Beihua Ying

Tsinghua University, Beijing, Beijing Shi, China

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Publications (6)1.95 Total impact

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    ABSTRACT: An Energy Efficient Sensor Network Processor with Latency-Aware Adaptive Compression
    IEICE Transactions. 01/2011; 94-C:1220-1228.
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    ABSTRACT: Energy is an important consideration in wireless sensor networks. In the current compression evaluations, traditional indices are still used, while energy efficiency is probably neglected. Moreover, various evaluation biases significantly affect the final results. All these factors lead to a subjective evaluation. In this paper, a new criterion is proposed and a series of tunable compression algorithms are reevaluated. The results show that the new criterion makes the evaluation more objective. Additionally it indicates the situations when compression is unnecessary. A new adaptive compression arbitration system is proposed based on the evaluation results, which improves the performance of compression algorithms.
    Sensors 01/2010; 10(4):3195-217. · 1.95 Impact Factor
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    Beihua Ying, Yongpan Liu, Hui Wang
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    ABSTRACT: Previous studies have indicated that data compression in wireless sensor networks is not always beneficial to energy conservation due to the additional computational energy costs. This work gives an energy-efficient arbitration mechanism that enhances the performance of compression algorithms by avoiding unnecessary energy losses. The adaptive compression arbitration system uses a new prediction modeling and adaptation. Tests show that the modeling method gives better predictions with the adaptive mechanism needing less data for modeling, which allows on-line prediction modeling instead of an off-line training process. Moreover, adaptive adjustments of the model parameters enable the system to keep good arbitration precision even as the data characteristics or applications change.
    Tsinghua Science & Technology 01/2010; 15(2):202-208.
  • Wei Liu, Beihua Ying, Huazhong Yang, Hui Wang
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    ABSTRACT: Resource constraints make it considerably difficult to implement and optimize cryptography algorithms on sensor nodes. In order to provide guidelines for design, it is necessary to predict overheads of these algorithms without final implementations and optimizations. In this paper, a mathematical model based on overheads of basic operations frequently used in cryptography algorithms is presented for predicting overheads of these algorithms. Simulation results of practical implementations of several popular algorithms verify that this model is very accurate. Because these basic operations cannot be ignored when implementing cryptography algorithms, the prediction results can be used as lower bounds of overheads. More importantly, as these basic operations are also elements of other applications such as data processing, their overheads can also be used to predict overheads of those applications using the same method.
    Advanced Communication Technology, 2009. ICACT 2009. 11th International Conference on; 03/2009
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    ABSTRACT: Energy efficiency is one of the most important design metrics for wireless sensor networks. As sensor data always have redundancies, compression is introduced for energy savings. However, in some cases, it is unlikely to be wise to trade computation energy for communication savings. In this paper, a novel node-level compression arbitration mechanism is proposed, which is applied to improve compression algorithms by avoiding unnecessary energy losses. Experimental results show that the highest percent savings of energy can reach 10% ~ 30% for different kinds of datasets. Furthermore, the overhead introduced by our proposed scheme is expected to be negligible approximately.
    Advanced Communication Technology, 2009. ICACT 2009. 11th International Conference on; 03/2009
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    ABSTRACT: In this paper, we propose an energy efficient architecture of wireless sensor network node. It consists of a general-purpose processor and several compression accelerators. To verify the low energy consumption of this architecture, we implement a baseband chip of sensor node by 1-poly 6-metal 0.18um CMOS technology, in which a hardware accelerator is realized based on a distributed wavelet compression algorithm. Our measurements show that the compression accelerator based architecture reduces over 98% energy consumption compared with the traditional solution.
    Proceedings of the 19th ACM Great Lakes Symposium on VLSI 2009, Boston Area, MA, USA, May 10-12 2009; 01/2009