Adaptive Algorithms for Diagnosing Large-Scale Failures in Computer Networks - 2015


We tend to propose a greedy algorithm, Cluster-MAX-COVERAGE (CMC), to efficiently diagnose large-scale clustered failures. We have a tendency to primarily address the challenge of determining faults with incomplete symptoms. CMC makes novel use of both positive and negative symptoms to output a hypothesis list with a low variety of false negatives and false positives quickly. CMC requires reports from about 0.5 as many nodes as alternative existing algorithms to determine failures with one hundred percent accuracy. Moreover, CMC accomplishes this gain significantly faster (typically by 2 orders of magnitude) than an algorithm that matches its accuracy. When there are fewer positive and negative symptoms at a reporting node, CMC performs a lot of higher than existing algorithms. We have a tendency to conjointly propose an adaptive algorithm known as Adaptive-MAX-COVERAGE (AMC) that performs efficiently during both independent and clustered failures. Throughout a series of failures that embody both independent and clustered, AMC leads to a reduced range of false negatives and false positives.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Partial Computation Offloading and Adaptive Task Scheduling for 5G-enabled Vehicular Networks ABSTRACT: In order to pique the interest of prospective users in the emerging 5G-enabled vehicular networks, a wide
PROJECT TITLE : Millimeter-Wave Mobile Sensing and Environment Mapping Models, Algorithms and Validation ABSTRACT: One relevant research paradigm, particularly at mm-wave and sub-THz bands, is to integrate efficient connectivity,
PROJECT TITLE : Deep Visual Odometry with Adaptive Memory ABSTRACT: A novel deep visual odometry (VO) method that takes into account global information by selecting memory and refining poses is presented here. The currently available
PROJECT TITLE : Data Dissemination in VANETs Using Clustering and Probabilistic Forwarding Based on Adaptive Jumping Multi-Objective Firefly Optimization ABSTRACT: The dissemination of data within a VANETs network calls for
PROJECT TITLE : Adaptive Hierarchical Attention-Enhanced Gated Network Integrating Reviews for Item Recommendation ABSTRACT: There have been a number of very successful studies that have focused on integrating ratings and reviews

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry