40821829
Service class based online QoS management in surveillance radar systems
Many application level qualities are functions of available computation resources. Recent studies have handled the computation resource allocation problem to maximize the overall application quality. However such QoS problem is fundamentally a multi-dimensional optimization problem that requires extensive computation. Therefore, online usage of optimization procedures may significantly reduce the computation resource available for applications. This raises the question of how to best use the optimization procedures for dynamic real-time task sets. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. A simplified radar application is used as an illustrative example.
7460330
Enhanced analysis of cache-related preemption delay in fixed-priority preemptive scheduling
We propose an enhanced technique for analyzing, and thus bounding cache related preemption delay in fixed priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache related preemption delay. Second, the technique considers phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache related preemption delay. The paper also compares the proposed technique with previous techniques. The results show that the proposed technique gives up to 60% tighter prediction of the worst case response time than the previous techniques.
195349457
Analysis of cache-related preemption delay in fixed-priority preemptive scheduling
We propose a technique for analyzing cache-related preemption delays of tasks that cause unpredictable variation in task execution time in the context of fixed-priority preemptive scheduling. The proposed technique consists of two steps. The first step performs a per-task analysis to estimate cache-related preemption cost for each execution point in a given task from the number of useful cache blocks at the execution point. The second step computes the worst case response time of each task using a response time equation and a linear programming technique which takes as its input the preemption cost information of tasks obtained in the first step. Our experimental results show that the proposed technique gives a prediction of the worst case cache-related preemption delay that is up to 60% tighter than that obtained from previous approaches.
17289303
Spare CASH: reclaiming holes to minimize aperiodic response times in a firm real-time environment
Scheduling periodic tasks that allow some instances to be skipped produces spare capacity in the schedule. Only a fraction of this spare capacity is uniformly distributed and can easily be reclaimed for servicing aperiodic requests. The remaining fraction of the spare capacity is non-uniformly distributed, and no existing technique has been able to reclaim it. We present a method for improving the response times of aperiodic tasks by identifying the non-uniform holes in the schedule and adding these holes as extra capacity to the capacity queue of the CASH mechanism. The non-uniform holes can account for a significant portion of spare capacity, and reclaiming this capacity results in considerable improvements to aperiodic response times.
42435746
Efficiently supporting hard/soft deadline transactions in real-time database systems
As in other application areas, there is an increasing need for managing a large amount of data in the real-time area. This need gave birth to a system called a real-time database system (RTDBS) that provides database operations with timing constraints. One typical timing constraint in an RTDBS is temporal consistency that states that a transaction must read temporally valid data objects. This requires the data objects to be updated repeatedly. This paper proposes three novel schemes that aim to minimize the number of updates of data objects needed for guaranteeing the temporal consistency requirements of transactions with hard-deadlines. The three guarantee schemes differ from each other in the amount of updates and the implementation complexity. This paper also gives a framework for integrating transactions with soft-deadlines into the three guarantee schemes.
16132542
Stochastic analysis of periodic real-time systems
This paper describes a stochastic analysis method for general periodic real-time systems. The proposed method accurately computes the response time distribution of each task in the system, thus making it possible to determine the deadline miss probability of individual tasks, even for systems with maximum utilization factor greater than one. The method uniformly covers both fixed-priority scheduling (such as rate monotonic) as well as dynamic-priority scheduling (such as earliest deadline first) and can handle arbitrary relative deadlines and execution time distributions. The accuracy of the method is proven by comparing the results from the analysis with those obtained from simulations, as well as other methodologies in the literature.
14489935
Dynamic resource allocation for CDMA-TDD indoor wireless systems
Future wireless communication systems are expected to provide a broad range of multimedia services that have a significant traffic asymmetry between uplink and downlink. The code division multiple access-time division duplex (CDMA-TDD) system is a promising solution to cope with the problem of traffic asymmetry. However, the TDD system is subject to inter-cell interference compared to frequency division duplex (FDD) system. Since both uplink and downlink share the same frequency in TDD, uplink and downlink may interfere each other especially when neighboring cells require different rates of traffic load. Thus, the resource allocation among cells is an important issue in TDD. In this paper, the resource allocation in the CDMA-TDD is formulated as a mixed integer programming (MIP) problem. A dynamic resource allocation algorithm (DRAA) is provided that effectively solves the traffic asymmetry problem. The MIP problem is also solved by a well-known branch and bound procedure. Both the crossed slot and non-crossed slot allocation are examined and compared to the DRAA. Computational result shows that proposed DRAA gives a good performance as the traffic asymmetry increases between the uplink and downlink. Copyright Â© 2003 John Wiley & Sons, Ltd.
3020567
Automatic recognition of animal vocalizations using averaged MFCC and linear discriminant analysis
In this paper we propose a method that uses the averaged Mel-frequency cepstral coefficients (MFCCs) and linear discriminant analysis (LDA) to automatically identify animals from their sounds. First, each syllable corresponding to a piece of vocalization is segmented. The averaged MFCCs over all frames in a syllable are calculated as the vocalization features. Linear discriminant analysis (LDA), which finds out a transformation matrix that minimizes the within-class distance and maximizes the between-class distance, is utilized to increase the classification accuracy while to reduce the dimensionality of the feature vectors. In our experiment, the average classification accuracy is 96.8% and 98.1% for 30 kinds of frog calls and 19 kinds of cricket calls, respectively.
12690340
A knowledge-based approach to citation extraction
Integration of the bibliographical information of scholarly publications available on the Internet is an important task in academic research. To accomplish this task, accurate reference metadata extraction for scholarly publications is essential for the integration of information from heterogeneous reference sources. In this paper, we propose a knowledge-based approach to literature mining and focus on reference metadata extraction methods for scholarly publications. We adopt an ontological knowledge representation framework called INFOMAP to automatically extract the reference metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different reference styles with a high degree of accuracy. The overall average field accuracy of citation extraction for a bioinformatics dataset is 97.87% for six reference styles.
3500682
Kernels in planar digraphs
A set S of vertices in a digraph D=(V,A) is a kernel if S is independent and every vertex in V-S has an out-neighbor in S. We show that there exist O(n2^1^9^.^1^k+n^4)-time and O(k^3^6+2^1^9^.^1^kk^9+n^2)-time algorithms for checking whether a planar digraph D of order n has a kernel with at most k vertices. Moreover, if D has a kernel of size at most k, the algorithms find such a kernel of minimal size.
31930663
Minimization of resource consumption for multidatabase query optimization
Due to the autonomy of individual databases, a multidatabase system (MDBS) has no control over the task execution within each database system. This complicates the issue of query optimization in a MDBS. Past researchers tackled this problem mainly by regenerating the cost model of each participating database systems. However a completely autonomous participating database system does nor own the information (data) as well as the mechanism (software) for converting data of one database to another to resolve the data type conflict problems that can occur in any MDBS environment. In addition, unpredictable factors that can drastically deviate the accuracy of a regenerated cost model (in the past research) come into play at unknown time. This confines the processing of an intersite operation (such as a join over two relations of different databases) to the MDBS only. The participating database systems will not be able to share the workload of the MDBS under this circumstance. Hence, minimizing the consumption of system resources of the MDBS is an urgent problem. The authors propose three scheduling algorithms that are used in the MDBS to reduce the processing cost of a multidatabase query. A major difference between the strategies and the past methods is that ours do not require the knowledge of the cost models of the participating databases.