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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Han Zhou Jiaming Huang Hongchang Fan Geng Ren Yi Gao Wei Dong Zhejiang Key Lab of Service Robot College of Computer Science Zhejiang University Alibaba Group

With the fast growth of the Internet of Things, people now are surrounded by plenty of devices. To achieve efficient interaction with these devices, human-device interaction technologies are evolving. Because existing methods (mobile App) require users to remember the mapping between the real-world device and the digital one, an important point is to break such a gap. In this paper, we propose VSLink, which offers human-device interaction in an Augmented-Reality-like manner. VSLink achieves fast object identification and pervasive interaction for fusing the physical and cyberspace. To improve processing speed and accuracy, VSLink adopts a two-step object identification method to locate the interaction targets. In VSLink, visual SLAM and object detection neural networks detect stable/-movable objects separately, and detection prior from SLAM is sent to neural networks which enables sparse-convolution-based inference acceleration. VSLink offers a platform where the user could customize the interaction target, function, and interface. We evaluated VSLink in an environment containing multiple objects to interact with. The results showed that it achieves a 33% network inference acceleration on state-of-the-art networks, and enables object identification with 30FPS video input.

关键词： Visualization Simultaneous localization and mapping Neural networks Cyberspace Object detection Sensors Mobile applications

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EdgeMan: Ensuring Real-Time service for Containerized Edge Systems

EdgeMan: Ensuring Real-Time Service for Containerized Edge S...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Wenzhao Zhang Wei Dong Geng Ren Yi Gao Zhejiang Key Lab of Service Robot College of Computer Science Zhejiang University Alibaba-Zhejiang University Joint Institute of Frontier Technologies Alibaba Group

Containers have emerged as a popular technology for edge computing platforms. Although there are varieties of container orchestration frameworks, e.g., Kubernetes to provide high-reliable services for cloud infrastructure, ensuring realtime service at the containerized edge systems (CESs) remains a challenge. In this paper, we propose Edgeman,a holistic edge service management framework for CESs, which consists of (1) a model-assisted event-driven lightweight online scheduling algorithm to provide request-level execution plans; (2) a bottleneck-metric-aware progressive resource allocation mechanism to improve resource efficiency. We then build a testbed that installed three containerized services with different latency sensitivities for concrete evaluation. Besides, we adopt real-world data traces from Alibaba and Twitter for large-scale emulations. Extensive experiments demonstrate that the deadline miss ratio of Edgemanis reduced 85.9% on average compared with existing methods in both industry and academia.

关键词： Industries Sensitivity Job shop scheduling Scheduling algorithms Social networking (online) Emulation Containers

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Horizontal-to-vertical video conversion

arXiv

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arXiv 2021年

作者： Zhu, Tun Zhang, Daoxin Hu, Yao Wang, Tianran Jiang, Xiaolong Zhu, Jianke Li, Jiawei The College of Computer Science Zhejiang University Hangzhou310027 China The Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Company of Alibaba Youku Cognitive and Intelligent Lab

At this blooming age of social media and mobile platform, mass consumers are migrating from horizontal video to vertical contents delivered on hand-held devices. Accordingly, revitalizing the exposure of horizontal video becomes vital and urgent, which is hereby tackled by our automated horizontal-to-vertical (abbreviated as H2V) video conversion framework. Essentially, the H2V framework performs subject-preserving video cropping instantiated in the proposed Rank-SS module. Rank-SS incorporates object detection to discover the candidate subjects, from which we select the primary subject-to-preserve leveraging location, appearance, and salient cues in a convolutional neural network. In addition to converting horizontal videos vertically by cropping around the selected subject, automatic shot detection and multi-object tracking are integrated into the H2V framework to accommodate long and complex videos. To develop H2V systems, we collect an H2V-142K dataset containing 125 videos (132K frames) and 9,500 cover images annotated with primary subject bounding boxes. On H2V-142K and public object detection datasets, our method demonstrates promising results on the subject selection comparing to the related solutions. Furthermore, our H2V framework is industrially deployed hosting millions of daily active users and exhibits favorable H2V conversion performance. By making this dataset as well as our approach publicly available, we wish to pave the way for more horizontal-to-vertical video conversion research. Our collected H2V-142K dataset is available at H2V-142K website. © 2021, CC BY.

关键词： Video signal processing

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Domo: Passive Per-Packet Delay Tomography in Wireless Ad-hoc Networks

Domo: Passive Per-Packet Delay Tomography in Wireless Ad-hoc...

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International Conference on Distributed Computing Systems

作者： Yi Gao Wei Dong Chun Chen Jiajun Bu Tianyu Chen Mingyuan Xia Xue Liu Xianghua Xu Zhejiang University Hangzhou Zhejiang CN Zhejiang Provincial Key Laboratory of Service Robot Zhejiang University China Hangzhou Dianzi University Hangzhou Zhejiang CN School of Computer Science McGill University Canada Zhejiang Provincial Key Lab of Data Storage and Transmission Technology Hangrhou Dianzi University China

In multi-hop wireless ad-hoc networks, packet delivery delay is one of the most important performance metrics. While a lot of research efforts have been spent on measuring and optimizing the end-to-end delay performance, there usually lack accurate and lightweight methods for decomposing the end-to-end delay into the per-hop delay for each packet. Knowledge on the per-hop per-packet delay can greatly improve the network visibility and facilitate network measurement and management. In this paper, we propose Domo, a passive, lightweight and accurate delay tomography approach to decomposing the packet end-to-end delay into each hop. The basic idea is to formulate the problem into a set of optimization problems by carefully considering the constraints among various timing quantities. At the network side, Domo attaches a small overhead to each packet for constructing constraints of the optimization problems. At the PC side, Domo employs semi-definite relaxation and several other methods to efficiently solve the optimization problems. We implement Domo and evaluate its performance extensively using large-scale simulations. Results show that Domo significantly outperforms two existing methods, nearly tripling the accuracy of the state-of-the-art.

关键词： Delays Ad hoc networks Wireless communication Optimization Accuracy Tomography Educational institutions

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Harmonious Hashing

Harmonious Hashing

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Xu, Bin Bu, Jiajun Lin, Yue Chen, Chun He, Xiaofei Cai, Deng Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University China State Key Lab of CAD and CG College of Computer Science Zhejiang University China

ISBN: (纸本)9781577356332

Hashing-based fast nearest neighbor search technique has attracted great attention in both research and industry areas recently. Many existing hashing approaches encode data with projection-based hash functions and represent each projected dimension by 1-bit. However, the dimensions with high variance hold large energy or information of data but treated equivalently as dimensions with low variance, which leads to a serious information loss. In this paper, we introduce a novel hashing algorithm called Harmonious Hashing which aims at learning hash functions with low information loss. Specifically, we learn a set of optimized projections to preserve the maximum cumulative energy and meet the constraint of equivalent variance on each dimension as much as possible. In this way, we could minimize the information loss after binarization. Despite the extreme simplicity, our method outperforms superiorly to many state-of-the-art hashing methods in large-scale and high-dimensional nearest neighbor search experiments.

关键词： Hash functions

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Whom to mention: Expand the diffusion of tweets by @ recommendation on micro-blogging systems

Whom to mention: Expand the diffusion of tweets by @ recomme...

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22nd International Conference on World Wide Web, WWW 2013

作者： Wang, Beidou Wang, Can Bu, Jiajun Chen, Chun Zhang, Wei Vivian Cai, Deng He, Xiaofei Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University China Microsoft Corporation Redmond WA United States State Key Lab of CAD and CG College of Computer Science Zhejiang University China

ISBN: (纸本)9781450320351

Nowadays, micro-blogging systems like Twitter have become one of the most important ways for information sharing. In Twitter, a user posts a message (tweet) and the others can forward the message (retweet). Mention is a new feature in micro-blogging systems. By mentioning users in a tweet, they will receive notifications and their possible retweets may help to initiate large cascade diffusion of the tweet. To enhance a tweet's diffusion by finding the right persons to mention, we propose in this paper a novel recommendation scheme named as whom-to-mention. Specifically, we present an in-depth study of mention mechanism and propose a recommendation scheme to solve the essential question of whom to mention in a tweet. In this paper, whom-to-mention is formulated as a ranking problem and we try to address several new challenges which are not well studied in the traditional information retrieval tasks. By adopting features including user interest match, content-dependent user relationship and user influence, a machine learned ranking function is trained based on newly defined information diffusion based relevance. The extensive evaluation using data gathered from real users demonstrates the advantage of our proposed algorithm compared with the traditional recommendation methods. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

关键词： Social networking (online)

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D2: Anomaly Detection and Diagnosis in Networked Embedded Systems by Program Profiling and Symptom Mining

D2: Anomaly Detection and Diagnosis in Networked Embedded Sy...

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Real-Time Systems Symposium (RTSS)

作者： Wei Dong Chun Chen Jiajun Bu Xue Liu Yunhao Liu Zhejiang Provincial Key Laboratory of Service Robot Zhejiang University China School of Computer Science McGill University Canada MOE Key Lab for Information System Security Tsinghua University China

Detecting and diagnosing anomalies in networked embedded systems like sensor networks is a very difficult task, due to the variable workloads and severe resource constraints. We notice that most node-level debugging tools can provide detailed program information inside the node but fail to detect when and where a problem occurs in the network. On the other hand, most network-level diagnosis tools can effectively detect a problem from the network but fail to narrow down the problem within the node because they lack detailed program information. To close the gap, we propose D2, a new anomaly detection and diagnosis method by combining program profiling and symptom mining. D2 employs binary instrumentation to perform lightweight function count profiling. Based on the statistics, D2 uses PCA (Principal Component Analysis) based approach for automatically detecting network anomalies. Compared to previous methods, D2 is able to point programmers closer to the most likely causes by a novel approach combining statistical tests and program call graph analysis. We implement our method based on TinyOS 2.1.1 and evaluate its effectiveness by case studies in the development of a working sensor network. Results show that our method is effective for detecting and diagnosing problems in real-world sensor network systems, and at the same time, incurs an acceptable overhead.

关键词： Instruments Principal component analysis Software Radiation detectors Educational institutions Debugging Random access memory

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Whom to Mention: Expand the Diffusion of Tweets by @ Recommendation on Micro-blogging Systems 13

Whom to Mention: Expand the Diffusion of Tweets by @ Recomme...

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International Conference on World Wide Web

作者： Beidou Wang Can Wang Jiajun Bu Chun Chen Wei Vivian Zhang Deng Cai Xiaofei He Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University China Microsoft Corporation Redmond WA USA State Key Lab of CAD&CG College of Computer Science Zhejiang University China

ISBN: (纸本)9781450324441

关键词： Micro-blogging Systems Twitter Mention Recommendation Information Diffusion Information Retrieval

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Reprogramming over Low Power Link Layer in Wireless Sensor Networks

Reprogramming over Low Power Link Layer in Wireless Sensor N...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Yi Gao Chun Chen Xue Liu Jiajun Bu Wei Dong Xianghua Xu College of Computer Science Zhejiang Provincial Key Lab of Service Robot McGill University School of Computer Science Hangzhou Dianzi University School of Computer Science

Reprogramming over the air is important for maintaining a wireless sensor network. Traditional reprogramming approaches assume always-on link layers. Given the energy limitation of sensor nodes, always-on link layers are often not desired for most sensor network applications. In this paper, we propose ROLP, a novel reprogramming protocol built on a widely used low power link layer in wireless sensor networks. ROLP employs an efficient control packets self-suppression scheme for reliable data transmission. ROLP also employs an adaptively falling asleep scheme based on the neighbor information to reduce the energy consumption. We implement ROLP based on TinyOS and evaluate its performance in two different indoor networks. Compared with the standard reprogramming protocol in TinyOS, ROLP is able to reduce the radio-on time by 57.6% and 39.0% in the two networks. Since radio operations cost most of the energy, these reductions save significant amount of energy and prolong the lifetime of a wireless sensor network.

关键词： Receivers Protocols Data communication Wireless sensor networks Reliability Educational institutions Mathematical model

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A bregman divergence optimization framework for ranking on data manifold and its new extensions 26

A bregman divergence optimization framework for ranking on d...

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26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12

作者： Xu, Bin Bu, Jiajun Chen, Chun Cai, Deng Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China State Key Lab of CADandCG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781577355687

Recently, graph-based ranking algorithms have received considerable interests in machine learning, computer vision and information retrieval communities. Ranking on data manifold (or manifold ranking, MR) is one of the representative approaches. One of the limitations of manifold ranking is its high computational complexity (O(n3), where n is the number of samples in database). In this paper, we cast the manifold ranking into a Bregman divergence optimization framework under which we transform the original MR to an equivalent optimal kernel matrix learning problem. With this new formulation, two effective and efficient extensions are proposed to enhance the ranking performance. Extensive experimental results on two real world image databases show the effectiveness of the proposed approach. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Graphic methods

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