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An Asynchronous Spectrum Sensing Period Optimization Model and Adaptive Fuzzy Adjustment Algorithm

Guo Cai-li Zeng Zhi-min Feng Chun-yan Liu Zi-qi,

电子与信息学报 , 2009,
Abstract: Based on the analysis of primary users' spectrum-usage characteristics, an asynchronous sensing period optimal model on minimal costs of channels is presented, and an Adaptive Fuzzy Adjustment Algorithm (AFAA) of spectrum sensing period is proposed for time-varying spectrum-usage characteristics. The AFAA can adjust sensing period adaptively in real time using fuzzy logic with parameters optimization. Experimental results show that the AFAA is effective under many kinds of situations where spectrum-usage pr...
Adaptive Fixed Priority End-To-End Imprecise Scheduling In Distributed Real Time Systems  [PDF]
W. El-Haweet,Islam Elgedawy,Ibrahim Abd El-Salam
Computer Science , 2013,
Abstract: In end-to-end distributed real time systems, a task may be executed sequentially on different processors. The end-toend task response time must not exceed the end-to-end task deadline to consider the task a schedulable task. In transient over load periods, deadlines may be missed or processors may saturate. The imprecise computation technique is a way to overcome the mentioned problems by trading off precision and timeliness. We developed an imprecise integrated framework for scheduling fixed priority end-to-end tasks in distributed real time systems by extending an existing integrated framework for the same problem. We devised a new priority assignment scheme called global mandatory relevance scheme to meet the concept of imprecise computation. We devised an algorithm for processor utilization adjustment, this algorithm decreases the processor load when the processor utilization is greater than one. Also we extended the schedulability analysis algorithms presented in the old framework to allow adaptive priority assignment and to meet imprecise computation concept. Simulation results showed that our new framework is more dependable and predictable than the existing framework over transient overload periods.
Adaptive Network Coding for Scheduling Real-time Traffic with Hard Deadlines  [PDF]
Lei Yang,Yalin Evren Sagduyu,Jason Hongjun Li,Junshan Zhang
Computer Science , 2012,
Abstract: We study adaptive network coding (NC) for scheduling real-time traffic over a single-hop wireless network. To meet the hard deadlines of real-time traffic, it is critical to strike a balance between maximizing the throughput and minimizing the risk that the entire block of coded packets may not be decodable by the deadline. Thus motivated, we explore adaptive NC, where the block size is adapted based on the remaining time to the deadline, by casting this sequential block size adaptation problem as a finite-horizon Markov decision process. One interesting finding is that the optimal block size and its corresponding action space monotonically decrease as the deadline approaches, and the optimal block size is bounded by the "greedy" block size. These unique structures make it possible to narrow down the search space of dynamic programming, building on which we develop a monotonicity-based backward induction algorithm (MBIA) that can solve for the optimal block size in polynomial time. Since channel erasure probabilities would be time-varying in a mobile network, we further develop a joint real-time scheduling and channel learning scheme with adaptive NC that can adapt to channel dynamics. We also generalize the analysis to multiple flows with hard deadlines and long-term delivery ratio constraints, devise a low-complexity online scheduling algorithm integrated with the MBIA, and then establish its asymptotical throughput-optimality. In addition to analysis and simulation results, we perform high fidelity wireless emulation tests with real radio transmissions to demonstrate the feasibility of the MBIA in finding the optimal block size in real time.
An Open Adaptive Scheduling Algorithm for Open Hybrid Real-Time Systems

HUAI Xiao-Yong,ZOU Yong,LI Ming-Shu,

软件学报 , 2004,
Abstract: To meet the system scheduling requirements of open hybrid real-time systems, an open adaptive real-time scheduling framework, called OARtS (open adaptive real-time scheduling), is presented in this paper, which comprises three key components: accept control, scheduling server and adaptive control. To guarantee the schedulability in the open environment, OARtS only accepts the task whose computing bandwidth requirement is no higher than the system's spare one. To schedule multi-constraint tasks, a two-layer scheduling mechanism is introduced. In the mechanism, the scheduling server components provide concurrent scheduling mechanism for multi-constraint tasks, and each of them is assigned to a bandwidth-independent computing bandwidth and has its specific scheduling policy to schedule its own task queue. To adapt to the change in the open environment, the adaptive control tries to tune the real-time service level so as to make full use of the system computing capability; to adapt to the uncertainty of execution time of the soft real-time task, a fuzzy control engine is used to regulate the task's computing bandwidth according to fuzzy rules of the scheduling error so as to eliminate the scheduling error and to get a satisfactory soft real-time performance.
Power-Aware Real-Time Scheduling upon Identical Multiprocessor Platforms  [PDF]
Vincent Nélis,Jo?l Goossens,Nicolas Navet,Raymond Devillers,Dragomir Milojevic
Computer Science , 2007,
Abstract: In this paper, we address the power-aware scheduling of sporadic constrained-deadline hard real-time tasks using dynamic voltage scaling upon multiprocessor platforms. We propose two distinct algorithms. Our first algorithm is an off-line speed determination mechanism which provides an identical speed for each processor. That speed guarantees that all deadlines are met if the jobs are scheduled using EDF. The second algorithm is an on-line and adaptive speed adjustment mechanism which reduces the energy consumption while the system is running.
Feedback Scheduling of Priority-Driven Control Networks  [PDF]
Feng Xia,Youxian Sun,Yu-Chu Tian
Computer Science , 2008,
Abstract: With traditional open-loop scheduling of network resources, the quality-of-control (QoC) of networked control systems (NCSs) may degrade significantly in the presence of limited bandwidth and variable workload. The goal of this work is to maximize the overall QoC of NCSs through dynamically allocating available network bandwidth. Based on codesign of control and scheduling, an integrated feedback scheduler is developed to enable flexible QoC management in dynamic environments. It encompasses a cascaded feedback scheduling module for sampling period adjustment and a direct feedback scheduling module for priority modification. The inherent characteristics of priority-driven control networks make it feasible to implement the proposed feedback scheduler in real-world systems. Extensive simulations show that the proposed approach leads to significant QoC improvement over the traditional open-loop scheduling scheme under both underloaded and overloaded network conditions.
Adaptive scheduling scheme to support real-time traffic in wireless local area networks

HUANG Jing-lian,

计算机应用 , 2008,
Abstract: To overcome the defect of IEEE 802.11e reference scheduler allocating fixed Transmission Opportunity (TXOP) duration, an adaptive scheduling scheme was proposed to support real-time traffic. The proposed scheduler dynamically allocated variable TXOP duration based on the traffic load information of the amount of buffered frames in each traffic stream queue sent by stations, to satisfy the requirements of different traffic under different load. By guaranteeing minimum delay of traffic, the scheduler tried to allocate TXOP for the new arrival traffic with proportional request reduction and linear programming. Detailed simulation results and comparison with IEEE 802.11e reference scheduler prove that the proposed scheduling scheme not only improves system throughput, but also decreases delay of real-time traffic.
Analysis of Real World Personnel Scheduling Problem: An Experimental Study of Lp-Based Algorithm for Multi-Time Multi-period Scheduling Problem for Hourly Employees
Sang Hyun Kim
International Journal of Soft Computing , 2012,
Abstract: Scheduling service employees at any campus dining center is not an easy task for a manager because most positions at a campus dining center are hourly-paid positions, leading to a high employee turnover and many uncertainties. In such a circumstance, a manager has a hard time to organize and project employees work schedules. The Johnson Commons (JC) dinning center at the University of Mississippi operated by Aramark also has similar difficulties in scheduling its hourly employees. After discussing with a manager and investigating the current scheduling system at the JC, it is found that the JC has one type of scheduling problem called the Multi-time Multi-Period Scheduling Problem. Therefore, the main purpose of this study is to find the optimal solution for the scheduling problem at the JC dining center. The result shows that with the optimal solution, the JC can save a total of $50,648.00 hourly employee labor expenses per year.
Theory of adaptive adjustment  [PDF]
Weihong Huang
Discrete Dynamics in Nature and Society , 2000, DOI: 10.1155/s102602260000056x
Abstract: Conventional adaptive expectation as a mechanism of stabilizing an unstable economic process is reexamined through a generalization to an adaptive adjustment framework. The generic structures of equilibria that can be stabilized through an adaptive adjustment mechanism are identified. The generalization can be applied to a broad class of discrete economic processes where the variables interested can be adjusted or controlled directly by economic agents such as in cobweb dynamics, Cournot games, Oligopoly markets, tatonnement price adjustment, tariff games, population control through immigration etc.
FEL-H Robust Control Real-Time Scheduling  [PDF]
Bing Du, Chun Ruan
Journal of Software Engineering and Applications (JSEA) , 2009, DOI: 10.4236/jsea.2009.21010
Abstract: The existing scheduling algorithms cannot adequately support modern embedded real-time applications. An important challenge for future research is how to model and introduce control mechanisms to real-time systems to improve real-time performance, and to allow the system to adapt to changes in the environment, the workload, or to changes in the system architecture due to failures. In this paper, we pursue this goal by formulating and simulating new real-time scheduling models that enable us to easily analyse feedback scheduling with various constraints, overload and disturbance, and by designing a robust, adaptive scheduler that responds gracefully to overload with robust H∞ and feedback error learning control.
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