• Journal of the Korean Operations Research and Management Science Society
• /
• v.18 no.2
• /
• pp.1-22
• /
• 1993

This paper deals with the problem of mixed model assembly line balancing. In mixed model assembly lines, tsks should be assigned to stations in such a manner that all stations have approximately the same amount of work on a production cycle basis. Further in balancing assembly lines, the related tasks, the performing task side and the team tasks should be considered to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines. In this paper, the heuristic dispatch assignment rule is developed to assign evenly tasks of each model to all stations. The heuristic method based on the assignment rule developed is presented for mixed model assembly line balancing with the considerations of the related tasks, the performing task side, and the team tasks. The proposed method is analyzed, and compared with other methods for line balancing.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.5
• /
• pp.361-367
• /
• 2014

In this paper, task scheduling and load balancing methods of multifrontal solution methods of finite element structural analysis in a modern multicore machine are introduced. Many structural analysis problems have generally irregular grid and many kinds of properties and materials. These irregularities and heterogeneities lead to bottleneck of parallelization and cause idle time to analysis. Therefore, task scheduling and load balancing are desired to reduce inefficiency. Several kinds of multithreaded parallelization methods are presented and comparison between static and dynamic task scheduling are shown. To reduce the idle time caused by irregular partitioned subdomains, computational load balancing methods, Balancing all tasks and minmax task pairing balancing, are invented. Theoretical and actual elapsed time are shown and the reason of their performance gap are discussed.

• Physical Therapy Korea
• /
• v.23 no.4
• /
• pp.16-26
• /
• 2016

Background: Deficiencies in the ability to maintain balance are common in elderly. Augmented feedback such as knowledge of results (KR) can accelerate learning and mastering a motor skill in older people. Objects: We designed this study to examine whether one session of Wii-Fit game with self-regulated KR is effective for elderly people, and to compare the effect of two different timings of self-regulated KR conditions. Methods: Thirty-nine community-dwelling elders, not living in hospice care or a nursing home, participated in this study. During acquisition, two groups of volunteers were trained in 10 blocks of a dynamic balancing task under the following 2 conditions, respectively: (a) a pre-trial self-regulated KR ($n_1=18$), or (b) a post-trial self-regulated KR ($n_2=21$). Immediate retention tests and delayed retention tests of balancing performance were administered in 15 minutes and 24 hours following acquisition period, respectively. Results: In both groups, significant improvements of balancing performances scores were observed during the acquisition period. Regardless of the group, mean of balancing performance scores on retention tests were well-maintained from the final session. There were no significant differences between groups in balancing performance scores during the acquisition period (p>.05); however, the post-trial self-regulated KR group exhibited significantly higher balancing performance scores in both the immediate retention test and delayed retention test than that of the pre-trial self-regulated KR group (p<.05). Conclusion: Therefore, subjects who regulated their feedback after a dynamic balancing task, during the acquisition period, experienced more efficient motor learning during the retention period than did subjects who regulated their feedback before a dynamic balancing task. Accordingly, in case of presenting the KR of motor learning in clinical settings to elders who reduced dynamic balance abilities, the requesting time of KR is imperative according to self-estimation processes as well as types of KR and practice.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.1
• /
• pp.117-135
• /
• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.314-317
• /
• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.

• Journal of Information Processing Systems
• /
• v.10 no.2
• /
• pp.193-214
• /
• 2014

Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.176-179
• /
• 2002

In recent years, an increasing amount of computer network research has focused on the problem of cluster system in order to achieve higher performance and lower cost. The load unbalance is the major defect that reduces performance of a cluster system that uses parallel program in a form of SPMD (Single Program Multiple Data). Also, the load unbalance is a problem of MPP (Massive Parallel Processors), and distributed system. The cluster system is a loosely-coupled distributed system, therefore, it has higher communication overhead than MPP. Dynamic load balancing can solve the load unbalance problem of cluster system and reduce its communication cost. The cluster systems considered in this paper consist of P heterogeneous nodes connected by a switch-based network. The master node can predict the average execution time of tasks for each slave node based on the information from the corresponding slave node. Then, the master node redistributes remaining tasks to each node considering the predicted execution time and the communication overhead for task migration. The proposed dynamic load balancing uses execution time prediction to optimize the task redistribution. The various performance factors such as node number, task number, and communication cost are considered to improve the performance of cluster system. From the simulation results, we verified the effectiveness of the proposed dynamic load balancing algorithm.

• Journal of information and communication convergence engineering
• /
• v.9 no.2
• /
• pp.141-149
• /
• 2011

We consider the problem of assigning tasks to homogeneous nodes in the distributed system, so as to minimize the amount of communication, while balancing the processors' loads. This issue can be posed as the graph partitioning problem. Given an undirected graph G=(nodes, edges), where nodes represent task modules and edges represent communication, the goal is to divide n, the number of processors, as to balance the processors' loads, while minimizing the capacity of edges cut. Since these two optimization criteria conflict each other, one has to make a compromise between them according to the given task type. We propose a new cost function to evaluate static task assignments and a heuristic algorithm to solve the transformed problem, explicitly describing the tradeoff between the two goals. Simulation results show that our approach outperforms an existing representative approach for a variety of task and processing systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.9
• /
• pp.4103-4121
• /
• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• Proceedings of the IEEK Conference
• /
• 2000.06c
• /
• pp.105-108
• /
• 2000

As Internet and WWW grow rapidly, the role of web servers is getting more important, and the number of users in a few popular site is also explosively increasing. Load balancing in clustered web server systems is important task to utilize whole system effectively, so dynamic load balancing is required to overcome the limit of static load balancing. In this paper, we propose two dynamic load balancing schemes, and analyzed load model and Performance improvement and also compare existing load balancing methods and IP filtering method. In case of load balancing with threshold, little extra traffic was required for better performance, but in case of load balancing with load weight, we found that the performance mainly depends on information exchange rate.