Physical Sciences and Mathematics Commons^™

Interpretable Learning In Multivariate Big Data Analysis For Network Monitoring, José Camacho, Rasmus Bro, David Kotz

Dartmouth Scholarship

There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it cannot be interpreted by a human operator. In this paper, we present an extension of the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool. In this extension, we propose a solution to the automatic derivation of features, a cornerstone step for the application of MBDA when the amount of data is massive. The resulting network monitoring approach allows …

---

Go to article

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

Three Power-Aware Routing Algorithms For Sensor Networks, Javed Aslam, Qun Li, Daniela Rus

Dartmouth Scholarship

This paper discusses online power‐aware routing in large wireless ad hoc networks (especially sensor networks) for applications in which the message sequence is not known. We seek to optimize the lifetime of the network. We show that online power‐aware routing does not have a constant competitive ratio to the off‐line optimal algorithm. We develop an approximation algorithm called max–min zP_min that has a good empirical competitive ratio. To ensure scalability, we introduce a second online algorithm for power‐aware routing. This hierarchical algorithm is called zone‐based routing. Our experiments show that its performance is quite good. Finally, we …