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Streaming Solutions for Fine-Grained Network Traff
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Online network trafficmeasurements and analysis is critical for detecting and preventing anyreal-time anomalies in the network. We propose, implement, and evaluate anonline, adaptive measurement platform, which utilizes real-time traffic analysisresults to refine subsequent traffic measurements. Central to our solution isthe concept of Multi-Resolution Tiling (MRT), a heuristic approach thatperforms sequential analysis of traffic data to zoom into traffic subregions ofinterest. However, MRT is sensitive to transient traffic spikes. In this paper,we propose three novel traffic streaming algorithms that overcome thelimitations of MRT and can cater to varying degrees of computational andstorage budgets, detection latency, and accuracy of query response. We evaluateour streaming algorithms on a highly parallel and programmable hardware as wellas a traditional software-based platform. The algorithms demonstratesi
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An Overlay-Based Data Mining Architecture Tolerant
4.0
Management scheme for highly scalable big data mininghas not been well studied in spite of the fact that big data mining providesmany valuable and important information for us. An overlay-based parallel datamining architecture, which executes fully distributed data management andprocessing by employing the overlay network, can achieve high scalability. However,the overlay-based parallel mining architecture is not capable of providing datamining services in case of the physical network disruption that is caused byrouter/communication line breakdowns because numerous nodes are removed fromthe overlay network. To cope with this issue, this paper proposes an overlaynetwork construction scheme based on node location in physical network, and a distributedtask allocation scheme using overlay network technology. The numerical analysisindicates that the proposed schemes considerably outperform the conventional scheme
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EAACK SECURE INTRUSION DETECTION SYSTEM FOR MANET
4.0
By
leveraging virtual machine (VM) technology which provides performance and fault
isolation, cloud resources can be
provisioned
on demand in a fine grained, multiplexed manner rather than in monolithic
pieces. By integrating volunteer computing into
cloud
architectures, we envision a gigantic self-organizing cloud (SOC) being formed
to reap the huge potential of untapped commodity
computing
power over the Internet. Toward this new architecture where each participant
may autonomously act as both resource
consumer
and provider, we propose a fully distributed, VM-multiplexing resource
allocation sche
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