• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2003-2021
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• 2020

Today's computer systems are widely integrated with CPU and GPU to achieve considerable performance, but energy consumption of such system directly affects operational cost, maintainability and environmental problem, which has been aroused wide concern by researchers, computer architects, and developers. To cope with energy problem, we propose a task-scheduling framework to reduce energy under performance constraint by rationally allocating the tasks across the CPU and GPU. The framework first collects the estimated energy consumption of programs and performance information. Next, we use above information to formalize the scheduling problem as the 0-1 knapsack problem. Then, we elaborate our experiment on typical platform to verify proposed scheduling framework. The experimental results show that our proposed algorithm saves 14.97% energy compared with that of the time-oriented policy and yields 37.23% performance improvement than that of energy-oriented scheme on average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.165-170
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• 2011

The Pfair scheduling algorithm, which is an optimal algorithm in the hard real-time multiprocessor environments, is based on the fixed quantum size. Recently, several methods that can determine the optimal quantum dynamically are developed in the mode change environments. These methods are based on the reach function and in many cases, we have to do the sequential search to find the optimal quantum. In this paper, we propose a new scheduling method, based on the improved reach function, that can determine the optimal quantum more quickly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4429-4445
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• 2019

As low-power and low-rate WSNs are being widely used for industrial applications, the scheduling of such applications becomes a critical issue to guarantee meeting the stringent requirements of determinism and tight latencies. This paper studies the link scheduling problem for real-time industrial applications in time-slotted channel hopping (TSCH) networks. We propose a heuristic algorithm for centralized link scheduling referred to as path-collision aware least laxity first (PC-LLF) algorithm, which dynamically prioritizes the packets based on the laxity time to the end-to-end deadlines and the amount of collisions that messages might deal with along their designated paths to the destination device. We propose schedulability analysis of real-time applications scheduled under our prioritization approach over TSCH networks, based on the literature on real-time schedulability analysis of multiprocessors and distributed systems. We show that our methodology provides an improved schedulability condition with respect to the existing approaches. Performance evaluation studies quantify to quantify the performance of our proposed approach under a variety of scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5013-5034
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• 2019

In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.83-104
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• 2011

Mobile grid is a combination of grid computing and mobile computing to build grid systems in a wireless mobile environment. The development of network technology is assisting in realizing mobile grid. Mobile grid based on established grid infrastructures needs effective resource management and reliable job scheduling because mobile grid utilizes not only static grid resources but also dynamic grid resources with mobility. However, mobile devices are considered as unavailable resources in traditional grids. Mobile resources should be integrated into existing grid sites. Therefore, this paper presents a mobile grid middleware interconnecting existing grid infrastructures with mobile resources and a mobile service agent installed on the mobile resources. This paper also proposes a mobile resource reliability-based job scheduling model in order to overcome the unreliability of wireless mobile devices and guarantee stable and reliable job processing. In the proposed job scheduling model, the mobile service agent calculates the mobile resource reliability of each resource by using diverse reliability metrics and predicts it. The mobile grid middleware allocated jobs to mobile resources by predicted mobile resource reliability. We implemented a simulation model that simplifies various functions of the proposed job scheduling model by using the DEVS (Discrete Event System Specification) which is the formalism for modeling and analyzing a general system. We also conducted diverse experiments for performance evaluation. Experimental results demonstrate that the proposed model can assist in improving the performance of mobile grid in comparison with existing job scheduling models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.63-67
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• 2024

Recently, artificial intelligence (AI) workloads encompassing various industries such as smart logistics, FinTech, and entertainment are being executed on the cloud. In this paper, we address the scheduling issues of various AI workloads on a multi-tenant cloud system composed of heterogeneous GPU clusters. Traditional scheduling decreases GPU utilization in such environments, degrading system performance significantly. To resolve these issues, we present a new scheduling approach utilizing genetic algorithm-based optimization techniques, implemented within a process-based event simulation framework. Trace driven simulations with diverse AI workload traces collected from Alibaba's MLaaS cluster demonstrate that the proposed scheduling improves GPU utilization compared to conventional scheduling significantly.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.61-67
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• 2000

In case of the remote controllable web-camera that was took notice especially in internet real-time broadcasting systems, a great many clients connect the server of web-camera to request the service. So, the scheduling methods are important. Web-camera systems have used to the traditional FIFO(First In First Out) or SDF(Shortest Distance First) scheduling method. But they does not satisfy both the minimization of moving distance on the web-camera and the fairness on the users. In this paper, We propose the 2D scheduling method, As a result, the moving distance of the web-camera decreases compared with FIFO scheduling method. And the starvation state on the user's request does not happen compared with SDF scheduling method. Thus, if the remote controllable web-camera systems use the 2D scheduling method, they are satisfied with the minimization of moving distance on the remote controllable web-camera and the fairness on the users simultaneously. Therefore the user's satisfaction and the performance of the systems are improved.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.127-137
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• 2003

A Web crawler is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance web crawlers are urgently demanded. In this paper, we study how to support dynamic scheduling for a multiprocess-based web crawler. For high performance, web crawlers are usually based on multiprocess in their implementations. In these systems, crawl scheduling which manages the allocation of web pages to each process for loading is one of the important issues. In this paper, we identify issues which are important and challenging in the crawl scheduling. To address the issue, we propose a dynamic crawl scheduling framework and subsequently a system architecture for a web crawler with dynamic crawl scheduling support. This paper presents the design of the Web crawler with dynamic scheduling support.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.64-72
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• 2003

A Web crawler is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance web crawlers are urgently demanded. In this paper, we study how to support dynamic scheduling for a multiprocess-based web crawler. For high peformance, web crawlers are usually based on multiprocess in their implementations. In these systems, crawl scheduling which manages the allocation of web pages to each process for loading is one of the important issues. In this paper, we identify issues which are important and challenging in the crawl scheduling. To address the issue, we propose a dynamic crawl scheduling framework and subsequently a system architecture for a web crawler with dynamic crawl scheduling support. And we analysed the behaviors of Web crawler. Based on the analysis result, we suggest the direction for the design of high performance Web crawler.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.6
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• pp.513-520
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• 2005

High-speed Portable Internet system provides 1-3 Mbps data transmission speed to terminals moving up to 60 km/sec. Since High-speed Portable Internet system supports services requiring different QoS, it needs an efficient scheduling method based on those different QoSs. This paper shows the performance comparisons of several different packet scheduling schemes for minimizing the mean delay over the downlink of High-speed Portable Internet system to support the packet data service. Simulation results show that proposed scheme superior to other schemes at side throughput and data loss rate.