62523912
Concurrency control strategies for ordered data broadcast in mobile computing systems
Although data broadcast has been shown to be an efficient method for disseminating data items in mobile computing systems, the issue on how to ensure consistency and currency of data items provided to mobile transactions (MT), which are generated by mobile clients, has not been examined adequately. While data items are being broadcast, update transactions may install new values for them. If the executions of update transactions and the broadcast of data items are interleaved without any control, mobile transactions may observe inconsistent data values. The problem will be more complex if the mobile clients maintain some cached data items for their mobile transactions. In this paper, we propose a concurrency control method, called ordered update first with order (OUFO), for the mobile computing systems where a mobile transaction consists of a sequence of read operations and each MT is associated with a time constraint on its completion time. Besides ensuring data consistency and maximizing currency of data to mobile transactions, OUFO also aims at reducing data access delay of mobile transactions using client caches. A hybrid re-broadcast/invalidation report (IR) mechanism is designed in OUFO for checking the validity of cached data items so as to improve cache consistency and minimize the overhead of transaction restarts due to data conflicts. This is highly important to the performance of the mobile computing systems where the mobile transactions are associated with a deadline constraint on their completion times. Extensive simulation experiments have been performed to compare the performance of OUFO with two other efficient schemes, the multi-version broadcast method and the periodic IR method. The performance results show that OUFO offers better performance in most aspects, even when network disconnection is common.
61064863
Concurrency control in mobile distributed real-time database systems
Abstract With the rapid advances in mobile computing technology, there is an increasing demand for processing real-time transactions in a mobile environment. This paper studies concurrency control problem in mobile distributed real-time database systems (MDRTDBS). Based on the High Priority Two Phase Locking (HP-2PL) scheme, we propose a distributed real-time locking protocol, called Distributed High Priority Two Phase Locking (DHP-2PL), for MDRTDBS. In the protocol, the characteristics of a mobile computing system are considered in resolving lock conflicts. Two strategies are proposed to further improve the system performance and to reduce the impact of mobile network on the performance of the DHP-2PL: (1) A transaction shipping approach is proposed to process transactions in a mobile environment by exploring the well-defined behavior of real-time transactions. (2) We explore the application semantics of real-time database applications by adopting the notion of similarity in concurrency control to further reduce the number of transaction restarts due to priority inversion, which could be very costly in a mobile network. A detailed simulation model of a MDRTDBS has been developed, and a series of simulation experiments have been conducted to evaluate the performance of the proposed approaches and the effectiveness of using similarity for concurrency control in MDRTDBS.
17905998
Location update generation in cellular mobile computing systems
An important issue in the design of a mobile computing system is how to manage the real-time locations of mobile clients. In the existing commercial cellular mobile computing systems, a two-tier architecture is used (13). However, the two-tier architecture is not scalable and is not suitable to the new mobile computing applications. In the literatures (1, 12), a hierarchical database structure is proposed in which the location information of the mobile clients within a cell is managed by the location database responsible for the cell. The location databases of different cells are organized into a tree structure to facilitate the search of mobile clients. Although this architecture can distribute the update and searching workload amongst the location databases in the system, it has the problem of heavy location update overhead and long search delay. Thus, it is not suitable to the system which is supporting real-time queries. In this paper, we study how to generate location update in the distance-based update method. Two methods are proposed for calculating the optimal distance threshold with the objectives to minimize the total location management cost and the latency in searching the location of a mobile client.
32532096
A Priority Feedback Mechanism for Distributed MPEG Video Player Systems
In this paper, a priority feedback mechanism is proposed for adjusting the priorities of the processes dynamically in a video server according to the current status of the clients — the status can be reflected by the number of frames being dropped in a period of time. The priority feedback mechanism is implemented in a distributed MPEG video player system. Different priority mapping functions are suggested for the priority feedback mechanism to cater for different service requirements of the clients, especially when the clients are demanding different quality of services. Experiment results have shown that when the video server is serving several clients where every client may demand a play speed of their own, the use of the priority feedback mechanism can effectively improve the whole system performance.
909685
Enhanced multi-version data broadcast schemes for time-constrained mobile computing systems
We study the data dissemination problem in time-constrained mobile computing systems (TCMCS) in which maximizing data currency (minimizing staleness) and meeting transaction deadlines are of equal importance as providing consistent data items to transactions. We first investigate what are the performance problems of the multi-version data (MV) broadcast technique when it is used for TCMCS. Then, we propose various enhancements to resolve the problems. In order to further reduce the probability of missing deadlines, we introduce a prioritized on-demand broadcast scheme, which is integrated with the data broadcast mechanism for disseminating data items to time-constrained transactions. The performance characteristics of the proposed strategies have been studied through extensive simulation.
38983149
READS: a prototyping environment for real-time active applications
We present our Real-time Active Database System, READS, which is a prototyping environment for real-time active database applications on a conventional Unix environment, e.g., Solaris 2.4. In READS, transactions are associated with deadlines and priorities. Priority scheduling is supported by the real-time extensions provided in the underlying operating system. READS can be served as a testbed for evaluating different issues in the design of real-time active database systems (RTADBS). Different approaches for assigning deadlines and priorities to triggered transactions have been suggested and discussed. An application, the programmed trading database system, is implemented with READS and experiments have been performed to study the impact of the deadline constraints on the performance of the deferred and immediate coupling modes for triggering.
15640953
Frequency layered color indexing for content-based image retrieval
Image patches of different spatial frequencies are likely to have different perceptual significance as well as reflect different physical properties. Incorporating such concept is helpful to the development of more effective image retrieval techniques. We introduce a method which separates an image into layers, each of which retains only pixels in areas with similar spatial frequency characteristics and uses simple low-level features to index the layers individually. The scheme associates indexing features with perceptual and physical significance thus implicitly incorporating high level knowledge into low level features. We present a computationally efficient implementation of the method, which enhances the power and at the same time retains the simplicity and elegance of basic color indexing. Experimental results are presented to demonstrate the effectiveness of the method.
2162231
A Robust Line-Feature-Based Hausdorff Distance for Shape Matching
The Hausdorff distance can be used to measure the similarity of two point sets. In matching the two point sets. one of the point sets is translated. rotated and scaled in order to obtain an optimal matching. which is a computationally intensive process. In this paper, a robust line-feature-based approach for model-based recognition is proposed. which can achieve a good performance level in matching, even in a noisy environment or with the existence of occlusion. The method is insensitive to noise and can find the rotation and scale of the image point set accurately and reliably. For this reason, instead of 4D matching, a 2D-2D matching algorithm can be used. This can greatly reduce the required memory and computation. Having rotated and scaled the image point set, the difference between the query point set and the model point set can be computed by considering translation only. The performance and the sensitivity to noise of our algorithm are evaluated using simulated data. Experiments show that our 2D-2D algorithm can give a high performance level when determining the relative scale and orientation of two point sets.
17076982
A new key frame representation for video segment retrieval
In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video shot. Therefore, this constructed key frame is called temporally maximum occurrence frame (TMOF), which is an optimal representation of all the frames in a video shot. The retrieval performance of this representation scheme is further improved by considering the k pixel values with the largest probabilities of occurrence and the highest peaks of the probability distribution of occurrence at each pixel position for a video shot. The corresponding schemes are called k-TMOF and k-pTMOF, respectively. These key frame representation schemes are compared to other histogram-based techniques for video shot representation and retrieval. In the experiments, three video sequences in the MPEG-7 content set were used to evaluate the performances of the different key frame representation schemes. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval.
14714935
An efficient low bit-rate video-coding algorithm focusing on moving regions
Block-based motion estimation and compensation are the most popular techniques for video coding. However, as the shape and the structure of an object in a picture are arbitrary, the performance of such conventional block-based methods may not be satisfactory. In this paper, a very low bit-rate video coding algorithm that focuses on moving regions is proposed. The aim is to improve the coding performance, which gives better subjective and objective quality than that of the conventional coding methods at the same bit rate. Eight patterns are pre-defined to approximate the moving regions in a macroblock. The patterns are then used for motion estimation and compensation to reduce the prediction errors. Furthermore, in order to increase the compression performance, the residual errors of a macroblock are rearranged into a block with no significant increase of high-order DCT coefficients. As a result, both the prediction efficiency and the compression efficiency are improved.
39178482
Illumination invariant face recognition
The appearance of a face will vary drastically when the illumination changes. Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, we propose a novel approach to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image between the face image and a reference face image, both of which are blurred by a Gaussian filter. An iterative algorithm is then used to update the reference image, which is reconstructed from the restored image by means of principal component analysis (PCA), in order to obtain a visually better restored image. Image processing techniques are also used to improve the quality of the restored image. To evaluate the performance of our algorithm, restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that face recognition using our method can achieve a higher recognition rate based on the Yale B database and the Yale database. Our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions, (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations, and (3) it does not need to detect accurate positions of some facial feature points or to warp the image for alignment, etc.