基于不精确计算移动实时数据库服务质量管理

移动实时数据库服务应用逐渐广泛,但系统负载不可预测和有限资源常导致事务重启或夭折,给系统带来损失甚至灾难。传统的基于最长执行时间实时调度算法已不能满足性能要求,提出结合不精确计算和反馈控制的新算法。考虑更新数据对象间联系并结合时间和值域有效性,提出性能新参数标准去保证系统性能和服务质量。通过仿真实验表明：算法可从稳定性能和暂态性能保证系统预定的服务质量规范。     

Improving transient performance of adaptive control architectures using frequency-limited system error dynamics

Although adaptive control theory offers mathematical tools to achieve system performance without excessive reliance on dynamical system models, its applications to safety-critical systems can be limited due to poor transient performance and robustness. In this paper, we develop an adaptive control architecture to achieve stabilisation and command following of uncertain dynamical systems with improved transient performance. Our framework consists of a new reference system and an adaptive controller. The proposed reference system captures a desired closed-loop dynamical system behaviour modified by a mismatch term representing the high-frequency content between the uncertain dynamical system and this reference system, i.e., the system error. In particular, this mismatch term allows the frequency content of the system error dynamics to be limited, which is used to drive the adaptive controller. It is shown that this key feature of our framework yields fast adaptation without incurring high-frequency oscillations in the transient performance. We further show the effects of design parameters on the system performance, analyse closeness of the uncertain dynamical system to the unmodified (ideal) reference system, discuss robustness of the proposed approach with respect to time-varying uncertainties and disturbances, and make connections to gradient minimisation and classical control theory. A numerical example is provided to demonstrate the efficacy of the proposed architecture.     

Evaluation of concurrency control strategies for mixed soft real-time database systems

Previous research in real-time concurrency control mainly focuses on the schedulability guarantee of hard real-time transactions and the reduction of the miss rate of soft real-time transactions. Although many new database applications have significant response time requirements, not much work has been done in the joint scheduling of traditional non-real-time transactions and soft real-time transactions. In this paper, we study the concurrency control problems in mixed soft real-time database systems, in which both non-real-time and soft real-time transactions exist simultaneously. The objectives are to identify the cost and the performance tradeoff in the design of cost-effective and practical real-time concurrency control protocols, and to evaluate their performance under different real-time and non-real-time supports. In particular, we are interested in studying the impacts of different scheduling approaches for soft real-time transactions on the performance of non-real-time transactions. Instead of proposing yet another completely new real-time concurrency control protocol, our objective is to design an efficient integrated concurrency control method based on existing techniques. We propose several methods to integrate the well-known two phase locking and optimistic concurrency control with the aims to meet the deadline requirements of soft real-time transactions and, at the same time, to minimize the impact on the performance of non-real-time transactions. We have conducted a series of experiments based on a sanitized version of stock trading systems to evaluate the performance of both soft real-time and non-real-time transactions under different real-time supports in the system.     

Novel scheduling policies in real-time multithread control system design

In this paper soft real-time scheduling approaches (Resource Reservations) are applied to multithread digital control design and implementation. The advantage of this choice is the possibility of raising the sampling frequencies beyond the hard real-time boundaries, while retaining control on the transient overloads. An important component of the proposed framework is a simulation tool, which allows for a fine tuning of the scheduling parameters. Experimental and simulation results on two case studies show a significant performance improvement with respect to hard real-time scheduling, especially when the feedback controller operates on dataflows requiring statistically widespread computation times.     

Robust fuzzy CPU utilization control for dynamic workloads

In a number of real-time applications such as target tracking, precise workloads are unknown a priori but may dynamically vary, for example, based on the changing number of targets to track. It is important to manage the CPU utilization, via feedback control, to avoid severe overload or underutilization even in the presence of dynamic workloads. However, it is challenge to model a real-time system for feedback control, as computer systems cannot be modeled via physics laws. In this paper, we present a novel closed-loop approach for utilization control based on formal fuzzy logic control theory, which is very effective to support the desired performance in a nonlinear dynamic system without requiring a system model. We mathematically prove the stability of the fuzzy closed-loop system. Further, in a real-time kernel, we implement and evaluate our fuzzy logic utilization controller as well as two existing utilization controllers based on the linear and model predictive control theory for an extensive set of workloads. Our approach supports the specified average utilization set-point, while showing the best transient performance in terms of utilization control among the tested approaches.     

Competitive online adaptive scheduling for sets of parallel jobs with fairness and efficiency

We study online adaptive scheduling for multiple sets of parallel jobs, where each set may contain one or more jobs with time-varying parallelism. This two-level scheduling scenario arises naturally when multiple parallel applications are submitted by different users or user groups in large parallel systems, where both user-level fairness and system-wide efficiency are of important concerns. To achieve fairness, we use the well-known equi-partitioning algorithm to distribute the available processors among the active job sets at any time. For efficiency, we apply a feedback-driven adaptive scheduler that periodically adjusts the processor allocations within each set by consciously exploiting the jobs’ execution history. We show that our algorithm achieves asymptotically competitive performance with respect to the set response time, which incorporates two widely used performance metrics, namely, total response time and makespan, as special cases. Both theoretical analysis and simulation results demonstrate that our algorithm improves upon an existing scheduler that provides only fairness but lacks efficiency. Furthermore, we provide a generalized framework for analyzing a family of scheduling algorithms based on feedback-driven policies with provable efficiency. Finally, we consider an extended multi-level hierarchical scheduling model and present a fair and efficient solution that effectively reduces the problem to the two-level model.     

Optimizing the radio resource utilization of multiaccess systems with a traffic-transmission quality adaptive packet scheduling

In this paper we state a general framework for radio resource allocation based on a matrix which highlights the trade-offs of complexity and efficiency. This framework is outlined for the systematic definition of scheduling algorithms that are jointly adaptive to traffic and to transmission quality in order to improve the radio resource utilization and the achievable throughput of cellular networks for the support of best-effort traffic. We consider the application of the matrix concept to both time division and code division multiple access, the latter scheme also bringing about mutual interference among competing users. Then we propose a scheduling algorithm for wireless systems, called channel adaptive open scheduling (CHAOS). The CHAOS performance in terms of throughput and delay is extensively compared with those resulting from a load adaptive channel independent scheduling (CIS). A major result of this work is the quantitative assessment of the performance advantage allowed by jointly accounting for traffic congestion and transmission quality. Moreover the main implementation issues related to the proposed algorithms are investigated.     

A formally verified application-level framework for real-time scheduling on POSIX real-time operating systems

We present a framework, called meta scheduler, for implementing real-time scheduling algorithms. The meta scheduler is a portable middleware layer component designed for implementations over POSIX-compliant operating systems. It accommodates pluggable real-time scheduling algorithms while offering the flexibility of platform independence - the singular underlying OS requirement is the now nearly ubiquitous POSIX compliance. The versatility of pluggable schedulers positions the meta scheduler for deployment in an interoperable heterogeneous real-time environment. We present the design of the meta scheduler and outline its implementation. Furthermore, we present a mechanized correctness verification using the UPPAAL model checker. Prototype implementation of the meta scheduler over QNX Neutrino real-time operating system demonstrates high performance and a small footprint.     

Mobile agent-enabled framework for structuring and building distributed systems on the internet

Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of proc- essing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel ap- proach to detecting deadlocks in distributed system by using mobile agents, which dem- onstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD (Mobile Agent Enabled Deadlock Detection) scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detec- tion strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.     

Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance

In order to accommodate actuator failures which are uncertain in time, pattern and value, we propose two adaptive backstepping control schemes for parametric strict feedback systems. Firstly a basic design scheme on the basis of existing approaches is considered. It is analyzed that, when actuator failures occur, transient performance of the adaptive system cannot be adjusted through changing controller design parameters. Then we propose a new controller design scheme based on a prescribed performance bound (PPB) which characterizes the convergence rate and maximum overshoot of the tracking error. It is shown that the tracking error satisfies the prescribed performance bound all the time. Simulation studies also verify the established theoretical results that the PPB based scheme can improve transient performance compared with the basic scheme, while both ensure stability and asymptotic tracking with zero steady state error in the presence of uncertain actuator failures.