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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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FedWNS: Data Distribution-Wise Node Selection in Federated Learning via Reinforcement Learning

FedWNS: Data Distribution-Wise Node Selection in Federated L...

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International Conference on Computer supported Cooperative Work in Design

作者： Chengwu Tu Shengjie Zhao Hao Deng School of Software Engineering Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Shanghai China Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education Shanghai China

To deal with the discrepancy between global and local objectives in the federated learning invoked by the non-independent, identically distributed (non-IID) data and mitigate the impact of catastrophic forgetting in the training phase, we propose a federated learning framework with data distribution-wise reinforcement learning to perform node selection to accelerate the convergence process and alleviate the accuracy degradation. In this framework, the agent on the central server observes the number of samples every node owns, the derived distribution information of every dataset, and the current local and global accuracy. Then infer the selected node-set to participate in the current federated learning round through policy network in reinforcement learning. Finally, we conduct simulations with publicly data sets. Simulation results indicate that our FedWNS outperforms the existing FedAvg and CSFedAvg on the testing accuracy and the communication rounds to reach target accuracy under different settings.

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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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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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MIME: Fast and Accurate Flow Information Compression for Multi-Spread Estimation

MIME: Fast and Accurate Flow Information Compression for Mul...

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International Conference on Network Protocols

作者： Hanwen Zhang He Huang Yu-E Sun Zhaojie Wang School of Computer Science & Technology Soochow University Suzhou China School of Rail Transportation Soochow University Suzhou China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Spread estimation is an essential issue in high-speed networks with wide applications, such as network billing, quality of service, anomaly detection, etc. As a promising technique, sketch can efficiently estimate per-flow spread with only a small memory cost. Many studies focus on improving the performance of sketches. However, these works primarily focus on optimizing the counter level or sketch level without considering the scenario of multi-spread estimation, which is crucial for improving memory utilization and detecting anomalies. In this paper, we propose an efficient flow information compression algorithm based on the on-chip/off-chip hybrid framework to estimate multiple flow spreads. In the on-chip memory, we filter out non-duplicates and sample them to the off-chip space for recording. In the off-chip memory, we compress each sampled non-duplicate to a carefully designed bit-cube. When the measurement is finished, we separate corresponding KV-flows from a specific flow based on the user query. Then, we rebuild this flow to a subset group based on the duplicate number of each KV-flow. Finally, according to the Multi-set theory, we derive an accurate multi-spread estimate formula to solve this issue with a high throughput and small on-chip memory usage. Furthermore, we evaluate the performance of our proposed estimator using real Internet traffic traces downloaded from CAIDA. Experiments show that, compared to the state-of-the-art, our proposal achieves a 97.2% lower average relative error in per-destination source flow spread estimation with a tight on-chip memory, e.g., 320KB. And our proposed method achieves 31.86 higher processing throughput.

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On multicast throughput scaling of hybrid wireless networks with general node density

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Computer Networks 2011年第15期55卷 3548-3561页

作者： Cheng Wang Changjun Jiang Xiang-Yang Li Yunhao Liu Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States TNLIST School of Software Tsinghua University China

In this paper, we consider hybrid wireless networks with a general node density λ ∈ [1, n ], where n ad hoc nodes are uniformly distributed and m base stations (BSs) are regularly placed in a square region A ( n , A ) = 1 , A × 1 , A with A ∈ [1, n ]. We focus on multicast sessions in which each ad hoc node as a user chooses randomly d ad hoc nodes as its destinations. Specifically, when d = 1 (or d = n − 1), a multicast session is essentially a unicast (or broadcast) session. We study the asymptotic multicast throughput for such a hybrid wireless network according to different cases in terms of m ∈ [1, n ] and d ∈ [1, n ], as n → ∞. To be specific, we design two types of multicast schemes, called hybrid scheme and BS - based scheme , respectively. For the hybrid scheme, there are two alternative routing backbones : sparse backbones and dense backbones . Particularly, according to different regimes of the node density λ = n A , we derive the thresholds in terms of m and d . Depending on these thresholds, we determine which scheme is preferred for the better performance of network throughput.

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

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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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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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