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Task assignment in heterogeneous computing systems using an effective iterated greedy algorithm

Journal of systems and Software 2011年第6期84卷 985-992页

作者： Qinma Kang Hong He Huimin Song Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China School of Information Engineering Shandong University at Weihai 180 Wenhua Xilu Weihai 264209 China School of Mathematics and Statistics Shandong University at Weihai Weihai 264209 China

A fundamental issue affecting the performance of a parallel application running on a heterogeneous computing system is the assignment of tasks to the processors in the system. The task assignment problem for more than three processors is known to be NP-hard, and therefore satisfactory suboptimal solutions obtainable in an acceptable amount of time are generally sought. This paper proposes a simple and effective iterative greedy algorithm to deal with the problem with goal of minimizing the total sum of execution and communication costs. The main idea in this algorithm is to improve the quality of the assignment in an iterative manner using results from previous iterations. The algorithm first uses a constructive heuristic to find an initial assignment and iteratively improves it in a greedy way. Through simulations over a wide range of parameters, we have demonstrated the effectiveness of our algorithm by comparing it with recent competing task assignment algorithms in the literature.

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Reduction Criteria for Probabilistic Models with Spatial Restrictions on States

Reduction Criteria for Probabilistic Models with Spatial Res...

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International Conference on Networks Security, Wireless Communications and Trusted computing, NSWCTC

作者： Niu Jun Guosun Zeng Embedded System and Service Computing Key Laboratory Ministry of Education Shanghai China College of Information Engineering Zhejiang Business and Technology Institute Ningbo China Department of Computer Science and Technology University of Tongji Shanghai China

ISBN: (纸本)9781424465972;9780769540115

Partial order reduction techniques have been used to combat the state explosion problem in model checking procedures for concurrent systems with probabilistic behaviors. There are some results that give criteria on applying partial order reduction for verifying quantitative time properties and reward-based properties on actions. However, there are many situations that reward-based properties are expressed on states rather than on actions because actions are triggered in no time and the quantities can not be obtained easily. This paper presents reduction criteria for a probabilistic temporal logic that allows specification of restrictions on quantitative measures given by spatial resources function for the states of the considered system and provides the proof of the correctness.

关键词： Explosions Computer networks Concurrent computing embedded computing educational technology Probabilistic logic Communication system security Computer security Information security Wireless communication

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Evaluating feedback systems for residential building energy monitoring

Evaluating feedback systems for residential building energy ...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Wenqi Wendy Guo Tania Ullah MengChu Zhou National Institute of Standards and Technology Gaithersburg MD USA ECE Dept. New Jersey Institute of Technology Newark NJ USA The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

Rising global energy demand, increasing electricity prices, and the limitation of natural resources have led to increased interest in energy monitoring of residential buildings. Much research has been done to examine the effect of energy use feedback to building occupants. An important step towards energy awareness is to provide timely and finegrained consumption information of major household energy expenditures through feedback systems, known as residential energy monitoring systems (REMS). To accomplish this, researchers and product designers are intent on improving the residential whole-building energy consumption estimates gained through sensor networks at homes. Additionally, profiling the usage of appliances and devices within a home can be used to determine an occupant's daily activities and to optimize energy consumption. In this work, we take a step toward creating an evaluation procedure for REMS by determining factors that affect their ability to accurately convey energy usage to occupants. Two feedback sensor systems are assessed in a testbed in which electrical loads typical to a home are operated. Preliminary tests show that the accuracy of the REMS measurement is dependent on an electrical load's power factor. Together with other findings, the results will assist researchers in forming a comprehensive test procedure that will characterize feedback systems in the future.

关键词： Reactive power Monitoring Buildings Power measurement Home appliances Energy consumption Measurement errors

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Virtual-Source and Virtual-Swarm-Based Particle Swarm Optimizer for Large-Scale Multi-Source Location via Robot Swarm

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Zhang, JunQi Lin, YuXuan Zhou, MengChu Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

Multi-source location is a significant application in the field of robot swarm and is required to find all sources whose number and distribution are unknown in advance. With few parameters and fast search, Particle Swarm Optimizer (PSO) variants that have certain grouping capability have been applied to address multi-source location problems by dividing a swarm such that every source has robots to locate. However, they are difficult to predetermine the exact number of groups, require a big number of robots, and are easily trapped in the no-signal areas when the proportion of no-signal areas is high. This work proposes a Virtual-source and Virtual-swarm-based PSO (VVPSO) to divide a search area into multiple cells equally, each of which has a virtual source in its center. Then, instead of robots grouping, only one group of robots is employed to traverse all virtual sources, and search their corresponding cells to locate real sources by a new PSO called Real-virtual mapping PSO (RMPSO). RMPSO asymmetrically maps a robot into a particle swarm with multiple virtual particles to perform PSO, which greatly reduces the requirements for the number of robots. Experimental results show that VVPSO has great search scalability and can solve large-scale multi-source location problems than two state-of-the-art grouping methods and three representative multimodal PSO variants, even with only one robot. Hence, this work greatly advances the field of multi-source location by using mobile robot swarm. IEEE

关键词： Robots

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A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability

A Better Cardinality Estimator with Fewer Bits, Constant Upd...

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

作者： Yang Du He Huang Yu-E Sun Kejian Li Boyu Zhang Guoju Gao School of Computer Science and Technology Soochow University Suzhou China School of Rail Transportation Soochow University Suzhou China Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education Shanghai China

Cardinality estimation is a fundamental problem with diverse practical applications. HyperLogLog (HLL) has become a standard in practice because it offers good memory efficiency, constant update time, and mergeability. Some recent work achieved better memory efficiency, but typically at the cost of impractical update time or losing mergeability, making them incompatible with applications like network-wide traffic measurement. This work presents SpikeSketch, a better cardinality estimator that reduces memory usage of HLL by 37% without sacrificing other crucial metrics. We adopt a bucket-based data structure to promise constant update time, design a smoothed log 4 ranking and a spike coding scheme to compress cardinality observables into buckets, and propose a lightweight mergeable lossy compression to balance memory usage, information loss, and mergeability. Then we derive an unbiased estimator for recovering cardinality from the lossy-compressed sketch. Theoretical and empirical results show that SpikeSketch can work as a drop-in replacement for HLL because it achieves a near-optimal MVP (memory-variance-product) of 4.08 (37% smaller than HLL) with constant update time and mergeability. Its memory efficiency even defeats ACPC and HLLL, the state-of-the-art lossless-compressed sketches using linear-time compression to reduce memory usage.

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A Generalized Model with Spatial Resources Labels

A Generalized Model with Spatial Resources Labels

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International Conference on Biomedical Engineering and Computer Science (ICBECS)

This paper proposes a generalized model by extending Markov chain with spatial resources labels, which can describe the functional and performance properties and some basic characteristics such as nondeterminacy and randomicity. The syntax and semantics of the new model are shown based on the existing temporal logics such as CSRL and pathCSRL. The model checking procedure is discussed and thus the practicability of the new model is intuitive. Based on the existing models, the proposed model includes spatial resources labels only by adding the spatial information to the existing labels of states, so the treatment of the state explosion problem is similar to that in the existing models.

关键词： educational technology Paper technology Logic Labeling educational institutions embedded system embedded computing Computer science education systems engineering education Computer science

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$\varepsilon$-Constraint and Fuzzy Logic-Based Optimization of Hazardous Material Transportation via Lane Reservation

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IEEE Transactions on Intelligent Transportation systems 2013年第2期14卷 847-857页

作者： Zhen Zhou Feng Chu Ada Che MengChu Zhou Computing Integrative Biology and Complex Systems Laboratory University of Evry-Val dEssonne Evry France School of Management Northwestern Polytechnical University Xian China Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

With economic development, a great amount of hazardous material is shipped in the transport network every day. Hazardous material transportation is well known for its high potential risk. An accident can cause very serious economic damage and will have a negative impact on public health and the environment over the long term. Transporting hazardous materials on special lanes can reduce the risk. However, a lane reservation strategy may worsen traffic conditions for other vehicles. This paper investigates a hazardous material transportation problem with lane reservation. The problem lies in how to choose lanes to be reserved in the network and select the path for each hazardous material shipment from the reserved lanes. The goal is to obtain the best compromise between the impact on normal traffic and the transportation risk. A multiobjective integer programming model is presented for the new problem. Then, an algorithm is developed based on the ε -constraint method and a fuzzy-logic-based approach. Pareto optimal solutions are obtained by the former, and a preferred solution is selected by the fuzzy-logic-based approach. Computational results demonstrate the efficiency of the proposed algorithm using an instance based on a real network topology and randomly generated instances.

关键词： Hazardous materials Accidents Roads Linear programming Vectors Optimization

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Trust reasoning and optimization based on associate petri net

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ICIC Express Letters 2011年第3期5卷 791-796页

作者： Fang, Xianwen Yan, Chungang Fan, Xiaoqin Yin, Zhixiang Department of Information and Computing Science Anhui University of Science and Technology No. 168 Shungengzhong Road Huainan 232001 China Key Lab of Embedded System and Service Computing Ministry of Education Tongji University No. 1239 Siping Road Shanghai 201804 China

Trust issue is an important problem both in social field and information field. At present, there are few methods considering the interaction behavior relativity between models which can judge the interaction influence, so the obtained trust value is imprecise and unreliable. In the paper, behavior-aware trust computation and reasoning methods based on Associate Petri net (APN) are presented, which use the APN reasoning and take the interaction relativity into account. Using Genetic Algorithm (GA) combined with the properties of APN, a trust optimization method is obtained. Theoretical analysis and experimental results indicate that the method owns both lower computation cost and lower error rate. © 2011 ISSN 1881-803X.

关键词： Genetic algorithms

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RETRACTED ARTICLE: Stability analysis of dynamic collaboration model under two-lane case

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Nonlinear Dynamics 2014年第1期81卷 1021-1021页

作者： Li, Zhipeng Zhang, Run Xu, Shangzhi Qian, Yeqing The Key Laboratory of Embedded System and Service Computing Supported by Ministry of Education Tongji University Shanghai China

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Learning How to Avoiding Obstacles for End-to-End Driving with Conditional Imitation Learning 19

Learning How to Avoiding Obstacles for End-to-End Driving wi...

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Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning

作者： Enwei Zhang Hongtu Zhou Yongchao Ding Junqiao Zhao Chen Ye The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University School of Electronics and Information Engineering Shanghai P. R. China Tongji University School of Electronics and Information Engineering Shanghai P. R. China Tongji University School of Electronics and Information Engineering P. R. China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University School of Electronics and Information Engineering P. R. China

ISBN: (纸本)9781450372213

Obstacle avoiding is one of the most complex tasks for autonomous driving systems, which was also ignored by many cutting-edge end-to-end learning-based methods. The difficulties stem from the integrated process of detection and interpretation of environment and obstacles and generation of proper behaviors. We make the use of CARLA, a simulator for autonomous driving research, and collect massive human drivers' reactions to obstacles on road subjecting to given driving commands, i.e. follow, go straight, turn left and turn right for about 6 hours. A behavior-Cloning neural network architecture is proposed with the modified loss that enlarge the effects of errors for steer, which indicates the benefit to high an accuracy. We found the data augmentation of the image is crucial to the training of the proposed network. And a reasonable limit allows avoiding unexpected stop. The experiments demonstrate 3 obstacle avoidance cases: for the same type as the training dataset, other automobile and two-wheeled vehicles. Finally, the CARLA benchmark is also tested.

关键词： imitation learning obstacle avoidance end-to-end autonomous vehicles

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