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International Conference on Parallel and Distributed systems (ICPADS)

作者： Pingyi Luo Yanmin Zhu Jia Peng Jiadi Yu Shanghai Key Lab. of Scalable Comput. & Syst. Shanghai China Department of Computer Science and Engineering Shanghai Key Lab of Scalable Computing and Systems Shanghai China

ISBN: (纸本)9781509053827

Crowdsourcing distributed sensing to smartphones has become an appealing paradigm for harnessing the power of the crowd for collecting and sharing information. Market-driven auctions have been recognized as an effective way to matching sensing service demand and supply. A crowdsourcer acts as an auctioneer and smartphone workers act as bidders who are willing to supply sensing services to crowdsourcers. A number of auction mechanisms have been proposed. Unfortunately, most of them assume there is only one crowdsourcer, which is not true in the real world. In this paper, we consider the design of distributed auctions for a crowdsourced sensing market with multiple crowdsourcers and many smartphone workers. We employ a distributed reverse auction that works in a fully distributed fashion. The mechanism requires no one to release its private information. With extensive simulations, we demonstrate that our distributed mechanism achieves the optimal social welfare, and produces better performance than a competing algorithm.

关键词： Conferences

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NoiseSense: A Crowd Sensing System for Urban Noise Mapping Service

NoiseSense: A Crowd Sensing System for Urban Noise Mapping S...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Zhaokun Qin Yanmin Zhu Department of Computer Science and Engineering Shanghai Key Lab of Scalable Computing and Systems Shanghai China

ISBN: (纸本)9781509053827

Noise pollution poses a serious threat to people living in cities today. To alleviate the negative impact of noise pollution, an urban noise mapping can be helpful. In this paper, we present the design of NoiseSense, a crowd sensing system for housing a real-time urban noise mapping service. A major challenge in building such a system is caused by the sparsity problem of the limited noise measurement data from smartphones. To tackle this challenge, we propose a semi-supervised tensor completion algorithm for inferring noise levels for locations without measurements by smartphone users. This algorithm leverages a variety of urban data sources, such as Point of Interests (PoIs), road networks, and check-in data. We implemented the system and developed an APP for smartphone users. We conducted experiments and field study. The experimental results show that the proposed algorithm is superior in inferring noise levels merely with sparse measurements from smartphone users.

关键词： Tensile stress Smart phones Noise measurement Noise level Sensors Roads Algorithm design and analysis

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When remote sensing data meet ubiquitous urban data: Fine-grained air quality inference

When remote sensing data meet ubiquitous urban data: Fine-gr...

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IEEE International Conference on Big Data

作者： Yanan Xu Yanmin Zhu Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Scalable Computing and Systems Shanghai China

ISBN: (纸本)9781467390064

With the growth of the economy, the air quality is becoming a serious issue, especially for those developing countries, such as China. Therefore, it is very important for the public and the government to access real-time air quality information. Unfortunately, the limited number of air quality monitoring stations is unable to provide fine-grained air quality information in a huge city, such as Beijing. One cost-effective approach for obtaining fine-grained air quality information is to infer air quality with those measured data at the monitoring stations. However, existing inference techniques have poor performance because of the extreme data sparsity problem (e.g., only 0.2% data are known). We observe that remote sensing has been a high-quality data source about urban dynamics. In this paper, we propose to integrate remote sensing data and ubiquitous urban data for air quality inference. There are two main challenges, i.e., data heterogeneity and incomplete remote sensing data. In response to the challenges, we propose a two-stage inference approach. In the first stage, we use the AOT remote sensing data and the meteorological data to infer the air quality values with an Artificial Neural Network (ANN). After this stage, we significantly reduce the percentage of empty cells in the tensor representing the spatio-temporal air quality values. In the second stage, we propose a tensor decomposition method to infer the complete set of air quality values. We use the spatial features (i.e., road features and POI features) and the temporal features (i.e., meteorological features) as the constraints in the tensor decomposition process. Experiments with real data sets show that our approach has profound performance advantage over the state-of-the-art methods, such as U-Air.

关键词： Air quality Remote sensing Monitoring Tensile stress Sensors Urban areas Pollution measurement

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A Hybrid Approach Based on Collab.rative Filtering to Recommending Mobile Apps

A Hybrid Approach Based on Collaborative Filtering to Recomm...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Xia Wu Yanmin Zhu Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Scalable Computing and Systems Shanghai China

ISBN: (纸本)9781509053827

With the rapid emergence of mobile devices, smart phones have penetrated into every aspect of people's daily life. The explosive growth of mobile applications makes it difficult for mobile users to find suitable and interesting applications. Mobile app recommendation has been explored by many researchers and some industry solutions are proposed for mobile users. Collab.rative filter (CF) is a popular technique in recommendation system, but it requires explicit feedback data like ratings, which are usually difficult to be collected. Many application markets provide keywords search functions and recommend applications with high download counts. However, downloading an application is a vague indicator of whether the user truly likes that application, as the user may probably uninstall that application immediately after it has been installed. Some other industry solutions involve users' personal data such as social networking, which may result in privacy leaks. In this paper, we propose two hybrid models based on collab.rative filtering to make mobile app recommendations. We leverage RFD (Recency, Frequency, Duration) model to lab.l the preference for users over applications from users' usage data. The first model, namely, improved item-oriented collab.rative filtering (IIOCF), improves the performance of the item-oriented approach by leveraging the latent factor model to discover latent factors among applications. The second model (HLF) is a hybrid model of the latent factor and item-oriented approach. This model sums the predictions of the latent factor model and item-oriented approach, thereby capturing the advantages of both approaches. Our experiment results over 6,568 applications and 25,302 users clearly show that HLF model has better performance than both the item-oriented and latent factor approach.

关键词： Mobile communication Collab.ration Sparse matrices Computational modeling Industries Frequency measurement Filtering

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AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses

AutoBench: Finding Workloads That You Need Using Pluggable H...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Yudi Zheng Andrea Rosà Luca Salucci Yao Li Haiyang Sun Omar Javed Lubomír Bulej Lydia Y. Chen Zhengwei Qi Walter Binder Faculty of Informatics Università della Svizzera italiana (USI) Lugano Switzerland Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China Cloud Server Technologies Group IBM Research Lab Zurich Switzerland

Researchers often rely on benchmarks to demonstrate feasibility or efficiency of their contributions. However, finding the right benchmark suite can be a daunting task - existing benchmark suites may be outdated, known to be flawed, or simply irrelevant for the proposed approach. Creating a proper benchmark suite is challenging, extremely time consuming, and also - unless it becomes widely popular - a thankless endeavor. In this paper, we introduce a novel approach to help researchers find relevant workloads for their experimental evaluation needs. Our approach relies on the huge number of open-source projects availab.e in public repositories, and on unit testing having become best practice in software development. Using a repository crawler employing pluggable static and dynamic analyses for filtering and workload characterization, we allow users to automatically find projects with relevant workloads. Preliminary results presented here show that unit tests can provide a viable source of workloads, and that the combination of static and dynamic analyses improves the ability to identify relevant workloads that can serve as the basis for custom benchmark suites.

关键词： Benchmark testing Open source software Java Libraries Context

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Crowdsourcing sensing to smartphones: A randomized auction approach 23

Crowdsourcing sensing to smartphones: A randomized auction a...

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23rd IEEE International Symposium on Quality of Service, IWQoS 2015

作者： Li, Juan Zhu, Yanmin Hua, Yiqun Yu, Jiadi Shanghai Key Lab of Scalable Computing and Systems Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467371131

Mobile crowdsourcing to smartphones has emerged as a compelling paradigm for collecting sensing data over a vast area for various monitoring applications. It is of paramount importance for mobile crowdsourcing to provide incentive mechanisms. State-of-the-art auction mechanisms for mobile crowdsourcing are deterministic in the sense that given the real costs of the smartphone users, a fixed set of smartphone users are recruited for performing sensing tasks. This leads to serious issues including reduced diversity of sensing devices and starvation of some users. In this paper, we propose an approximate-truthful randomized combinatorial auction mechanism for the social cost minimization problem, which is NP-hard. We design an approximate task allocation algorithm that is near optimal with polynomial-time complexity and use it as a block to construct the whole randomized auction mechanism. We carry out numerical studies and show that our randomized auction mechanism achieves approximate truthfulness, individual rationality, and high computation efficiency. Moreover, the proposed mechanism increases diversity of devices and prevents starvation of some smartphones. © 2015 IEEE.

关键词： Smartphones

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OverUDP: Tunneling Transport Layer Protocols in UDP for P2P Application of IPv4

OverUDP: Tunneling Transport Layer Protocols in UDP for P2P ...

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International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Maziar Janbeglou Nevil Brownlee Shanghai Key Laboratory of Scalable and Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Physical Med. and Rehabilitation Northwestern University Chicago IL USA Max Nader Lab Rehabilitation Institute of Chicago Chicago IL USA

The majority of Internet services today are client-server based, where the server is often designed to be a centralized system that serves many clients. In this model most user credentials and profiles are stored in corporate servers. There have been many security and privacy breaches happening in the latter model that cause a lot of personal identifiable information and private content exposure. The peer-to-peer model was introduced as an alternative to the previous model for some Internet applications such as file sharing in a decentralized system. Current P2P-based solutions suffer from covering all transport layer protocols. In this research, we address these issues and introduce the OverUDP approach that enables all transport layer protocol such as TCP, UDP, ICMP, SCTP, DCCP, RUDP, etc. to be used in P2P model.

关键词： Protocols IP networks Servers Ports (Computers) Virtual private networks Web and internet services

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Crowdsourcing sensing to smartphones: A randomized auction approach

Crowdsourcing sensing to smartphones: A randomized auction a...

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International Workshop on Quality of Service

作者： Juan Li Yanmin Zhu Yiqun Hua Jiadi Yu Shanghai Key Lab of Scalable Computing and Systems Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

关键词： Smart phones Sensors Resource management Crowdsourcing Mobile communication Approximation algorithms Minimization

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Utility-maximizing data collection in crowd sensing: An optimal scheduling approach

Utility-maximizing data collection in crowd sensing: An opti...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Yang Han Yanmin Zhu Jiadi Yu Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Scalable Computing and Systems Shanghai China

Sensing data collection is of great significance in mobile crowd sensing. We consider the problem of online maximization of data utility of the sensing data collected from smartphone users under a time average budget constraint. There are several major challenges, including random and unknown phone contexts, budget constraint and existence of data redundancy. Little work has studied this crucial problem. In this paper we formulate it as an online scheduling problem which determines sensing decisions for smartphones that are distributed over different regions of interest We first propose a centralized online scheduling algorithm based on stochastic optimal control. To address the poor scalab.lity issue of the centralized algorithm, we further propose a distributed online scheduling algorithm based on distributed correlated scheduling. It does not require any priori knowledge of future smartphone contexts, and hence sensing decisions can locally be made by individual smartphones. Rigorous theoretical analysis show that our algorithms can achieve a time average data utility that is within O{1/V) of the theoretical optimum. Extensive simulations demonstrate that our algorithms produce high time average data utility.

关键词： Nickel

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A probabilistic approach to statistical QoS provision of event detection in sensor networks

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Wireless Networks 2015年第2期22卷 439-451页

作者： Yanmin Zhu Lionel M. Ni Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Scalable Computing and Systems Shanghai China Hong Kong University of Science and Technology Hong Kong China

It is of significant importance to provide network-wide Quality of Service (QoS) for a wide range of event detection applications in wireless sensor networks. This paper investigates the important problem of QoS provision to abnormal event detection. For event detection applications, there are two key performance metrics, i.e., detection probability and detection latency. This paper considers both metrics, aiming to provide statistical QoS for abnormal event detection. It is, however, a challenging issue because of stringent resource constraints of sensor nodes and unpredictable randomness of physical events. We propose a probabilistic approach to statistical QoS provision for event detection in sensor networks. We propose a distributed algorithm that iteratively determines the active probability of each sensor node. The probability is kept small for energy efficiency but sufficiently large to provide the required detection QoS. Our approach is flexible and can detection QoS customized by applications. Comprehensive simulation experiments have been conducted, which demonstrate that our approach is able to provide the required detection QoS for event detection and achieves considerably longer the system lifetime compared with other competing schemes.

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