10444531
On using similarity for concurrency control in real-time database systems
Most of the proposed concurrency control protocols for real-time database systems (RTDBS) are based on serializability theorem. Owing to the unique characteristics of real-time database applications and the importance of satisfying the timing constraint of the transactions, serializable concurrency control protocols are not suitable for RTDBS for most cases. In this paper, another notion of correctness, similarity, is used for concurrency control in a RTDBS, for instance, a stock trading database system. Similarity is a less restrictive notion comparing with serializability. By studying the correctness requirements of the stock trading database applications, a real-time two phase locking protocol, High Priority 2 Phase Locking (H2PL) is re-defined based on similarity. Although the new protocol cannot ensure serializability, the concurrency of the system is higher and the amount of inconsistency in the database is tolerable. On the other hand, the performance of the whole system can be much improved.
16283914
Approaches for broadcasting temporal data in mobile computing systems
Abstract Rapid advances in mobile communication technology have spawned many new mobile applications. A key element in many of these systems is the need to distribute real-time information from a database server to mobile clients. While data broadcast has been shown to be an efficient data dissemination technique, many issues such as selection of broadcast data and caching strategies at mobile clients are still active research areas. In this paper, we consider an important characteristic of many mobile computing systems which has often been ignored in the design of broadcast algorithms: the fact that many data items are associated with temporal constraints on their validity. We introduce the notion of absolute validity interval (AVI) to capture the temporal constraints of the data items, formulate a temporal data model and examine both static and dynamic approaches to select data items based on their access frequencies as well as their AVI. The reason for considering the AVI of the data items in broadcast selection is to increase the client cache hit probability so that the access delay for a data item will be much reduced. Based on the results from extensive simulation experiments, it is concluded the AVI-based approaches, by improving cache hit probability, can significantly improve the mean response time and reduce the number of deadline missing requests.
8292420
Priority Scheduling of Transactions in Distributed Real-Time Databases
One of the most important issues in the design of distributed real-time database system (DRTDBS) is transaction scheduling which consists of two parts: priority scheduling and real-time concurrency control. In the past studies, mostly, these issues are studied separately although they have a very close interaction with each other. In this paper, we propose new priority assignment policies for DRTDBS and study their impact on two typical real-time concurrency control protocols (RT-CCPs), High Priority Two Phase Locking (HP-2PL) and Optimistic Concurrency Control with Broadcast Commit (OCC-BC). Our performance results show that many factors, such as data conflict resolution, degree of data contention and transaction restarts, that are unique to database systems, have significant impact on the performance of the policies which in turn affect the performance of the real-time concurrency control protocols. OCC-BC is more affected by the priority assignment policies than HP-2PL owing to the late detection of conflict. In the design of priority assignment policies, we have found that neither the purely deadline driven policies nor data contention driven policies are suitable for DRTDBS. Our proposed policy, the Mixed Method (MM), which considers both transaction timeliness and data contention, outperforms other policies over a wide range of system parameter settings.
39491407
Mobile Distributed Real-Time Database Systems
16685984
A multi-version data model for executing real-time transactions in a mobile environment
With the significant advances in mobile computing technology, there is an increasing demand for various mobile applications to process transactions in a real-time fashion. When remote data access is considered in a mobile environment, data access delay becomes one of the most serious problems in meeting transaction deadlines. In this paper, we propose a multi-version data model and adopt the relative consistency as the correctness criterion for processing of real-time transactions in a mobile environment. The purpose is to reduce the impacts of unpredictable and unreliable mobile network on processing of the real-time transactions. Under the proposed model, the overheads for concurrency control can be significantly reduced, and the data availability is much enhanced even under network failures. A real-time transaction may access stale data, provided that they are relatively consistent with the data accessed by the transaction, and the staleness of the data is within the requirements. An image transaction model, which pre-fetches multiple data versions at fixed hosts, is proposed to reduce the data access delay and to simplify the management of the real-time transactions in a mobile environment. The image transaction model also helps in reducing the transaction-restart overheads and minimizing the impacts of the unpredictable performance of mobile network on transaction executions.
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.
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.
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.
18244295
An efficient illumination normalization method for face recognition
In this paper, an efficient representation method insensitive to varying illumination is proposed for human face recognition. Theoretical analysis based on the human face model and the illumination model shows that the effects of varying lighting on a human face image can be modeled by a sequence of multiplicative and additive noises. Instead of computing these noises, which is very difficult for real applications, we aim to reduce or even remove their effect. In our method, a local normalization technique is applied to an image, which can effectively and efficiently eliminate the effect of uneven illuminations while keeping the local statistical properties of the processed image the same as in the corresponding image under normal lighting condition. After processing, the image under varying illumination will have similar pixel values to the corresponding image that is under normal lighting condition. Then, the processed images are used for face recognition. The proposed algorithm has been evaluated based on the Yale database, the AR database, the PIE database, the YaleB database and the combined database by using different face recognition methods such as PCA, ICA and Gabor wavelets. Consistent and promising results were obtained, which show that our method can effectively eliminate the effect of uneven illumination and greatly improve the recognition results.
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.
26133489
Robust 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 them 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 presented, which can achieve good matching, even in a noisy environment or with the existence of occlusion. We propose three different ways for forming the line segments for a point set. Two of the methods are based on a fixed reference point, which are the centroid and the center of the minimal disk of the point set. The third method is based on the longest possible line segments formed within the point set. The line features extracted based on the respective line segments are insensitive to noise and can be used to determine the rotation and scale of the image point set accurately and reliably, and more importantly, 2D-2D matching algorithm can be adopted. The first 2D-matching is to compute the relative scale and orientation between the two point sets. Having rotated and scaled the image point set, the M-Estimation Hausdorff distance is applied for the second 2D-matching to measure the relative translation between the query point set and the model point set. This 2D-2D matching can greatly reduce the required memory and computation when compared to a 4D-matching. Both the performance and the sensitivity to noise of our algorithms are evaluated using simulated data. Experiments show that our 2D-2D algorithms can yield a high level of performance when determining the scale, the orientation and the similarity of two point sets.