IEEE Organizations related to Scheduling Algorithms

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Conferences related to Scheduling Algorithms

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Periodicals related to Scheduling Algorithms

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Most published Xplore authors for Scheduling Algorithms

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Xplore Articles related to Scheduling Algorithms

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Shortest path set induced vertex ordering and its application to distributed distance optimal formation path planning and control on graphs

52nd IEEE Conference on Decision and Control, 2013

For the task of moving a group of indistinguishable agents on a connected graph with unit edge lengths into an arbitrary goal formation, it was shown that distance optimal paths can be computed to complete with a tight convergence time guarantee [30], using a fully centralized algorithm. In this study, we establish the existence of a more fundamental ordering of ...


Bandwidth Management

Wireless Communications Resource Management, None

This chapter contains sections titled:Differences between Wired and Wireless CommunicationsSchedulers based on Generalized Processor SharingSchedulers for Throughput MaximizationDelay Performance of Wireless SchedulersQoS in Wireless Scheduling and Admission Control]]>


Evaluation and improvement of VoIP capacity for LTE

European Wireless 2012; 18th European Wireless Conference 2012, 2012

LTE-Advanced (LTE-A) proposed by the 3rd Generation Partnership Project (3GPP) has been accepted by the International Telecommunication Union (ITU) in 2010 as an IMT-Advanced (IMT-A) compliant 4G mobile radio system. Besides high spectral efficiency for data services, LTE-A had to prove its capability to support a large number of voice calls through Voice over IP (VoIP).


Hybrid adaptive meta-scheduling system for grid computing

2013 International Conference on Information Communication and Embedded Systems (ICICES), 2013

When the trend in human culture advances, the problems in their science and engineering is increased. To solve those problems, lot of computing power is needed. Grid is a heterogeneous system that allows sharing of resources. Grid computing is a technology that works what super computer does. Efficient utilization of the grid environment requires large amount of computing power. Scheduling ...


An effective Multi-Objective task scheduling algorithm using Min-Max normalization in cloud computing

2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 2016

Cloud computing has gained enormous popularity both in business and academia due its on demand service over Internet to the customers on pay-as-you-go model. Task scheduling in cloud computing is a well known problem that has been paid enormous attention. This is even more challenging, particularly for multi-cloud environment. Due to its NP-Hardness, many heuristics have been developed recently. In ...


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Educational Resources on Scheduling Algorithms

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IEEE.tv Videos

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IEEE-USA E-Books

  • Shortest path set induced vertex ordering and its application to distributed distance optimal formation path planning and control on graphs

    For the task of moving a group of indistinguishable agents on a connected graph with unit edge lengths into an arbitrary goal formation, it was shown that distance optimal paths can be computed to complete with a tight convergence time guarantee [30], using a fully centralized algorithm. In this study, we establish the existence of a more fundamental ordering of the vertices on the underlying graph network, induced by a fixed goal formation. The ordering leads to a simple distributed scheduling algorithm that assures the same convergence time. The vertex ordering also readily extends to more general graphs - those with arbitrary integer capacities and edge lengths - for which we again provide guarantees on the convergence time until the desired formation is achieved. Simulations, accessible via a web browser, confirm our theoretical developments.

  • Bandwidth Management

    This chapter contains sections titled:Differences between Wired and Wireless CommunicationsSchedulers based on Generalized Processor SharingSchedulers for Throughput MaximizationDelay Performance of Wireless SchedulersQoS in Wireless Scheduling and Admission Control]]>

  • Evaluation and improvement of VoIP capacity for LTE

    LTE-Advanced (LTE-A) proposed by the 3rd Generation Partnership Project (3GPP) has been accepted by the International Telecommunication Union (ITU) in 2010 as an IMT-Advanced (IMT-A) compliant 4G mobile radio system. Besides high spectral efficiency for data services, LTE-A had to prove its capability to support a large number of voice calls through Voice over IP (VoIP).

  • Hybrid adaptive meta-scheduling system for grid computing

    When the trend in human culture advances, the problems in their science and engineering is increased. To solve those problems, lot of computing power is needed. Grid is a heterogeneous system that allows sharing of resources. Grid computing is a technology that works what super computer does. Efficient utilization of the grid environment requires large amount of computing power. Scheduling independent jobs to the resources is not an easy task. Meta- scheduling schedules maximum number of jobs to the minimum amount of resources which is a very tedious task. Many scheduling algorithms exist to focus either on the job side or on the resource side. Existing Grid Meta - schedulers either target system-centric metrics, such as utilization and throughput, or prioritize jobs based on utility metrics provided by the users. In the proposed work, to utilize the power of grid completely, both the job and resources are taken into account. Jobs are prioritized based on the common location sum that considers both user and system priority. Resources are prioritized based on the computing power which obtained as the normalized value of the CPU _ available. So the high priority job can be submitted to the corresponding resources based on the computing power and it helps to improve the performance.

  • An effective Multi-Objective task scheduling algorithm using Min-Max normalization in cloud computing

    Cloud computing has gained enormous popularity both in business and academia due its on demand service over Internet to the customers on pay-as-you-go model. Task scheduling in cloud computing is a well known problem that has been paid enormous attention. This is even more challenging, particularly for multi-cloud environment. Due to its NP-Hardness, many heuristics have been developed recently. In this paper, we also present a task scheduling algorithm which is based on the popular Min-Max normalization technique in data mining. We refer our proposed algorithm as Normalized Multi-Objective Min-Min Max-Min Scheduling (NMOMXS). Through simulation, the algorithm is shown to outperform two well known existing algorithms in terms of makespan and resource utilization.

  • Distributed Cooperative Precoding in Cellular Systems

    We consider the problem of cooperative precoder selection for interference management in a broadband cellular wireless system. The problem is posed as a sum-rate maximization problem and a solution employing distributed scheduling and precoder selection is proposed. The solution is then shown to be optimal under certain asymptotic conditions. This is also verified using system simulations.

  • Efficient Algorithm on heterogeneous computing system

    Distributed task scheduling in a heterogeneous computing environment is one of the most challenging problems. The optimally mapping of independent tasks onto heterogeneous distributed computing systems is known to be NP-complete. The most common objective function of a distributed task scheduling problem is to reduce the make span and increase the load balancing across the machines. In this paper, we introduce a new scheduling algorithm called, Efficient Algorithm on Heterogeneous Computing System (EAHCS) which balances the load well across the machines and reduces the make span time. In our evaluation study, a number of experiments with various simulation settings have been conducted. The results obtained using the proposed heuristic improves over the existing approaches.

  • Enhancing Performance of MapReduce Framework in Heterogeneous Environments

    MapReduce framework in no time established as a vital distributed model for the applications which are data-intensive. Hadoop default scheduler is restricted by the idea that cluster nodes are homogeneous. The job execution time is extended by the tasks and TaskTrackers which are running slowly in heterogeneous Hadoop cluster. In this paper, we propose a unique MapReduce scheduler that identifies the straggler tasks and TaskTrackers that are running fast in an exceedingly heterogeneous Hadoop cluster so that the JobTracker can assigns slow tasks to the fast TaskTrackers within the cluster. We observe that the experimental results shows consistent improvement in performance to the LATE scheduler and Hadoop default scheduler for various workloads of Hi-Bench benchmark suite by minimizing the job completion time.

  • A Note on EDF Schedulingfor Real-Time Energy Harvesting Systems

    Energy harvesting is the capture of ambient energy, its conversion into a usable form, and its storage for immediate or future use. Interest in energy harvesting has increased over the last decade because of its environmental friendliness and its ability to power devices without electric wires. This term has been frequently applied in recent years in the context of small autonomous embedded devices such as wireless sensor nodes. In this paper, we address the scheduling problem for a single processor device that executes preemptable time critical tasks. Each one has a certain energy requirement and arrives at an unpredictable time. We ask the question whether the traditional task scheduling algorithm earliest deadline first (EDF) is convenient for energy harvesting environments. The paper shows that EDF has a zero competitive factor but nevertheless is optimal for online non-idling settings.

  • Energy aware real time scheduling algorithm for mixed task set

    Energy consumption is one of the major limiting factors of battery operated real-time systems. Optimizing energy consumption without affecting performance and schedulability is the major topic to be researched. In this paper, an energy aware real time scheduling algorithm is proposed for a system with mixed task set consisting of both periodic and aperiodic tasks. Dynamic energy reduction techniques like Dynamic Voltage and Frequency Scaling (DVFS) is used for energy optimization without affecting the responsiveness of aperiodic tasks. Performance of the proposed algorithm is compared with non-DVS algorithm. Experimental evaluation reveals that the proposed algorithm saves 54.44% of energy in comparison with non-DVS algorithms. It achieves this with no degradation in responsiveness of the aperiodic tasks.



Standards related to Scheduling Algorithms

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