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| 1 | MilkyWay-2 supercomputer: system and application显示文摘 | Xiangke LIAO Liquan XIAO Canqun YANG Yutong LU | 2014 | Frontiers of Computer Science2014，8，3： | 32 |
| 2 | A scalable code dissemination protocol in heterogeneous wireless sensor networks显示文摘Code dissemination is currently a major research issue in wireless sensor networks (WSNs).Many studies focus on code dissemination in homogeneous WSNs,mainly using a broadcast approach to solve this problem;few studies on code dissemination in heterogeneous WSNs.Furthermore,broadcasting cannot readily be used to solve the heterogenous WSN code dissemination problem directly,which is where we have focused our attention.We transformed this problem into a minimum non-leaf nodes (MNN) Steiner tree problem.We designed a scalable multicast protocol,named Heterogeneous Sensor Networks Scalable Reprogramming Protocol (HSR) to solve the MNN problem.HSR can build different multicast trees according to different nodes or code modules to disseminate different codes to them.HSR is able to approximate the MNN tree problem to a ratio of ln|R| (R is the set of all destinations) best known lowest bound.Therefore,the communication cost is significantly decreased and the total energy required by WSNs is reduced.We further designed two scalable schemes,special routing log and hops-restricted local broadcast,which compress the multicast tree information and deliver the multicast messages without loss.We also designed a 3-stage pipeline to speed up the transmission of packets,which alleviated interference and hidden terminal issues.We evaluated our design through comprehensive simulations and prototype implementations on Mica2 motes.Experimental results demonstrate that HSR outperforms previous protocols including the most recent studies on Sprinkler and uCast. | PENG ShaoLiang LI ShanShan LIAO XiangKe PENG YuXing XIAO Nong | 2012 | Science China(Information Sciences)2012，55，6： | 5 |
| 3 | Enhancement of cooperation between file systems and applications — VFS extensions for optimized performance显示文摘Modern operating systems incorporate an abstract layer called Virtual File System(VFS), which is positioned between user applications and real file systems to hide the differences of various file systems and to expose generic application interfaces for requesting file system services. However, VFS sometimes does not give applications an opportunity to pass information to file systems to help them make correct optimization decisions. In this paper, we review the Linux VFS, discuss its deficiencies and propose several extensions to allow applications to cooperate with the file systems more efficiently. We introduce simple prefetching interfaces and advisory flags to allow applications to communicate application-related semantics to VFS and/or the underlying file systems. These suggestions, which neither affect the semantics of applications nor modify their programming models, not only lead to simple VFS/file systems but also guide them to make correct performance-related decisions, if required. We demonstrate that these interfaces and flags are also easy to implement and can boost application performance by up to 4.29 X. | WANG Li LIAO XiangKe XUE JingLing WEIL Sage WEN YunChuan YANG XueJun | 2015 | Science China(Information Sciences)2015，58，9： | 2 |
| 4 | Leach: an automatic learning cache for inline primary deduplication system显示文摘 | Bin LIN Shanshan LI Xiangke LIAO Jing ZHANG Xiaodong LIU | 2014 | Frontiers of Computer Science2014，8，2： | 2 |
| 5 | RTS-PGATS based approach for data-intensive scheduling in data grids显示文摘格子计算是计算机资源在的联合一泛泛地联合了,异构,并且地理上驱散的环境。格子数据是在格子计算使用的数据,它由大规模数据集中的应用程序组成,生产并且消费数据的巨大的数量,越过很多机器分布式。数据格子计算填写其各个要求可以各在不同资源上被复制的巨大的分布式的数据集合的独立任务的集合。减少应用程序的结束时间并且改进格子的性能,适当计算资源应该被选择执行这些任务和选择服务这些任务要求的文件的适当存储资源。这个问题能因此被分解为二亚问题:存储资源的选择和到计算资源的任务的赋值。这份报纸建议一个调度程序,它被分解为能在平行跑并且使用两平行禁忌搜索和一个平行基因算法的三部分。最后,建议算法被把它与另外的相关算法作比较评估,它指向最小化 makespan。模拟结果证明建议途径能是为安排大数据格子应用的一种好选择。 | Kenli LI Zhao TONG Dan LIU Teklay TESFAZGHI Xiangke LIAO | 2011 | Frontiers of Computer Science2011，5，4： | 2 |
| 6 | MilkyWay-2: back to the world Top 1显示文摘 | Xiangke LIAO | 2014 | Frontiers of Computer Science2014，8，3： | 1 |
| 7 | Self-monitoring for sensor networks 显示文摘 | Dong Dezun Liu Yunhao Liao Xiangke | 2006 | Elsevier Computer Communications2006，，29： | 1 |
| 8 | LCCFS: a lightweight distributed file system for cloud computing without journaling and metadata services显示文摘The major usage of a file system integrated with a cloud computing platform is to provide the storage for VM(virtual machine) instances. Distributed file systems, especially those implemented on top of object storage have many potential advantages over traditional local file systems for VM instance storage. In this paper, we make an investigation in the requirements imposed on a file system in cloud computing scenario,and claim that the implementation of a file system for VM instance storage could be reasonably simplified. We demonstrate that on top of an object storage with simple object-granularity transaction support, a lightweight distributed file system, which requires neither journaling nor dedicated metadata services, can be developed for cloud computing. We have implemented such a distributed file system, called LCCFS(lightweight cloud computing file system), based on the RADOS(reliable autonomic distributed object storage) object storage.Our experimental results show that for the main workloads in cloud computing, LCCFS achieves almost the same or slightly higher performance than CephFS(ceph filesystem), another published distributed file system based on RADOS. Compared to CephFS, LCCFS has only one tenth of its LOCs(lines of code). This theoretical simplicity makes it easy to implement LCCFS correctly and stably by avoiding the sheer design and implementation complexity behind CephFS, thereby making LCCFS a promising candidate in the cloud computing production environment. | Li WANG Jingling XUE Xiangke LIAO Yunchuan WEN Min CHEN | 2019 | Science China(Information Sciences)2019，62，7： | 1 |
| 9 | Energy efficient muhipath routing using network coding in wireless sensor networks 显示文摘 | Li Shanshan Zhu Peidong Liao Xiangke | 2006 | Ad-Hoc Mobile and Wireless Networks2006，41，4： | 1 |
| 10 | He Match: A redundancy layout placement scheme for erasure-coded storages in practical heterogeneous failure patterns显示文摘Erasure codes are widely used in storage systems for providing data reliability due to the advantage of high storage efficiency, while the access efficiency becomes the main shortcoming because of the extra data retrieve and decoding for accessing unavailable data. Most existing work designs erasure codes based on the ideal failure pattern where all storage nodes fail at the same rate. However in practice, the physical storage nodes fail at different rates due to the heterogeneous hardware, topologies and application behaviors. In this paper,we consider the heterogeneous failure pattern and analyze how the failure pattern impacts the overall access efficiency and reliability of erasure-coded storage systems. We propose He Match, a redundancy layout placement scheme in practical heterogeneous failure pattern for erasure-coded storage access efficiency. Specifically, we first study how the heterogeneous failure pattern impacts the access efficiency and propose a general model based on the Tanner graph to evaluate and predict the access efficiency in specific failure pattern and redundancy layout.Then, we propose the redundancy layout placement scheme, which matches the redundancy layout with the physical storage nodes in practical heterogeneous failure patterns based on the evaluation and prediction from our model. The experimental results demonstrate that the model we propose accurately evaluates the access efficiency, and He Match saves unavailable data access cost by up to 20% and improves the system reliability as well. | ZHANG Jing LI ShanShan LIAO XiangKe PENG ShaoLiang LIU XiaoDong JIA ZhouYang | 2015 | Science China(Information Sciences)2015，58，6： | 1 |
| 11 | A survey of script learning显示文摘Script is the structured knowledge representation of prototypical real-life event sequences.Learning the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensible inferences.Script learning is an interesting and promising research direction,in which a trained script learning system can process narrative texts to capture script knowledge and draw inferences.However,there are currently no survey articles on script learning,so we are providing this comprehensive survey to deeply investigate the standard framework and the major research topics on script learning.This research field contains three main topics:event representations,script learning models,and evaluation approaches.For each topic,we systematically summarize and categorize the existing script learning systems,and carefully analyze and compare the advantages and disadvantages of the representative systems.We also discuss the current state of the research and possible future directions. | Yi HAN Linbo QIAO Jianming ZHENG Hefeng WU Dongsheng LI Xiangke LIAO | 2021 | Frontiers of Information Technology & Electronic Engineering2021，22，3： | 0 |
| 12 | HTDcr:a job execution framework for high-throughput computing on supercomputers显示文摘High-throughput computing(HTC)is a computing paradigm that aims to accomplish jobs by easily breaking them into smaller,independent components.However,it requires a large amount of computing power for a long time.Most existing HTC frameworks are job-oriented without support for coscheduling with hardware architecture and task-level execution.Also,most of the frameworks reach a limited scale,and their usability needs further improvement.Herein,we present HTDcr,a job execution framework for the HTC on supercomputers.This study aims to improve the throughput,task dispatching,and usability of the framework.In detail,the throughput optimizations include a sophisticated designed task management system,a hierarchical scheduler,and the co-optimization of the task-scheduling strategy with the application and hardware characteristics.The optimizations for usability include a programable execution workflow,mechanisms for more robust and reliable service qualities,and a fine-grained resource allocation system for the colocation of multiple jobs.According to our evaluations,HTDcr can achieve outstanding scalability and high throughput on large-scale clusters for the HTC workload.We evaluate HTDcr with several microbenchmarks and real-world applications on Tianhe-2 and Sunway TaihuLight to demonstrate its effects on existing design mechanisms.For instance,the task scheduling for two real-world applications integrated with the application and hardware characteristics achieves 1.7×and 1.9×speedups over the basic task-scheduling strategy. | Jiazhi JIANG Dan HUANG Hu CHEN Yutong LU Xiangke LIAO | 2024 | Science China(Information Sciences)2024，67，1： | 0 |
| 13 | SupraBiology 2014: Promoting UK-China collaboration on Systems Biology and High Performance Computing显示文摘 | Ettore Murabito Riccardo Colombo Chengkun Wu Malkhey Verma Samrina Rehman Jacky Snoep Shao-Liang Peng Naiyang Guan Xiangke Liao Hans V. Westerhoff | 2015 | Frontiers of Electrical and Electronic Engineering in China2015，10，1： | 0 |
| 14 | P-Zone: Connectivity-based Packet Path Tracing in Wireless Sensor Networks显示文摘 | LU Xiaopei DONG Dezun LIAO Xiangke PENG Shaoliang | 2013 | Chinese Journal of Electronics2013，22，3： | 0 |
| 15 | Evolutionary Multi-Tasking Optimization for High-Efficiency Time Series Data Clustering显示文摘Time series clustering is a challenging problem due to the large-volume,high-dimensional,and warping characteristics of time series data.Traditional clustering methods often use a single criterion or distance measure,which may not capture all the features of the data.This paper proposes a novel method for time series clustering based on evolutionary multi-tasking optimization,termed i-MFEA,which uses an improved multifactorial evolutionary algorithm to optimize multiple clustering tasks simultaneously,each with a different validity index or distance measure.Therefore,i-MFEA can produce diverse and robust clustering solutions that satisfy various preferences of decision-makers.Experiments on two artificial datasets show that i-MFEA outperforms single-objective evolutionary algorithms and traditional clustering methods in terms of convergence speed and clustering quality.The paper also discusses how i-MFEA can address two long-standing issues in time series clustering:the choice of appropriate similarity measure and the number of clusters. | Rui Wang Wenhua Li Kaili Shen Tao Zhang Xiangke Liao | 2024 | Tsinghua Science and Technology2024，29，2： | 0 |
| 16 | Learning to Branch in Combinatorial Optimization With Graph Pointer Networks显示文摘Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances. | Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao | 2024 | IEEE/CAA Journal of Automatica Sinica2024，11，1： | 0 |
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