The problem of maximizing the throughput of contiguous-media system is addressed. A new stripping model, Paged Segment Striping (PSS), is proposed. This model makes it possible to change the round length dynamically w...
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The problem of maximizing the throughput of contiguous-media system is addressed. A new stripping model, Paged Segment Striping (PSS), is proposed. This model makes it possible to change the round length dynamically without additional search overhead. In the dynamic scheme, even a significant change in the user's trends induces only a small performance degradation. By building on the dynamic scheme's ability to self-adjusting round length, performance is increased up to 46% with the same resources. Since it requires little more calculation overhead than the static scheme, the dynamicscheduling scheme is better than the static scheme in most cases.
It is shown that the problem of maximising the total reward of online tasks can be solved by finding the minimum of the maximum derivatives of the reward functions. Based on the modified approach and a close observati...
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It is shown that the problem of maximising the total reward of online tasks can be solved by finding the minimum of the maximum derivatives of the reward functions. Based on the modified approach and a close observation of task arrival characteristics, a heuristic algorithm with average complexity close to O(N) is presented.
Energy harvesting embedded systems are embedded systems that integrate with energy harvesting modules. In this kind of systems, service tasks and energy harvesting tasks must be scheduled efficiently to keep the whole...
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Energy harvesting embedded systems are embedded systems that integrate with energy harvesting modules. In this kind of systems, service tasks and energy harvesting tasks must be scheduled efficiently to keep the whole system working properly as long as possible. In this paper, we model an energy harvesting embedded system with an energy model, a task model, and a resource model and propose a dynamic task schedulingalgorithm. The proposed algorithm is based on dynamic voltage and frequency scaling technique and dynamically concentrates all disperse free time together to harvest energy. We validate the efficiency and effectiveness of the proposed algorithm under both energy-constraint and non-energy-constraint situations with the Yartiss simulation tool.
Most of the process-schedulingalgorithms, which can be exploited by spacecraft avionics systems, fall into one of the two main categories: static algorithms and dynamicalgorithms. 12 Static algorithms assign priorit...
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ISBN:
(纸本)0780381556
Most of the process-schedulingalgorithms, which can be exploited by spacecraft avionics systems, fall into one of the two main categories: static algorithms and dynamicalgorithms. 12 Static algorithms assign priorities to processes before runtime. These algorithms bound the CPU utilization and require considerable information about the runtime parameters of processes in advance. These disadvantages encourage the spacecraft avionics system designers to exploit dynamicalgorithms instead. But these algorithms have their own disadvantages. For example, these algorithms require so many context switches to schedule the processes. This causes a notable overhead in the runtime. One of the well-known dynamicalgorithms is the MLF (Minimum Laxity First) algorithm. The MLF algorithm suffers from a serious problem (in addition to the need for so many context switches). This paper proposes a novel dynamicalgorithm called Optimized MLF which is an attempt to solve the problems of the MLF algorithm in order to make it more applicable to spacecraft avionics systems. The performance of the proposed schedulingalgorithm is evaluated through the use of mathematical modeling as well as simulation results. Both the mathematical model and simulation results show that the optimized MLF algorithm requires less context switches than the traditional MLF and makes the MLF algorithm more applicable to spacecraft avionics systems.
The Ant Colony Optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. The ACO algorithms provide inherent parallelism, which is very useful in multiprocessor envir...
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The Ant Colony Optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. The ACO algorithms provide inherent parallelism, which is very useful in multiprocessor environments. They provide balance between exploration and exploitation along with robustness and simplicity of individual agent. In this paper, ACO based dynamic scheduling algorithm for homogeneous multiprocessor real-time systems is proposed. The results obtained during simulation are measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU) and compared with the results of Earliest Deadline First (EDF) algorithm in the same environment. It has been observed that the proposed algorithm is very efficient in underloaded conditions and it performs very well during overloaded conditions also. Moreover, the proposed algorithm can schedule some typical instances successfully which are not possible to schedule using EDF algorithm.
This research addresses the timeliness of task execution in real-time systems. Specifically, we investigate the dynamicscheduling of tasks with well-defined timing constraints. We present a dynamic uniprocessor sched...
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This research addresses the timeliness of task execution in real-time systems. Specifically, we investigate the dynamicscheduling of tasks with well-defined timing constraints. We present a dynamic uniprocessor schedulingalgorithm with an O(n log n) worst case complexity. The preemptive scheduling performed by our algorithm is shown to be of higher efficiency than that of other known algorithms. Furthermore, tasks may be related by precedence constraints, and they may have arbitrary deadlines and start times (which need not equal their arrival times). An experimental evaluation or the algorithm compares its average case behavior to the worst case. An analytic model also presented in this paper is used for explanation of the experimental results and is validated with actual system measurements. The dynamic scheduling algorithm is the basis of a real-time multiprocessor operating system kernel developed in conjunction with this research. Specifically, this algorithm is used. at the lowest, threads-based layer of the kernel whenever threads are created.
A hard real-time system is usually subject to stringent reliability and timing constraints due to the fact that failure to produce correct results in a timely manner may lead to a disaster. Almost all fault-tolerant s...
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A hard real-time system is usually subject to stringent reliability and timing constraints due to the fact that failure to produce correct results in a timely manner may lead to a disaster. Almost all fault-tolerant schedulingalgorithms at present are designed to deal with hardware faults, while less of those take possible software faults into account. Presented in this paper is a new software fault-tolerant real-time schedulingalgorithm that is similar to EOF, called EBPA (expectation-based probing algorithm). The important contributions of the algorithm are probing a certain steps during the executions of primaries, which leads to improving the predictive quality of canceling ineffective primaries when heavy workload occurs and preventing early failures in execution from triggering failures in the subsequent primary executions as soon as possible. Therefore, the algorithm increases the successful percentage of tasks' completion, and meanwhile decreases the wasted CPU time slots. The simulation experiments show that the algorithm has a better trade-offs between scheduling costs and scheduling performance than the well-known algorithms so far. Moreover, some experimental parameters, such as the number of probing steps and failure probability, are also taken into account.
With the rapid development of fifth generation (5G) communication technology, Wireless Rechargeable Sensor Networks (WRSNs) have gained attention. Wireless Power Transfer (WPT) enables WRSNs to play important roles in...
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Mobile Resource Management without Cloud Server (MRM) is the computing resource integrated management of mobile devices in order to establish mobile cloud computing infrastructure without a cloud server and to provide...
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Mobile Resource Management without Cloud Server (MRM) is the computing resource integrated management of mobile devices in order to establish mobile cloud computing infrastructure without a cloud server and to provide computing services in this research. The MRM forms a logical resource pool to integrate physical resources from scattered mobile devices and provides computing services. In other words, the MRM offers static and dynamic performance-based computing services, designed to provide computing services that guarantee availability and expandability through a mobile device resource pool without a cloud server. To this end, the MRM defines static and dynamic metadata to manage mobile devices. Detailed schemes consisting of the MRM configuration, the MRM management, and the MRM operation are established to design and implement the MRM. To integrate the MRM resources and validate the effectiveness of the computing services, the configuration time for resource integration, and the task time, in accordance with simultaneous requests for computing services, is measured, and the availability results for the MRM are demonstrated.
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