This paper considers efficient and low complexity multiuser scheduling algorithms for the uplink multiple-input multiple-output systems. The exhaustive search algorithm (ESA) that gives the optimal performance, howeve...
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ISBN:
(纸本)9781457701009
This paper considers efficient and low complexity multiuser scheduling algorithms for the uplink multiple-input multiple-output systems. The exhaustive search algorithm (ESA) that gives the optimal performance, however, is complexity prohibitive for practical implementation. Aiming at reducing the complexity while keeping the achievable sum rate performance, two heuristic algorithms are proposed for the multiuser scheduling problem: the improved genetic algorithm and simplified norm-based greedy algorithm. Numerical examples demonstrate that our proposed scheduling algorithms perform close to the optimal ESA, while with much lower complexity.
Task scheduling and resource scheduling are the core issue in cloud computing. Pointing at the premature problem in the scheduling algorithm of particle swarm, we propose a scheduling algorithm of cloud task particle ...
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For great change of service time for request,big difference of hardware and software server and different network performance,this paper proposes a dynamic-feedback algorithm based on AHP in the course of studying the...
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For great change of service time for request,big difference of hardware and software server and different network performance,this paper proposes a dynamic-feedback algorithm based on AHP in the course of studying the algorithm of load balancing in the cluster-based system. Combined with Weighted scheduling algorithm of the kernel, based on the parameters influencing the performance of cluster system from dynamic feedback,we can adjust the servers'weight,solve the load imbalance problem among the servers effectively and certainly improve the throughput of the whole system.
Many multiprocessor real-time operating systems offer the possibility to restrict the migrations of any task to a specified subset of processors by setting affinity masks. A notion of “strong arbitrary processor affi...
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ISBN:
(纸本)9781509028122
Many multiprocessor real-time operating systems offer the possibility to restrict the migrations of any task to a specified subset of processors by setting affinity masks. A notion of “strong arbitrary processor affinity scheduling” (strong APA scheduling) has been proposed; this notion avoids schedulability losses due to overly simple implementations of processor affinities. Due to potential overheads, strong APA has not been implemented so far in a real-time operating system. We show that, in the special but highly relevant case of hierarchical processor affinities (HPA), strong APA scheduling can be implemented with a vastly improved runtime complexity. In particular, we present a strong HPA scheduler with a runtime complexity of O(m) per task arrival and O(log n+m 2 ) per task departure, where mis the number of processors and n is the number of tasks, thus improving on the previous bounds of O(m 2 ) and O(mn). The improved runtime algorithms allowed us to implement support for strong hierarchical processor affinities in LITMUSRT. We benchmarked this implementation on a 24-core platform and observed nonnegligible, but still viable runtime overheads. Additionally, in the case of a bilevel affinity hierarchy and when job priorities are based on deadlines, we argue that the performance of our strong HPA scheduler, HPA-EDF, can be related to system optimality in the following way: any collection of jobs that is schedulable (under any policy) on m unit-speed processors subject to hierarchical affinity constraints is correctly scheduled by HPA-EDF on m processors of speed 2.415.
Wireless communication systems are predicted to appear massively in the future human life. In case of 5G communications, high expectations in terms of Quality of Service and reliability are foreseen. However, the deve...
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ISBN:
(纸本)9781479966653
Wireless communication systems are predicted to appear massively in the future human life. In case of 5G communications, high expectations in terms of Quality of Service and reliability are foreseen. However, the development of future systems has to cope with a better exploitation of the available resources. As a matter of fact, system coexistence and frequency sharing are two of the most promising approaches to achieve spectrum efficiency. Cognitive Radio (CR) is a key enabler of these approaches, which are also arising in Satellite Communications (SatComs). In this paper, a carrier allocation based scheduling algorithm inspired by genetic algorithms (GA) is proposed by taking into account different environment conditions and service requirements of the users of the cognitive satellite system.
MapReduce includes three phases of map, shuffle, and reduce. Since the map phase is CPU-intensive and the shuffle phase is I/O-intensive, these phases can be conducted in parallel. This paper studies a joint schedulin...
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ISBN:
(纸本)9781509022809
MapReduce includes three phases of map, shuffle, and reduce. Since the map phase is CPU-intensive and the shuffle phase is I/O-intensive, these phases can be conducted in parallel. This paper studies a joint scheduling optimization of overlapping map and shuffle phases to minimize the average job makespan. Challenges come from the dependency relationship between map and shuffle phases, since the shuffle phase may wait to transfer the data emitted by the map phase. A new concept of the strong pair is introduced. Two jobs are defined as a strong pair, if the shuffle and map workloads of one job equal the map and shuffle workloads of the other job, respectively. We prove that, if the entire set of jobs can be decomposed to strong pairs of jobs, then the optimal schedule is to pairwisely execute jobs that can form a strong pair. Following the above intuition, several offline and online scheduling policies are proposed. They first group jobs according to job workloads, and then, execute jobs within each group through a pairwise manner. Real data-driven experiments validate the efficiency and effectiveness of the proposed policies.
作者：
Coviello, N.DIATI
Politecnico di Torino Italy DICEA
Università la Sapienza Rome Italy
The paper describes a timetable-dependent method for assessing railway capacity, based on the generation and the analysis of sets of feasible timetables. This approach permits the consideration of all the major variab...
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Real-time embedded systems have become widely used in many fields such as control, monitoring and aviation. They perform several tasks under strict time constraints. In such systems, deadline miss may lead to catastro...
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ISBN:
(纸本)9781509006809
Real-time embedded systems have become widely used in many fields such as control, monitoring and aviation. They perform several tasks under strict time constraints. In such systems, deadline miss may lead to catastrophic results so that all jobs need to be scheduled appropriately to ensure that they meet their deadline times. This paper presents an efficient dynamic scheduling algorithm during run-time to schedule periodic tasks in multiprocessor environments and uniprocessor as well using a dynamic average estimation. Dynamic average estimation refers to changing in different probability distributions when a task is added or removed from them. It is not always available a value of Worst-Case Execution Time (WCET) in many real-time applications such as multimedia where data has a great variation. The proposed approach selects which task or a set of tasks must be picked up for execution. A simulation system was developed to show validation of the proposed approach.
In Grid computing environment application scheduling is very crucial because the resources are more heterogeneous, geographically distributed, complex and owned by different organizations, they are more prone to failu...
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ISBN:
(纸本)9781509016679
In Grid computing environment application scheduling is very crucial because the resources are more heterogeneous, geographically distributed, complex and owned by different organizations, they are more prone to failures. Generally, during application/job scheduling only performance factor of resources are considered. But if a node with high computational power also have high failure rate, then there is no such benefit of allocating task to that node because every time a failure occurs it needs recovery and in turn costs in term of time. Thus, failure increases make-span for the job and decreases system/node performance. So, it would be a great idea if we take into consideration failure rate and computational capacity of resources during scheduling. In this paper, to improve the system performance we have proposed a failure-aware scheduling algorithm by taking into consideration both performance and failure factors.
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