205 research outputs found

    MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations

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    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

    Metadata indexing in a structured peer-to-peer network

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 69-77).Peer-to-peer networks require an efficient means for performing searches for files by metadata keywords. Unfortunately, current methods usually sacrifice either scalability or recall. Arpeggio is a peer-to-peer file-sharing network that uses the Chord lookup primitive as a basis for constructing a distributed keyword-set index, augmented with index-side filtering, to address this problem. We introduce index gateways, a technique for minimizing index maintenance overhead. Arpeggio also includes a content distribution system for finding source peers for a file; we present a novel system that uses Chord subrings to track live source peers without the cost of inserting the data itself into the network, and supports postfetching: using information in the index to improve the availability of rare files. The result is a system that provides efficient query operations with the scalability and reliability advantages of full decentralization. We use analysis and simulation results to show that our indexing system has reasonable storage and bandwidth costs, and improves load distribution.by Dan R.K. Ports.M.Eng

    No Provisioned Concurrency: Fast RDMA-codesigned Remote Fork for Serverless Computing

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    Serverless platforms essentially face a tradeoff between container startup time and provisioned concurrency (i.e., cached instances), which is further exaggerated by the frequent need for remote container initialization. This paper presents MITOSIS, an operating system primitive that provides fast remote fork, which exploits a deep codesign of the OS kernel with RDMA. By leveraging the fast remote read capability of RDMA and partial state transfer across serverless containers, MITOSIS bridges the performance gap between local and remote container initialization. MITOSIS is the first to fork over 10,000 new containers from one instance across multiple machines within a second, while allowing the new containers to efficiently transfer the pre-materialized states of the forked one. We have implemented MITOSIS on Linux and integrated it with FN, a popular serverless platform. Under load spikes in real-world serverless workloads, MITOSIS reduces the function tail latency by 89% with orders of magnitude lower memory usage. For serverless workflow that requires state transfer, MITOSIS improves its execution time by 86%.Comment: To appear in OSDI'2

    Self-Optimization of Internet Services with Dynamic Resource Provisioning

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    Self-optimization through dynamic resource provisioning is an appealing approach to tackle load variation in Internet services. It allows to assign or release resources to/from Internet services according to the varying load. However, dynamic resource provisioning raises several challenges among which: (i) How to plan a good capacity of an Internet service, i.e.~a necessary and sufficient amount of resource to handle the Internet service workload, (ii) How to manage both gradual load variation and load peaks in Internet services, (iii) How to prevent system oscillations in presence of potentially concurrent dynamic resource provisioning, and (iv) How to provide generic self-optimization that applies to different Internet services such as e-mail services, streaming servers or e-commerce web systems. This paper precisely answers these questions. It presents the design principles and implementation details of a self-optimization autonomic manager. It describes the results of an experimental evaluation of the self-optimization manager with a realistic e-commerce multi-tier web application running in a Linux cluster of computers. The experimental results show the usefulness of self-optimization in terms of end-user's perceived performance and system's operational costs, with a negligible overhead

    An Analysis of Planarity in Face-Routing

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    In this report we investigate the limits of routing according to left- or right-hand rule (LHR). Using LHR, a node upon receipt of a message will forward to the neighbour that sits next in counter-clockwise order in the network graph. When used to recover from greedy routing failures, LHR guarantees success if implemented over planar graphs. This is often referred to as face or geographic routing. In the current body of knowledge it is known that if planarity is violated then LHR is guaranteed only to eventually return to the point of origin. Our work seeks to understand why a non-planar environment stops LHR from making delivery guarantees. Our investigation begins with an analysis to enumerate all node con gurations that cause intersections. A trace over each con guration reveals that LHR is able to recover from all but a single case, the `umbrella' con guration so named for its appearance. We use this information to propose the Prohibitive Link Detection Protocol (PDLP) that can guarantee delivery over non-planar graphs using standard face-routing techniques. As the name implies, the protocol detects and circumvents the `bad' links that hamper LHR. The goal of this work is to maintain routing guarantees while disturbing the network graph as little as possible. In doing so, a new starting point emerges from which to build rich distributed protocols in the spirit of protocols such as CLDP and GDSTR

    Prohibitive-link Detection and Routing Protocol

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    Abstract In this paper we investigate the limits of routing according to left-or righthand rule (LHR). Using LHR, a node upon receipt of a message will forward to the neighbour that sits next in counter-clockwise order in the network graph. When used to recover from greedy routing failures, LHR guarantees success if implemented over planar graphs. We note, however, that if planarity is violated then LHR is only guaranteed to eventually return to the point of origin. Our work seeks to understand why. An enumeration and analysis of possible intersections leads us to propose the Prohibitive-link Detection and Routing Protocol (PDRP) that can guarantee delivery over non-planar graphs. As the name implies, the protocol detects and circumvents the 'bad' links that hamper LHR. Our implementation of PDRP in TinyOS reveals the same level of service as face-routing protocols despite preserving most intersecting links in the network
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