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IEEE Symposium on real-time and Embedded Technology and Applications

作者： Hahnsang Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

Electric vehicles powered with large-scale battery packs are gaining popularity as gasoline price soars. Large-scale battery packs usually consist of an estimated 12,000 battery cells connected in series and parallel, which are susceptible to battery-cell failures. Unfortunately, current battery-management systems are unable to handle the inevitable battery-cell failures very well. To address this problem, we propose a dynamic reconfiguration framework that monitors, reconfigures, and controls large-scale battery packs online. The framework is built upon a syntactic bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. In particular, the semantic bypassing mechanism is dictated by constant-voltage-keeping and dynamic-voltage-allowing policies. The former policy is effective in preventing unavoidable voltage drops during the battery discharge, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements. Our experimental evaluation has shown the proposed framework to enable the battery packs to be 9 times as fault-tolerant as a legacy scheme.

关键词： Large-scale systems Vehicle dynamics Centralized control Control systems Voltage real time systems Battery management systems Application software Embedded computing Power engineering computing

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Scheduling of Battery Charge, Discharge, and Rest

Scheduling of Battery Charge, Discharge, and Rest

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real-time Systems Symposium (RTSS)

作者： Hahnsang Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

Electric vehicles operate inefficiently with a naive battery management system that charges or discharges battery cells in a pack based solely on application load demands. The battery pack's operation-time and lifetime can be extended significantly by effectively scheduling (the cyber part) battery charge, discharge, and rest activities, based on the battery characteristics (the physical part). We propose a set of policies for scheduling battery-cell activities, called the weighted-k round-robin (kRR) scheduling framework. This framework dynamically adapts battery-cell activities to load demands and the condition of individual cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage-imbalances. The framework comprises two key components. First, an adaptive filter estimates the upcoming load demand. Then, based on the estimated load demand, the kRR scheduler determines the number of parallel-connected cells to be discharged simultaneously. The scheduler also effectively partitions the cells in the pack, allowing the cells to be simultaneously charged and discharged in coordination with the battery reconfiguration system we developed earlier [17]. Besides the kRR scheduling framework, we characterize the discharge and recovery efficiency of a Lithium-ion battery cell. The kRR scheduling framework is shown to outperform three alternative scheduling mechanisms with respect to the operation-time by 7-56%, and improve the tolerance of voltage-imbalance by up to 50%.

关键词： real time systems Robustness Global warming Threshold voltage Processor scheduling Laboratories Battery powered vehicles Battery management systems Application software Adaptive filters

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Fast discovery of spectrum opportunities in cognitive radio networks

Fast discovery of spectrum opportunities in cognitive radio ...

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2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN 2008

作者： Kim, Hyoil Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)9781424420179

We address the problem of rapidly discovering spectrum opportunities for seamless service provisioning for secondary users (SUs) in cognitive radio networks (CRNs). Specifically, we propose an efficient sensing-sequence that incurs a small opportunity-discovery delay by considering (1) the probability that a spectrum band (or a channel) may be available at the time of sensing, (2) the duration of sensing on a channel, and (3) the channel capacity. We derive the optimal sensing-sequence for channels with homogeneous capacities, and a suboptimal sequence for channels with heterogeneous capacities for which the problem of finding the optimal sensing-sequence is shown to be NP-hard. To support the proposed sensing-sequence, we also propose a channel-management strategy that optimally selects and updates the list of backup channels. A hybrid of maximum likelihood (ML) and Bayesian inference is also introduced for flexible estimation of ON/OFF channel-usage patterns and prediction of channel availability when sensing produces infrequent samples. The proposed schemes are evaluated via in-depth simulation. For the scenarios we considered, the proposed suboptimal sequence is shown to achieve close-to-optimal performance, reducing the opportunity-discovery delay by up to 47% over an existing probability-based sequence. The hybrid estimation strategy is also shown to outperform the ML-only strategy by reducing the overall opportunity-discovery delay by up to 34%. ©2008 IEEE.

关键词： Bayesian networks

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ARCMA: Attack-resilient collaborative message authentication in Wireless Sensor Networks 08

ARCMA: Attack-resilient collaborative message authentication...

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4th International Conference on Security and Privacy in Communication Networks, SecureComm'08

作者： Cho, Min-Gyu Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)9781605582412

Data Centric Storage (DCS) is a well-known data storage and query processing mechanism for Wireless Sensor Networks (WSNs), storing sensed data or their metadata at pre-specified locations. Queries issued by mobile users are sent to, and processed at, such storage nodes. However, securing DCS is very difficult because WSNs usually operate in an unattended environment and hence are subject to node-capture attacks. Even after capturing a single node, an attacker may be able to subvert the entire system by using the keying material extracted from the captured node. To remedy/alleviate the above problem, we propose Attack-Resilient Collaborative Message Authentication (ARCMA), in which sensor nodes collaboratively authenticate messages to be sent to, or received from, remote nodes. In ARCMA, each node belongs to one of k groups, and constructs an Authentication Tree (AT) which is formed with k nodes, each from a distinct group. Each node collaborates with the other nodes in its AT to authenticate messages. We propose two heuristics, called MIN and OPT, to construct ATs. Our analysis shows that the security of ARCMA does not degrade until the attacker capture k or more nodes. We also evaluate the overhead of constructing ATs and the cost of authenticating messages using ATs. Copyright 2008 ACM.

关键词： Authentication

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Fast Discovery of Spectrum Opportunities in Cognitive Radio Networks

Fast Discovery of Spectrum Opportunities in Cognitive Radio ...

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IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN

作者： Hyoil Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

关键词： Sensors Channel capacity Delay Algorithm design and analysis Availability Channel estimation Maximum likelihood estimation

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On accurate measurement of link quality in multi-hop wireless mesh networks

On accurate measurement of link quality in multi-hop wireles...

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12th Annual International Conference on Mobile computing and Networking, MOBICOM 2006

作者： Kim, Kyu-Han Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)1595932860

This paper presents a highly efficient and accurate link-quality measurement framework, called EAR (Efficient and Accurate link-quality monitoR), for multi-hop wireless mesh networks, that has several salient features. First, it exploits three complementary measurement schemes: passive, cooperative, and active monitoring. EAR maximizes the measurement accuracy by (i) dynamically and adaptively adopting one of these schemes and (ii) opportunistically exploiting the unicast application traffic present in the network, while minimizing the measurement overhead. Second, EAR effectively identifies the existence of wireless link asymmetry by measuring the quality of each link in both directions of the link, thus improving the utilization of network capacity by up to 114%. Finally, its reliance on both the network layer and the IEEE 802.11-based device driver solutions makes EAR easily deployable in existing multi-hop wireless mesh networks without system recompilation or MAC firmware modification. EAR has been evaluated extensively via both n.s-2-based simulation and experimentation on our Linux-based implementation. Both simulation and experimentation results have shown EAR to provide highly accurate link-quality measurements with minimum overhead. Copyright 2006 ACM.

关键词： Wireless telecommunication systems

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SMRP: Fast restoration of multicast sessions from persistent failures

SMRP: Fast restoration of multicast sessions from persistent...

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2005 International Conference on Dependable Systems and Networks

作者： Wu, Jian Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan

The growing reliance of networked applications on timely and reliable data transfer requires the underlying networking infrastructure to provide adequate services even in the presence of "persistent" failures (e.g., broken links/routers). It is much more difficult to meet this requirement for multicast sessions than for unicast communications because any on-tree component failure may often cause simultaneous service disruptions to multiple receivers. This paper presents a new multicast routing protocol, called the Survivable Multicast Routing Protocol (SMRP), which facilitates fast recovery of multicast sessions in face of persistent failures via local detour paths. Our evaluation results show that SMRP trades end-to-end delay and resource usage for short, and hence fast, recovery paths. For example, under a certain set of parameter values, SMRP shortens the recovery path by 20% with only a 5% increase of end-to-end delay and resource usage. Moreover, several design enhancements have made SMRP efficient, robust, flexible and scalable. © 2005 IEEE.

关键词： Multicasting

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Priority refinement for dependent tasks in large embedded real-time software

Priority refinement for dependent tasks in large embedded re...

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11th IEEE real-time and Embedded Technology and Applications Symposium, RTAS 2005

作者： Merrick, Jeffrey R. Wang, Shige Shin, Kong G. Song, Jing Milam, William Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2122 Ford Motor Company

In a large embedded real-time system, priority assignment can greatly affect the timing behavior - which can consequently affect the overall behavior - of the system. Thus, it is crucial for model-based design of a large embedded real-time system to be able to intelligently assign priorities such that tasks can meet their deadlines. In this paper, we propose a priority-refinement method for dependent tasks distributed throughout a heterogeneous multiprocessor environment. In this method, we refine an initial priority assignment iteratively using the simulated annealing technique with tasks' latest completion times (LCT). Our evaluations, based on randomly-generated models, have shown that the refinement method outperforms other priority-assignment schemes and scales well for large, complex, real-time systems. This method has been implemented in the Automatic Integration of Reusable Embedded Software (AIRES) toolkit and has been successfully applied to a vehicle system control application. © 2005 IEEE.

关键词： Embedded systems

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Priority refinement for dependent tasks in large embedded real-time software

Priority refinement for dependent tasks in large embedded re...

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IEEE Symposium on real-time and Embedded Technology and Applications

作者： J.R. Merrick S. Wang K.G. Shin Department of Electrical Engineering and Computer Science Real-Time Computing Laboratory The University of Michigan Ann Arbor MI

关键词： Embedded software real time systems Timing Simulated annealing Vehicles Control systems Application software Programming Software architecture Embedded computing

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Journal of Information science and engineering: Editorial notice

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Journal of Information science and engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

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