29622238
Optimistic concurrency control protocol for real-time databases
In recent years, the use of optimistic schemes for concurrency control in real-time database systems (RTDBS) has received more and more attention. Different real-time optimistic protocols have been proposed. They incorporate different priority conflict resolution methods into the validation phase of a transaction to give preferences for the commitment of higher priority transactions. However, some of these protocols suffer from the problem of heavy restart overheads. Restarting near-to-complete transactions greatly increases the system workload and the deadline missing probability of the transactions (Haritsa et al., 1992; Huang, 1991). In order to reduce the number of restarts, dynamic adjustment of the serialization order of the conflicting transactions has been suggested using timestamp intervals to record the transactions' serialization constraints (Lee and Son, 1993a, 1993b; Lee, 1994). However, these kinds of protocols have the problem of heavy implementation overheads as the timestamp intervals have to be checked and updated in case of any conflict even though the transactions are still in their read phases (Lee, 1994). In this paper, we propose a new real-time optimistic protocol which employs the notion of dynamic adjustment of serialization order by backward-adjusting the non-serious conflicting transactions before the committing transactions so that many restarts can be eliminated. In the protocol, the overhead to support dynamic adjustment of serialization order is small. All checking is performed at the validation test of a transaction so as to provide more freedom for the adjustments. No conflict and serialization constraints have to be recorded during the read phase of a transaction. Performance studies of the proposed protocol by varying different parameters indicate that it outperforms other protocols.
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.
39491407
Mobile Distributed Real-Time Database Systems
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.
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.
17018329
An efficient method for generating location updates for processing of location-dependent continuous queries
Recent advances in mobile computing and mobile communication technology have led to the emergence of many innovative mobile computing applications. Some of them require providing support to location-dependent continuous queries (LDCQs) on moving objects. The result of a location-dependent query depends on the current locations of the moving objects. When the query is specified as continuous, the requesting client can get continuously changing results. In order to provide correct and timely results to requesting clients, the locations of moving objects have to be closely monitored. In this paper, we propose an adaptive monitoring method (AMM) for managing the locations of moving objects to maintain the correctness of the results of query evaluation without significantly increasing the wireless bandwidth requirements. Extensive simulation experiments have been conducted to investigate the performance of the proposed method as compared to plain dead-reckoning (PDR).
18536131
An efficient color compensation scheme for skin color segmentation
Skin color is a useful means for human face detection. In this paper, we propose an efficient color compensation method for skin color segmentation under varying lighting conditions. One of the major problems of using skin color is that a face region may not be detected under poor or uneven lighting conditions. Our approach considers the distribution of the color components of skin pixels and the color response of capturing machines under different illuminations. Experimental results show that this algorithm can improve the performance of face segmentation under poor or strong lighting conditions.
10239266
Scene cut detection using the colored pattern appearance model
In this paper, we propose to use the colored pattern appearance model (CPAM) as a content representation for video scene break detection. This model represents a scene by means of global statistics of the local visual appearance, and was originally motivated by studies in human color vision. The performance of this method is compared to several histogram-based approaches. An adaptive thresholding technique, namely entropic thresholding, is applied to determine the respective optimal threshold values for each of the approaches. In the experiments, the two video sequences in the MPEG-7 content set are used to evaluate the performances of the CPAM and the histogram-based methods. Experimental results show that our proposed model outperforms other histogram-based approaches in scene break detection.
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.
5051365
Promising Approach to Distributed Query Processing
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.