• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5694-5711
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• 2017

The technology of cloud computing is growing very quickly, thus it is required to manage the process of resource allocation. In this paper, load balancing algorithm based on honey bee behavior (LBA_HB) is proposed. Its main goal is distribute workload of multiple network links in the way that avoid underutilization and over utilization of the resources. This can be achieved by allocating the incoming task to a virtual machine (VM) which meets two conditions; number of tasks currently processing by this VM is less than number of tasks currently processing by other VMs and the deviation of this VM processing time from average processing time of all VMs is less than a threshold value. The proposed algorithm is compared with different scheduling algorithms; honey bee, ant colony, modified throttled and round robin algorithms. The results of experiments show the efficiency of the proposed algorithm in terms of execution time, response time, makespan, standard deviation of load, and degree of imbalance.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.167-174
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• 2014

In this paper, we address a task allocation problem for a robot team that performs a search and attack mission. The robots are limited in sensing and communication capabilities, and carry different types of resources that are used to attack a target. The environment is uncertain and dynamic where no prior information about targets is given and dynamic events unpredictably happen. The goal of robot team is to collect total utilities as much as possible by destroying targets in a mission horizon. To solve the problem, we propose a distributed task allocation framework incorporated with effective resource management based on resource welfare. The framework we propose enables the robot team to retain more robots available by balancing resources among robots, and respond smoothly to dynamic events, which results in system performance improvement.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.36-46
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• 2005

In traditional production lines, such as assembly lines, each worker is usually assigned to a fixed task, which is beneficial since it reduces the amount of training needed for workers to master their assigned tasks. However, when workers complete their tasks at different speeds, the slowest worker will determine the overall pace of the production line and limit production. To avoid this problem, the self-balancing production line was introduced. In this type of production line, each worker works dynamically, thus they can maintain balanced production. Previous research analyzing the performance of these lines has ignored the walk-back time associated with dynamic workers. U-shaped production lines have also been analyzed and policies for such lines have been proposed. However, the walk-back time cannot be ignored in practice, and research taking this factor into account is needed to enable balanced production and thus the maximum production rate. In this paper, we propose production policies for a production line with the walk-back time taken into account, and define and analyze the conditions for self-balancing. Furthermore, we have compared the performance of such a line with that of other production lines under the same conditions, and the results show the superiority of this line in certain cases.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.158-170
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• 2021

Virtualization technologies are being adopted and broadly utilized in many fields and at different levels. In cloud computing, achieving load balancing across large distributed virtual machines is considered a complex optimization problem with an essential importance in cloud computing systems and data centers as the overloading or underloading of tasks on VMs may cause multiple issues in the cloud system like longer execution time, machine failure, high power consumption, etc. Therefore, load balancing mechanism is an important aspect in cloud computing that assist in overcoming different performance issues. In this research, we propose a new approach that combines the advantages of different task allocation algorithms like Round robin algorithm, and Random allocation with different threshold techniques like the VM utilization and the number of allocation counts using least connection mechanism. We performed extensive simulations and experiments that augment different scheduling policies to overcome the resource utilization problem without compromising other performance measures like makespan and execution time of the tasks. The proposed system provided better results compared to the original round robin as it takes into consideration the dynamic state of the system.

• IE interfaces
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• v.16 no.spc
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• pp.76-81
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• 2003

BPMS (Business Process Management Systems) is aninformation system that systematically supports designing, administrating, and improving the business processes. It can execute the business processes by assigning tasks to human or computer agents according to the predefined definitions of the processes. In this research we developed a task assignment algorithm that can maximize overall process efficiency under the limitation of agents' capacity. Since BPMS manipulates the formal and predictable business processes, we can analyze the processes using queuing theory to achieve overall process efficiency. We first transform the business processes into queuing network model in which the agents are considered as servers. After that, workloads of agents are calculated as server utilization and we can determine the task assignment policy by balancing the workloads. This will make the workloads of all agents be minimized, and the overall process efficiency is achieved in this way. Another application of the results can be capacity planning of agents in advance and business process optimization in reengineering context. We performed the simulation analysis to validate the results and also show the effectiveness of the algorithm by comparing with well known dispatching policies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.123-128
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• 2019

The Internet Engineering Task Force (IETF) proposed IPv6 Routing Protocol for Low-power Lossy Network (RPL) as a routing protocol for Low Power and Lossy Networks (LLN). In RPL networks, only a few parent nodes are connected to many child nodes, which is called Thundering Herd Phenomenon. To solve this problem, it has been considered to limit the maximum number of child nodes connected per node using the CNC (Child Number Count) parameter. However, the problem remains that some parent nodes can be attached with as many as the maximum number of child nodes. How to determine the maximum CNC value is yet another problem. Therefore, in this paper, we propose an algorithm that evenly distributes the number of child nodes connected per node, to solve the Thundering Herd Phenomenon problem. The performance of the proposed algorithm is compared with that of the conventional RPL using CNC. As a result, we showed that the proposed algorithm performs better in terms of load balancing.

• IE interfaces
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• v.22 no.3
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• pp.263-277
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• 2009

This research deals with a task assignment problem to worker group which consists of one master and one assistant. Each task must be assigned to only one worker group and it is possible to make a pair of each master and each assistant to organize a worker group. A worker group may have more than one task assigned to it, but the workloads of each worker group must be balanced within the allowable range. This problem can be formulated mathematically using the Mixed Integer Programming(MIP), where the objective function is to minimize the total assignment cost. A two phase heuristic algorithm is suggested in order to find approximate solutions. The first phase is to obtain an initial solution, where the initial assignment is performed to follow the workload adjustment. In the second phase, the solution is improved through the repeated process of the exchange and the assignment adjustment. Numerical experiments have been performed to evaluate the performance of the heuristic algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.8
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• pp.445-455
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• 2002

In this paper, we present a new task scheduling scheme ior the efficient execution of the tasks of compound nodes of hierarchical task graph(HTG) on shared memory system. The proposed scheme for exploitation functional parallelism is autoscheduling that performs the role of scheduling by processor itself without any dedicated global scheduler. To adapt the proposed scheduling scheme for various platforms, Including a uni-processor systems, Java threads were used for implementation, and the performance is analyzed in comparison with a conventional bit vector method. The experimental results showed that the proposed method was found to be more efficient in its execution time and exhibited good load-balancing when using the experimental parameter values. Furthermore, the memory size could be reduced when using the proposed algorithm compared with a conventional scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.165-171
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• 2005

In this paper, the centralized dynamic load-balancing was processed effectively by using the network based parallel genetic algorithm. Unlike the existing method using genetic algorithm, the performance of central scheduler was improved by distributing the process for the searching of the optimal task assignment to clients. A roulette wheel selection and an elite preservation strategy were used as selection operation to improve the convergence speed of optimal solution. A chromosome was encoded by using sliding window method. And a cyclic crossover was used as crossover operation. By the result of simulation for the performance estimation of central scheduler according to the change of flexibility of load-balancing method, it was verified that the performance is improved in the proposed method.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.53-61
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• 2002

This paper propose an dynamic load balancing algorithm for heterogeneous distributed systems. The algorithm allows this tasks to be relocated. The key of the algorithm is to transfer a suitable amount of processing demand from senders to receivers. This amount is determined dynamically during sender-receiver negotiations. Factors considered when this amount is determined include processing speeds of different nodes, the current load state of both sender and receiver, and the processing demands of tasks eligible for relocation. This paper also propose a load state measurement scheme which is designed particularly for heterogeneous systems. This results of the study show that the proposed algorithm outperforms the existing algorithms and is stable over a range of system attributes.