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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Lu Fang Tong Liu Yanmin Zhu Yuanyuan Yang School of Computer Engineering and Science Shanghai University Shanghai Engineering Research Center of Intelligent Computing System Shanghai Key Lab of Scalable Computing and Systems Stony Brook University

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

Multi-access Edge computing (MEC) comes forth as a promising computing paradigm to meet the low-delay requirements of computation-intensive applications. In this work, we focus on the task offloading and dispatching problem in MEC, where mobile devices (MDs) can decide to execute tasks locally or offload them to access points (APs), and each AP can dispatch its received tasks to other APs. Specially, we consider both APs and MDs are selfish, which aim to minimize their respective task completion delay. The problem is particularly difficult, as there exists computing resource competition among MDs and APs, respectively. Furthermore, the offloading decisions made by MDs and the dispatching decisions made by APs are interactive. To overcome the challenges, we first formulate the problem as a multi-leader multi-follower Stackelberg game, and rigorously prove the existence of a Stackelberg equilibrium. Then, we propose an efficient approach to achieve a Stackelberg equilibrium, which includes a Q-learning based offloading strategy for MDs and a best response based dispatching strategy for APs. We also demonstrate an upper bound of the total completion delay achieved by our approach with a constant approximation ratio. Extensive simulations are also conducted to show the performance of our approach, compared with baselines.

关键词： Upper bound Simulation Games Dispatching Mobile handsets Delays Task analysis

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Accuracy-Guaranteed Event Detection via Collaborative Mobile Crowdsensing with Unreliable Users 15th

Accuracy-Guaranteed Event Detection via Collaborative Mobile...

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15th EAI International Conference on Collaborative computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Liu, Tong Wu, Wenbin Zhu, Yanmin Tong, Weiqin School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China 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)9783030301453

Recently, mobile crowdsensing has become a promising paradigm to collect rich spatial sensing data, by taking advantage of widely distributed sensing devices like smartphones. Based on sensing data, event detection can be conducted in urban areas, to monitor abnormal incidents like traffic jam. However, how to guarantee the detection accuracy is still an open issue, especially when unreliable users who may report wrong observations are considered. In this work, we focus on the problem of user recruitment in collaborative mobile crowdsensing, aiming to optimize the fine-grained detection accuracy in a large urban area. Unfortunately, the problem is proved to be NP-hard, which means there is no polynomial-time algorithm to achieve the optimal solution unless P NP. To meet the challenge, we first employ a probabilistic model to characterize the unreliability of users, and measure the uncertainty of inferring event occurrences given collected observations by Shannon entropy. Then, by leveraging the properties of adaptive monotonicity and adaptive submodularity, we propose an adaptive greedy algorithm for user recruitment, which is theoretically proved to achieve a constant approximation ratio guarantee. Extensive simulations are conducted, which show our proposed algorithm outperforms baselines under different settings. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Polynomial approximation

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Improved impossible differential cryptanalysis of large-block Rijndael

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Science China(Information Sciences) 2019年第3期62卷 5-18页

作者： Ya LIU Yifan SHI Dawu GU Bo DAI Fengyu ZHAO Wei LI Zhiqiang LIU Zhiqiang ZENG Engineering Research Center of Optical Instrument and System Ministry of Education Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University School of Computer Science and Technology Donghua University Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Science and Technology on Information Assurance Laboratory

Rijndael is a substitution-permutation network（SPN） block cipher for the AES development process. Its block and key sizes range from 128 to 256 bits in steps of 32 bits, which can be denoted by Rijndael-b-k, where b and k are the block and key sizes, respectively. Among them, Rijndael-128-128/192/256,that is, AES, has been studied by many researchers, and the security of other large-block versions of Rijndael has been exploited less frequently. However, more attention has been paid to large-block versions of block ciphers with the fast development of quantum computers. In this paper, we propose improved impossible differential attacks on 10-round Rijndael-256-256, 10-round Rijndael-224-256, and 9-round Rijndael-224-224 using precomputation tables, redundancies of key schedules, and multiple impossible differentials. For 10-round Rijndael-256-256, the data, time, and memory complexities of our attack were approximately 2244.4chosen plaintexts, 2240.1encryptions, and 2181.4blocks, respectively. For 10-round Rijndael-224-256, the data, time, and memory complexities of our attack were approximately 2214.4chosen plaintexts, 2241.3encryptions, and 2183.4blocks, respectively. For 9-round Rijndael-224-224, the data, time, and memory complexities of our attack are approximately 2214.4chosen plaintexts, 2113.4encryptions, and 287.4blocks,respectively, or 2206.6chosen plaintexts, 2153.6encryptions, and 2111.6blocks, respectively. To the best of our knowledge, our results are currently the best on Rijndael-256-256 and Rijndael-224-224/256.

关键词： block cipher Rijndael precomputation tables impossible di?erentials multiple impossible differential attacks

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Espresso: Brewing Java for More Non-Volatility with Non-volatile Memory

arXiv

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arXiv 2017年

作者： Wu, Mingyu Zhao, Ziming Li, Haoyu Li, Heting Chen, Haibo Zang, Binyu Guan, Haibing Shanghai Key Lab. of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University

Fast, byte-addressable non-volatile memory (NVM) em-braces both near-DRAM latency and disk-like persistence, which has generated considerable interests to revolutionize system software stack and programming models. However, it is less understood how NVM can be combined with managed runtime like Java virtual machine (JVM) to ease persistence management. This paper proposes Espresso1, a holistic ex-tension to Java and its runtime, to enable Java programmers to exploit NVM for persistence management with high perfor-mance. Espresso first provides a general persistent heap de-sign called Persistent Java Heap (PJH) to manage persistent data as normal Java objects. The heap is then strengthened with a recoverable mechanism to provide crash consistency for heap metadata. It then provides a new abstraction called Persistent Java Object (PJO) to provide an easy-to-use but safe persistent programming model for programmers to per-sist application data. The evaluation confirms that Espresso significantly outperforms state-of-art NVM support for Java (i.e., JPA and PCJ) while being compatible to existing data structures in Java programs. Copyright © 2017, The Authors. All rights reserved.

关键词： Nonvolatile storage

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Accelerating Traditional File systems on Non-volatile Main Memory

Accelerating Traditional File Systems on Non-volatile Main M...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Weitong Jin Yanmin Zhu Linpeng Huang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai Key Lab of Scalable Computing and Systems

ISBN: (纸本)9781538632086

New non-volatile memory (NVM) technologies, e.g., Phase Change Memory (PCM), are emerging with main features such as byte addressability, cheapness and large size, and will be deployed to serve as main memory. For fast processing of big data, block device drivers have been developed for NVM such that traditional file systems (e.g., EXT4) operated on non-volatile main memory. However, the existing block driver blindly caches pages, which incurs unnecessary access delays. To overcome this drawback, this paper develops a novel block device driver, called NVMBD, for byte-addressable non-volatile main memory. It adopts two methods of processing block I/O requests, i.e., traditional block I/O and BMAP. On the one hand, traditional block I/O reads/writes 512B sectors with multiple load/store instructions. On the other hand, BMAP inserts NVM pages into the page cache tree when processing block I/O requests, which removes the page movement between the page cache and the NVM. BMAP involves in the management of page cache, but it is transparent to file systems. BMAP provides file systems with the DAX-like feature, improving the file system performance. Through comprehensive experiments, we demonstrate that the developed block device driver significantly improves the file access performance.

关键词： Nonvolatile memory Performance evaluation Random access memory Device drivers Kernel System performance

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Topology and survivability analysis for flight flow networks: Case studies of three China airline companies 11

Topology and survivability analysis for flight flow networks...

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11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017

作者： Gao, Xiaofeng Dang, Yaru Chen, Guihai Gu, Jian Wang, Yongjian Shanghai Key Lab of Scalable Computing and Systems Dept. of Computer Science Shanghai Jiao Tong University Shanghai China Civil Aviation SandT Educational Evaluation Research Center Civil Aviation University of China Tianjin China Key Laboratory of Information Network Security Ministry of Public Security Third Research Institute of Ministry of Public Security Shanghai China

ISBN: (纸本)9781450348881

In this paper we study the survivability feature of airline networks. To measure survivability, we comprehensively consider the network structure measures such as degree distribution, average path length, clustering coefficient, and density;the centrality metrics such as degree centrality and betweenness centrality;as well as the connectivity measures such as maximum connected subgraph size and overall efficiency. Taking three listed China airline companies as examples, namely Air China, China Southern Airlines, and China Eastern Airlines, we provide mass number of simulations to test the survivability of the three companies under random attacks and malicious attacks. The results depict the scalefree features of such networks without small-world characteristics, while the attack simulations reflect the survivability of airline networks clearly. To the best of our knowledge, we are the first to provide case studies for airline networks of individual airline companies in China, which has both theoretical and practical significance in related areas. © 2017 ACM.

关键词： Complex networks

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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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Multiple influence maximization in social networks 10

Multiple influence maximization in social networks

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10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016

作者： Sun, Honglin Gao, Xiaofeng Chen, Guihai Gu, Jian Wang, Yongjian Shanghai Key Lab. of Scalable Computing and Systems Dept. of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of Information Network Security of Ministry of Public Security Third Research Institute of Ministry of Public Security Shanghai China

ISBN: (纸本)9781450341424

Influence Maximization, a technique of social analysis to help marketers select a small group of users to promote their products with the goal of maximizing their influence spread, has been studied for a long time. However, previous researches did not consider the scenario that a company may intend to promote serval kinds of products in the same social network, where each user has different preferences for different categories. Considering this scenario in this paper, we propose the Multiple Influence Maximization (MIM) problem based on the assumption that one seed user can accept serval kinds of goods for free, and at the same time non-seed users have enough purchasing power to accept different promotions from their social friends. To address this issue, we design the corresponding greedy algorithm framework with an approximate radio of 1-1/e if the influence function is submodular. Besides, to simplify the computation of influence spread and considering the properties of real social influence propagation, we propose a novel influence quantitative computation model in which influence function fortunately is submodular. Applying this model into our MIM problem, the experiment results show that the greedy algorithm out-performs serval traditional heuristics in influence spread without loss of performance. © 2015 ACM.

关键词： Method of moments

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A Distributed Auction Approach to Crowdsourced Sensing over Smartphones

A Distributed Auction Approach to Crowdsourced Sensing over ...

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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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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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