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检索条件"机构=Services Computing Technology and System Lab"

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Concurrent Transmission Method for Mobile Applications using Multihoming Devices

Concurrent Transmission Method for Mobile Applications using...

引用

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

作者： Feng Lu Zirui Wang Xiaofei Liao Hai Jin Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781479934300

Mobile devices with multihoming capabilities have gained large-scale popularity in recent years. However, these network interfaces cannot be fully utilized in most applications. In this paper, we propose a concurrent transmission method that allows mobile applications to fully use multiple interfaces simultaneously in a transparent manner. Using this method, applications benefit from network enhancement, including minimum transmission delay and maximum throughput. Our experimental results show that we achieve a bandwidth aggregation efficiency of 90% on throughput and reduce 28% transmission delay. In addition, we analyze the lowest power consumption according to our model.

关键词： Delays Network interfaces Radio frequency Data communication Throughput Bandwidth Protocols

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SoMed: A Hybrid DHT Framework towards Scalable Decentralized Microblogging services

SoMed: A Hybrid DHT Framework towards Scalable Decentralized...

引用

International Conference on Parallel and Distributed systems (ICPADS)

作者： Jinzhou Huang Hai Jin Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

Microblogging services have experienced unprecedented growth. They serve more as news media outlets than online social networks, which can predict the H1N1 virus emergency, detect earthquakes, and live major events. These kinds of burst events will cause peak access. Servers will suffer from large amount of concurrent access and lead to single point of failures. Furthermore, divergent behaviors of two categories of users, social users and media users, will lead to asymmetric workloads. For some media users, such as Lady Gaga, who accounts for over 20 million followers, will generate a huge amount of traffic and make the centralized mechanism hard to scale. To address these problems together, we present SoMed, a hybrid DHT framework towards scalable, decentralized microblogging services. We also conduct a simulation with real traces of Twitter. The results show significantly bandwidth saving and response time reducing with high reliability and availability.

关键词： Media Peer-to-peer computing Twitter Bandwidth Routing Servers

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MomentSA: A Fast and Accurate Method for Stochastic Kronecker Graph Parameter computing

MomentSA: A Fast and Accurate Method for Stochastic Kronecke...

引用

International Conference on Computer Supported Cooperative Work in Design

作者： Yongqiang Li Zhiyuan Shao Hong Huang Yinuo Li Hai Jin Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781538614839

Stochastic Kronecker Graph model is widely used to generate synthetic graphs that simulate real-world graphs. In this model, the initiator matrix decides the degree to which the synthetic graph approximates the real-world graph. The computing of initiator matrix, however, requires that the number of the nodes of input graph is the power of the dimension of the initiator matrix. In order to fulfill such requirement, some methods (e.g., KronFit and Moment) add isolated nodes to the input graph, which damages the input graph's properties. Other method (e.g., KronEM) predicts the links between the nodes after adding isolated nodes. Unfortunately, the prediction dramatically increases the complexity of computing. In this paper, we propose a method named as MomentSA to solve the problems. Our method completes the input graphs by leveraging the law of property changes of graphs, which does not need to predict the links as method KronEM. Simultaneously, our method uses the moment-based estimation and ADAM (Adaptive Moment Estimation) method to compute the initiator matrix, which can compute the initiator matrix quickly. Experiment results on our prototype implementation suggest that the initiator matrix computed from our method is more accurate than existing state-of-art systems, and the speed of computing is about three to four orders of magnitude faster than state-of-art systems.

关键词： Maximum likelihood estimation Stochastic processes Computational modeling Complexity theory Prototypes Data models

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Efficient and Progressive Algorithms for Distributed Skyline Queries over Uncertain Data

Efficient and Progressive Algorithms for Distributed Skyline...

引用

IEEE International Conference on Distributed computing systems

作者： Xiaofeng Ding Hai Jin Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781424472611;9780769540597

The skyline operator has received considerable attention from the database community, due to its importance in many applications including multi-criteria decision making, preference answering, and so forth. In many applications where uncertain data a re inherently exist, i.e., data collected from different sources in distributed locations are usually with imprecise measurements, and thus exhibit kind of uncertainty. Taking into account the network delay and economic cost associated with sharing and communicating large amounts of distributed data over an internet, an important problem in this scenario is to retrieve the global skyline tuples from all the distributed local sites with minimum communication cost. Based on the well known notation of the probabilistic skyline query over centralized uncertain data, in this paper, for the first time, we propose the notation of distributed skyline queries over uncertain data. Furthermore, two communication- and computation-efficient algorithms are proposed to retrieve the qualified skylines from distributed local sites. Extensive experiments have been conducted to verify the efficiency and the effectiveness of our algorithms with both the synthetic and real data sets.

关键词： Plant uncertain Distribute network delay Uncertainty algorithms

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SKVM: Scaling In-Memory Key-Value Store on Multicore

SKVM: Scaling In-Memory Key-Value Store on Multicore

引用

IEEE Symposium on Computers and Communication

作者： Ran Zheng Wenjin Wang Hai Jin Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781467371957

SKVM is a high performance in-memory Key-Value (KV) store for multicore, which is designed for high concurrent data access. There are some problems of existing systems dealing with high concurrent data processing on multicore: lock competition, cache coherency overhead, and large numbers of concurrent network connections. To solve the problems and make the in-memory KV store scale well on multicore, high concurrent data access is divided into two steps: high concurrent connection processing and high concurrent data processing. Half sync/half async model (HSHA) is adopted to eliminate network bottle-neck, which can support high concurrent network connection. Through data partition, lock competition is eliminated and cache movement is reduced. Furthermore, consistent hash is adopted as data distribution strategy which can improve the scalability of system on multicore. Though some of these ideas appear elsewhere, SKVM is the first to combine them together. The experimental results show that SKVM can reach at most 2.4× higher throughput than Memcached, and scales near linearly with the number of cores under any workload.

关键词： In-Memory KV store Multicore Scalability Concurrent data access

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A Novel Metadata Extraction Method for Surveillance Video

A Novel Metadata Extraction Method for Surveillance Video

引用

International Conference on computing, Networking and Communications

作者： Ran Zheng Long Chen Hai Jin Lei Zhu Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781467385800

Surveillance videos are increasing massively with monitoring cameras widely deployed in cities. Metadata of moving objects in videos can reduce video storage and be utilized in many video analysis applications. The whole metadata extraction is too time-consuming to be fulfilled quickly. Therefore, it is urgent to parallelize and accelerate the extraction process. However, iterative execution of traditional metadata extraction methods makes the parallelization quite challenging. In this paper, we propose a novel Parallel Metadata Extraction (PME) method for surveillance video. A novel video segmentation algorithm is designed to segment whole video into independent video segments. The metadata of each video segment is extracted independently and simultaneously on computer nodes, which will be integrated later to guarantee the completeness of the metadata. Performance evaluations demonstrate that PME can accelerate extraction process greatly almost without metadata loss.

关键词： Surveillance Videos Video Segmentation Metadata Extraction Iterative Execution MapReduce

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Harnessing Dynamic Interests of Crowd in Chinese Online Shopping Festivals

Harnessing Dynamic Interests of Crowd in Chinese Online Shop...

引用

IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Linhai He Xia Xie Hai Jin Fangming Liu Xijiang Ke Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

Online shopping is popular in promotion festivals like Singles' Day in China. With the presence of a flash crowd of customers during the limited time in E-commerce websites, the traditional system provides multi-dimensional product ranking lists including popularity based bought lists and viewed lists due to the customers' conformity to the popular products. However, the overloaded information may cause a long path to purchase for customers, who can not efficiently buy satisfied products within the time-limited festivals. To shorten customers' purchasing path, this paper designs an interests-based ranking method to automatically and efficiently aggregate an unified ranking list, by analyzing thousands of customers' shopping behavior to harness the dynamic and wide interests of crowd. Initially, we transform the local interaction behavior of flash crowd into the interests of crowd, which then is further personalized to an unified ranking for each customer. We combine user's temporal interests and current crowd wisdom to generate a new personalized unified ranking. The combined ranking is continuously adjusted with the recent fixed past time window data iteratively according to the evolution growth of crowd. An implementation test is carried out on a real world trace in large-scale interaction logs, which is from Alibaba Tmall with 12 million users and 29 thousand brands. It shows that combining the user's temporal interests and the aggregated crowd wisdom ranking improve the quality of item recommendations distinctly.

关键词： Aggregates Bayes methods Market research Mathematical model Bipartite graph Time complexity Predictive models

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A Rule-based Framework of Metadata Extraction from Scientific Papers

A Rule-based Framework of Metadata Extraction from Scientifi...

引用

2011 IEEE 10th International Symposium on Distributed computing and Applications to Business,Engineering(第十届电子商务、工程及科学领域的分布式计算和应用国际学术研讨会 DCABES 2011)

作者： Zhixin Guo Hai Jin Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan 430074 China

Most scientific documents on the web are unstructured or semi-structured, and the automatic document metadata extraction process becomes an important task. This paper describes a framework for automatic metadata extraction from scientific papers. Based on a spatial and visual knowledge principle, our system can extract title, authors and abstract from scientific papers. We utilize format information such as font size and position to guide the metadata extraction process. The experiment results show that our system achieves a high accuracy in header metadata extraction which can effectively assist the automatic index creation for digital libraries.

关键词： document metadata information extraction rulebased

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Heterogeneous Grid Workflow Management Based on Virtual Service

Heterogeneous Grid Workflow Management Based on Virtual Serv...

引用

第七届网格与协同计算国际会议(Seventh International Conference on Grid and Cooperative computing GCC 2008)

作者： Song Wu Kai Wang Hai Jin Deqing Zou Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424432806;9780769534497

Heterogeneous grid workflow management plays an important role in the grid interoperation. It integrates service resources from different grid systems and packs them as atomic services into a composite service. The focuses of the research are how to shield the difference among the heterogeneous grid services and how to provide a flexible way to compose services. Heterogeneous grid workflow management mechanism, based on virtual service, compiles with BPEL4WS standards and shields the differences in the aspects of both organization of service information and the types of service among heterogeneous grids. The mechanism compensates for the weakness that traditional mechanism requires prior static binding in the service selection and scheduling. The proposed mechanism can provide some new functions like service backup and dynamic service selection based on QoS to improve the flexibility and stability of workflow management. In addition, in order to address the issues of tight coupling between data and service, the proposed mechanism employs virtual data space and corresponding data transferring solution.

关键词： workflow management grid service virtual service dynamic binding

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Communication-Efficient and Privacy-Preserving Data Aggregation without Trusted Authority

Communication-Efficient and Privacy-Preserving Data Aggregat...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Xuhui Gong Qiang-Sheng Hua Lixiang Qian Dongxiao Yu Hai Jin Services Computing Technology and System Lab/Big Data Technology and System Lab/Cluster and Grid Computing Lab Huazhong University of Science and Technology P. R. China

ISBN: (纸本)9781538641293

Privacy-preserving data aggregation has been extensively studied in the past decades. However, most of these works target at specific aggregation functions such as additive or multiplicative aggregation functions. Meanwhile, they assume there exists a trusted authority which facilitates the keys and other information distribution. In this paper, we aim to devise a communication efficient and privacy-preserving protocol that can exactly compute arbitrary data aggregation functions without trusted authority. In our model, there exist one untrusted aggregator and n participants. We assume that all communication channels are insecure and are subject to eavesdropping attacks. Our protocol is designed under the semi-honest model, and it can also tolerate k (k ≤ n-2) collusive adversaries. Our protocol achieves (n - k) -source anonymity. That is, for the source of each collected data aparting from the colluded participants, what the aggregator learns is only from one of the (n - k) non-colluded ones. Compared with recent work [1] that computes arbitrary aggregation functions by collecting all the participants' data using the trusted authority, our protocol increases merely by at most a factor of O(([logn/loglogn]) 2 ) in terms of computation time and communication cost. The key of our protocol is that we have designed algorithms that can efficiently assign unique sequence numbers to each participant without the trusted authority.

关键词： Protocols Data aggregation Computational modeling Privacy Additives Encryption

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