P4DNS: In-Network DNS

In network computing offers an appealing scalability trajectory for network services, as application performance scales with network devices. Despite its potential, in-network computing may not be suitable for all applications, both due to paradigm assumptions and network-device limitations. As the users' demands from the Internet keep growing, any limitations on the scalability of network services such as DNS limits the scalability of end-to-end experience. In this paper we present P4DNS, an in-network DNS solution, exploring the span and limitations of implementing a realistic network service within a network device. P4DNS is a high performance DNS server, implemented in P4->NetFPGA and providing performance improvement compared with software-based solutions. We discuss the limitations of implementing in-network services using today's paradigms and the trade-offs between data and control planesLeverhulme Trust Isaac Newton Trus

MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations

Camera orientations (i.e., rotation and zoom) govern the content that a camera captures in a given scene, which in turn heavily influences the accuracy of live video analytics pipelines. However, existing analytics approaches leave this crucial adaptation knob untouched, instead opting to only alter the way that captured images from fixed orientations are encoded, streamed, and analyzed. We present MadEye, a camera-server system that automatically and continually adapts orientations to maximize accuracy for the workload and resource constraints at hand. To realize this using commodity pan-tilt-zoom (PTZ) cameras, MadEye embeds (1) a search algorithm that rapidly explores the massive space of orientations to identify a fruitful subset at each time, and (2) a novel knowledge distillation strategy to efficiently (with only camera resources) select the ones that maximize workload accuracy. Experiments on diverse workloads show that MadEye boosts accuracy by 2.9-25.7% for the same resource usage, or achieves the same accuracy with 2-3.7x lower resource costs.Comment: 19 pages, 16 figure

Acoustic and mechanical properties of luffa fiber-reinforced biocomposites

This chapter presents an overview of acoustic and mechanical behaviors of luffa fiber reinforced biocomposites. A growing number of studies are examining the composites of biodegradable fibers such as flax, hemp, kenaf and luffa due to the adverse effects of chemical materials on nature. The low cost and superior acoustic and acceptable mechanical properties of biocomposites make them very attractive for practical applications such as sound and vibration isolation. However, the acoustic and mechanical characteristics of biocomposites and their dynamic behaviors should be fully determined before considering them for practical applications. In this chapter, acoustic properties, such as sound absorption and transmission loss, and mechanical properties, such as damping and elasticity of luffa fiber reinforced composites, are presented. The variations in acoustic and mechanical properties due to different samples and manufacturing process are explored.WOS:000532438200017Scopus - Affiliation ID: 60105072Book Citation Index- ScienceArticle; Book ChapterOcak2019YÖK - 2018-1