inspection (DPI) has the ability to inspect both packet headers and payloads to identify the attack signatures in o...

The high-speed data flow network always makes a serious performance bottleneck on intrusion detection system, leading to the detector of parallel intrusion detection system load unevenly. Packets cannot be fast through the detection system, the processing time tends to make the network more congested and packet loss rate surged high. To solve this problem, a dynamic forecast load balancing sche...

Compared to other analytical platforms, comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS) has much increased separation power for analysis of complex samples and thus is increasingly used in metabolomics for biomarker discovery. However, accurate peak detection remains a bottleneck for wide applications of GC×GC-MS. Therefore, the normal-exponential-Bern...

Nearly all existing nanoelectronic sensors are based on charge detection, where molecular binding changes the charge density of the sensor and leads to sensing signal. However, intrinsically slow dynamics of interface-trapped charges and defect-mediated charge-transfer processes significantly limit those sensors' response to tens to hundreds of seconds, which has long been known as a bottleneck...

Because small dual-task costs with ideomotor-compatible tasks do not necessarily indicate the absence of a bottleneck, M.-C. Lien, R. S. McCann, E. Ruthruff, and R. W. Proctor (2005) considered additional sources of evidence regarding bottleneck bypass. This evidence argued against complete bottleneck bypass and, instead, supported an engage-bottleneck-later model in which early bottleneck subs...

Deep neural networks (DNNs) have shown extraordinary performance in recent years for various applications including image classification, object detection, speech recognition, natural language processing, etc. Accuracydriven DNN architectures tend to increase the model sizes and computations at a very fast pace, demanding massive amount of hardware resources. Frequent communication between proc...