Peng Yu-xing

A Delay Sensitive Feedback Control Data Aggregation Approach in Wireless Sensor Network

In wireless sensor networks (WSN) real-time data delivery is a challenging issue, especially when bursty events happen and many emergent packets appear. The cluster-based data aggregation has emerged as a basic and general technique in sensor networks. However, there is a trade-off issue between aggregation waiting (AW) delay and aggregation accuracy. Therefore, we propose a Delay Sensitive Feedback Control (DSFC) model to solve the trade-off issue. Our goal is to decrease the AW delay on the condition of meeting the desired aggregation accuracy for emergent packets when emergent event occurs. Simulation results verify the performance of DSFC, and demonstrate their attraction.

An efficient two-level bitmap index for cloud data management

A Cloud may be seen as a type of flexible computing infrastructure consisting of many compute nodes, where resizable computing capacities can be provided to different customers. To fully harness the power of the Cloud, efficient data management is needed to handle huge volumes of data and support a large number of concurrent end users. To achieve that, a scalable and high-throughput indexing scheme is generally required. Such an indexing scheme must support parallel search to improve scalability. In this paper, we present a bitmap based indexing scheme for efficient data processing in the Cloud. Our approach can be summarized as follows. First, we build a local bitmap index for each compute node which only indexes data residing on the node. Second, we organize the compute nodes as a structured overlay and each node maintains a portion of the global index for the whole different data. The global index is also bitmap index to indicate the node each data resides in. Third, all bitmaps are compressed by adopting run-length coding for reducing storage requirement. We conduct extensive experiments on a LAN, and the results demonstrate that our indexing scheme is dynamic, efficient and scalable.

An Efficient Distributed B-tree Index Method in Cloud Computing

To support online index and range queries, the Distributed B-tree is adopted to index the mass and rapidly in- creasing data in cloud computing. But current Distributed B-tree has three defects: low degree of concurrency, frequent node splitting and high cost of updates in clients. For above mentioned defects, this paper presents efficient distribute B- tree index in cloud computing environment, which effectively enhances the performance of the distributed B-tree index. First, it improves concurrent access by the distributed B-tree high concurrency access method based on node split history. Second, it reduces the splitting frequency by the method of dynamic changing node size. Finally, it reduces node update cost in all client buffers by the regional delayed update method. Experimental results show that, this method has high per- formance in cloud computing environments.

A Low Complexity Spatial Parameter Codec Algorithm in MDCT Domain

With stereo audio steping into peoples daily lives, spatial parametric technology comes to its broad prospects for development. Spatial parameteric technology is a method for stereo compression. MDCT is excluded in the current scheme for spatial cues representation,due to its lacking of phase information and energy conservation. In this paper, Construction of new spatial parameter codec framework in MDCT domain, and Optimization of calculating for the new module, to reduce computational complexity of the system. A Low Complexity Spatial Parameter Codec Algorithm in MDCT Domain was proposed to improve it. The MDCT-MDST conversion, in matrix form, is approximating to a banded sparse matrix. To compare with the EaacPlus system, this method avoids separate transforming for cues representation and saves significant computation, realizing low-complexity and high-efficiency spatial parameter codec, reducing 26.1% of operation complexity.

Feedback control with prediction for thread allocation in pipeline architecture web server

With the sharply development of high-speed backbone network and phenomenal growth of Web applications, many kinds of Web server structures have been advanced and implemented to increase the serving ability of Web server. In this paper, we propose a pipeline architecture multi-thread web server open KETA which divides the requests processing into several independent phases. This architecture reduces parallelism granularity and achieves inner-request parallelism to enhance its processing capability. Furthermore, a combined feed-forward/feedback model is designed to manage thread allocation in this special architecture. The feed-forward predictor relates instantaneous measurements of queue length and processing rate of each pipeline phase to the thread allocation over a finite prediction horizon. The feedback controller deals with the uncertainty the predictor brings and improves open KETAs performance farther. Experimental results show the capability of open KETA and the effectiveness of the thread allocation model.

Research on perceptible spatial information estimation based on spatial hearing theory

With stereo audio steping into peoples daily lives, spatial parametric technology comes to its broad prospects for development. Spatial parameteric technology is a method for stereo compression. In this paper, Construction of new spatial parameter perception two-dimensional model on perception spatial information estimation domain, and Optimization of calculating for the new module, to reduce computational complexity of the system. Spatial Perception Entropy was proposed to improve it. Its computation method which based on Just Noticeable Difference Model avoids separate transforming for cues representation and saves significant computation, optimizing spatial parameter selection and realizing high-efficiency spatial audio coding.