Hao-Ping Hung

Versatile Transcoding Proxy for Internet Content Adaptation

Recent technology advances in multimedia communication have ushered in a new era of personal communication. Users can ubiquitously access the Internet via various mobile devices. For the mobile devices featured with lower bandwidth network connectivity, transcoding can be used to reduce the object size by lowering the quality of a multimedia object. In view of the monolithic transcoders which only provide transcoding services and have limited performances due to the unknown data types and protocols in the prior research, we propose the architecture of versatile transcoding proxy (VTP). Based on the concept of the agent system, the VTP architecture can accept and execute the transcoding preference script provided by the client or the server to transform the corresponding data or protocol according to the users specification. In order to enhance the effectiveness of the VTP architecture, we adopt the concept of dynamic cache categories and propose the scheme maximum profit replacement with dynamic cache categories (DCC-MPR). Based on the weighted transcoding graph, scheme DCC-MPR performs cache replacement according to the content in the caching candidate set, which is generated by the concept of dynamic programming. The experimental results show that the proposed architecture VTP and the corresponding scheme DCC-MPR have better performances in many aspects compared to the conventional transcoding proxy systems.

A QoS-aware transcoding proxy using on-demand data broadcasting

The high diversity in the capabilities of various mobile devices such as display capabilities and computation power makes the design of mobile information systems more challenging. A transcoding proxy is placed between a client and an information server to coordinate the mismatch between what the server provides and what the client prefers. However, most research works in transcoding proxies in mobile computing environments are under the traditional client-server architecture and do not employ the data broadcast technique which is has been deemed a promising technique to design a power conservation, high scalable and high band-width utilization. In addition, the issue of QoS provision is also not addressed. In view of this, we design in this paper a QoS-aware transcoding proxy by utilizing the on-demand broadcasting technique. We first propose a QoS-aware transcoding proxy architecture, abbreviated as QTP, and model it as a queueing network. By analyzing the queueing network, several theoretical results are derived. We then propose a version decision policy and a service admission control scheme to provide QoS in QTP. The derived results are used to guide the execution of the proposed version decision policy and service admission control scheme to achieve the given QoS requirement. To measure the performance of QTP, several experiments are conducted. Experimental results show that the proposed scheme is more scalable than traditional client-server systems. In addition, the proposed scheme is able to effectively control the system load to attain the desired QoS

On Channel Allocation for Heterogeneous Data Broadcasting

We explore in this paper the problem of generating broadcast programs in a heterogeneous data broadcasting environment, in which disseminated data items can be of different sizes. Given the broadcast database and the number of channels, we first derive the analytical model of the heterogeneous data broadcasting to obtain the average waiting time of mobile users, and prove the allocation problem as an NP-complete problem. In order to solve such problem, we propose a two-phase architecture to perform channel allocation. Algorithm DRP (dimension reduction partitioning) is employed to perform rough allocation to derive the satisfactory solutions, whereas mechanism CDMS (cost-diminishing movement selection) is used for fine allocation to achieve local optimum solutions. In addition, we also propose algorithm GA-CDMS according to the concept of hybrid genetic algorithm for comparison purposes. GA-CDMS can perform global search more accurately and efficiently than conventional genetic algorithm GA and the suboptimum that GA-CDMS achieves will be very close to the optimal solution. In the experiments, we consider the important issues such as accuracy, scalability, diversity and the efficiency. From the experimental results, we show that the proposed two-phase channel allocation is very practical in performing an effective channel allocation with high efficiency in a heterogeneous broadcasting environment.

On Exploring Channel Allocation in the Diverse Data Broadcasting Environment

In recent years, data broadcasting becomes a promising technique to design a mobile information system with power conservation, high scalability and high bandwidth utilization. However, prior research topics in data broadcasting are mainly based on the assumption that the disseminated data items are of the same size. We explore in this paper the problem of generating broadcast programs in a diverse data broadcasting environment, in which disseminated data items can be of different sizes. Given the broadcast database and the channel number, we propose algorithms DRP (dimension reduction partitioning) to perform the channel allocation for each data item. Moreover, a cost-diminishing selection mechanism is also used to help DRP achieve the local optimum with low complexity. With the capability of generating effective broadcast programs efficiently, the proposed mechanism can be practically used in a diverse data broadcasting environment

Efficient range-constrained similarity search on wavelet synopses over multiple streams

Due to the resource limitation in the data stream environment, it has been reported that answering user queries according to the wavelet synopsis of a stream is an essential ability of a Data Stream Management System (DSMS). In this paper, motivated by the fact that a user may be interested in an arbitrary range of the data streams, we investigate two important types of range-constrained queries in time series streaming environments: the distance queries (which aim at obtaining the Euclidean distance between two streams) and the kNN queries (which aim at discovering k nearest neighbors to a reference stream). To achieve high efficiency in processing these two types of queries, we propose procedure RED (standing for Range-constrained Euclidean Distance) and algorithm EKS (standing for Enhanced KNN Search). Compared to the existing methods in the prior research, the advantageous features of our approaches are in two folds. First, our approaches are capable of processing the queries directly from the wavelet synopses retained in the main memory without using IDWT to reconstruct the data cells. This feature allows us to save the complexity in both memory and time. Moreover, our approaches enable the users to query the DSMS within their range of interest. Unlike the conventional methods which only support the full-range query processing, this feature will enhance the flexibility at the client side. We evaluate procedure RED and algorithm EKS on live and synthetic datasets empirically and show that the proposed approaches are efficient in similarity search and kNN discovery within arbitrary ranges in the time series streaming environments.

A general model of hybrid data dissemination

Hybrid data dissemination, which combines the push-based (i.e., broadcast) and pull-based (i.e., on-demand) data delivery, is the most common technique to deliver information in a mobile computing system. Most of the prior works in hibrid dissemination are based on the assumption that each delivered data item is of the same size. However, in the modern communication environment in which various information is delivered, the conventional dissemination schemes suffer from the efficiency issues. In this paper, we consider a general model of hybrid data dissemination, in which each data item is allowed to have an arbitrary size. The analytical model MGBC (Model of General Broadcast Channels) and MGOD (Model of General On-demand Channels) are first proposed to describe the broadcast and on-demand channels, respectively. In addition, the scheme GDS (General Dissemination Scheme) is adopted to perform the channel allocation and the data classification. Experimental results show that the proposed approach gives a near-optimal solution in achieving the minimun access time in the general dissemination environment.

Variant Bandwidth Channel Allocation in the Data Broadcasting Environment

Data broadcast is a technique to realize energy saving and bandwidth utilization in a mobile computing environment. However, traditional schemes schedule data items without considering channel bandwidth. Therefore, the above drawback leads to the unfair broadcasting rate of each item of the different access frequency. In this paper, we address the problem of generating a broadcast program to disseminate data via multiple channels with variant bandwidth. In view of the characteristics of variant bandwidth, we propose an algorithm using adaptive partition on bandwidth to generate broadcast program to avoid the above drawback so as to minimize the average waiting time. The empirical results show that our approach is able to produce broadcast programs of high quality and is very efficient in a data broadcasting environment with variant bandwidth.

MULS: A General Framework of Providing Multilevel Service Quality in Sequential Data Broadcasting

In recent years, data broadcasting becomes a promising technique to design a mobile information system with power conservation, high scalability and high bandwidth utilization. In many applications, the query issued by a mobile client corresponds to multiple items which should be accessed in a sequential order. In this paper, we study the scheduling approach in such a sequential data broadcasting environment. Explicitly, we propose a general framework referred to as MULS (standing for MUlti-Level Service) for an information system. There are two primary stages in MULS: on-line scheduling and optimization procedure. In the first stage, we propose an On- Line Scheduling algorithm (denoted by OLS) to allocate the data items into multiple channels. As for the second stage, we devise an optimization procedure SCI, standing for Sampling with Controlled Iteration, to enhance the quality of broadcast programs generated by algorithm OLS. Procedure SCI is able to strike a compromise between effectiveness and efficiency by tuning the control parameters. According to the experimental results, we show that algorithm OLS with procedure SCI outperforms the approaches in prior works prominently in both effectiveness (i.e., the average access time of mobile users) and efficiency (i.e., the complexity of the scheduling algorithm). Therefore, by cooperating algorithm OLS with procedure SCI, the proposed MULS framework is able to generate broadcast programs with flexibility of providing different service qualities under different requirements of effectiveness and efficiency: in the dynamic environment in which the access patterns and information contents change rapidly, the parameters used in SCI will perform online scheduling with satisfactory service quality. As for the static environment in which the query profile and the database are updated infrequently, larger values of parameters are helpful to generate an optimized broadcast program, indicating the advantageous feature of MULS.

A General Framework of Time-Variant Bandwidth Allocation in the Data Broadcasting Environment

Data broadcast is an advanced technique to realize large scalability and bandwidth utilization in a mobile computing environment. In this environment, the channel bandwidth of each channel is variant with time in real cases. However, traditional schemes do not consider time-variant bandwidth of each channel to schedule data items. Therefore, the above drawback degrades the performance in generating broadcast programs. In this paper, we address the problem of generating a broadcast program to disseminate data via multiple channels of time-variant bandwidth. In view of the characteristics of time-variant bandwidth, we propose an algorithm using adaptive allocation on time-variant bandwidth to generate the broadcast program to avoid the above drawback to minimize average waiting time. Experimental results show that our approach is able to generate the broadcast programs with high quality and is very efficient in a data broadcasting environment with the time-variant bandwidth.

On designing a shortest-path-based cache replacement in a transcoding proxy

The technology advance in network has accelerated the development of multimedia applications over the wired and wireless communication. To alleviate network congestion and to reduce latency and workload on multimedia servers, the concept of multimedia proxy has been proposed to cache popular contents. Caching the data objects can relieve the bandwidth demand on the external network, and reduce the average time to load a remote data object to local side. Since the effectiveness of a proxy server depends largely on cache replacement policy, various approaches are proposed in recent years. In this paper, we discuss the cache replacement policy in a multimedia transcoding proxy. Unlike the cache replacement for conventional web objects, to replace some elements with others in the cache of a transcoding proxy, we should further consider the transcoding relationship among the cached items. To maintain the transcoding relationship and to perform cache replacement, we propose in this paper the RESP framework (standing for REplacement with Shortest Path). The RESP framework contains two primary components, i.e., procedure MASP (standing for Minimum Aggregate Cost with Shortest Path) and algorithm EBR (standing for Exchange-Based Replacement). Procedure MASP maintains the transcoding relationship using a shortest path table, whereas algorithm EBR performs cache replacement according to an exchanging strategy. The experimental results show that the RESP framework can approximate the optimal cache replacement with much lower execution time for processing user queries.