• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1849-1876
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• 2022

Wireless Sensor Network (WSN) is considered as an integral part of the Internet of Things (IoT) for collecting real-time data from the site having many applications in industry 4.0 and smart cities. The task of nodes is to sense the environment and send the relevant information over the internet. Though this task seems very straightforward but it is vulnerable to certain issues like energy consumption, delay, throughput, etc. To efficiently address these issues, this work develops a cross-layer model for the optimization between MAC and the Network layer of the OSI model for WSN. A high value of duty cycle for nodes is selected to control the delay and further enhances data transmission reliability. A node measurement prediction system based on the Kalman filter has been introduced, which uses the constraint based on covariance value to decide the scheduling scheme of the nodes. The concept of duty cycle for node scheduling is employed with a greedy data forwarding scheme. The proposed Duty Cycle-based Greedy Routing (DCGR) scheme aims to minimize the hop count, thereby mitigating the energy consumption rate. The proposed algorithm is tested using a real-world wastewater treatment dataset. The proposed method marks an 87.5% increase in the energy efficiency and reduction in the network latency by 61% when validated with other similar pre-existing schemes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.885-888
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• 1995

Virtual Manufacturing System(VMS) is a computer model that represents the precise and whole structure of manufacturing system and simulates their physical and logical behavior in operation. In this paper, a real time simulation for the virtual factory is proposed to integrate a process planning with scheduling under distributed environments. In order to communicate the information under distributed environment, weuse a sever/client concept and socket program. the VMS is implemented on the internet environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2509-2528
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• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1074-1086
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• 2015

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4311-4330
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• 2015

Cloud computing has become a new paradigm by enabling on-demand provisioning of applications, platforms or computing resources for clients. Workflow scheduling has always been treated as one of the most challenging problems in clouds. Commercial clouds have been widely used in scientific research, such as biology, astronomy and weather forecasting. Certainly, it is very important for a cloud service provider to pursue the profits for the commercial essence of clouds. This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds. This work takes the communication into account, which has always been ignored. And then, a topology-based workflow-scheduling algorithm named Resource Auction Algorithm (REAL) is proposed in the objective of getting more profits. The algorithm gives a good performance on searching for the optimum schedule for a sample workflow. Also, we find that there exists a certain resource amount, which gets the most profits to help us get more enthusiasm for further developing the research. Experimental results demonstrate that the analysis of the strategies for most profits is reasonable, and REAL gives a good performance on efficiently getting an optimized scheme with low computing complexity.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.1-10
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• 2008

In this paper, a packet scheduling algorithm, called the modified PLFS, is proposed for real-time traffic in IEEE 802.22 WRAN systems. The modified PLFS(Packet Loss Fair Scheduling) algorithm utilizes not only the delay of the Head of Line(HOL) packets in buffer of each user but also the amount of expected loss packets in the next-next frame when a service will not be given in the next frame. The performances of the modified PLFS are compared with those of PLFS and M-LWDF in terms of the average packet loss rate and throughput. The simulation results show that the proposed scheduling algorithm performs much better than the PLFS and M-LWDF algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4050-4067
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• 2014

In wireless sensor networks, link scheduling is a fundamental problem related to throughput capacity and delay. For a given set of communication requests $L=\{l_1,l_2,{\cdots},l_n\}$, the MLS (maximum link scheduling) problem aims to find the largest possible subset S of Lsuch that the links in S can be scheduled simultaneously. Most of the existing results did not consider bidirectional transmission setting, which is more realistic in wireless sensor networks. In this paper, under physical interference model SINR (signal-to-noise-plus-interference-ratio) and bidirectional transmission model, we propose a constant factor approximation algorithm MLSA (Maximum Link Scheduling Algorithm) for MLS. It is proved that in the same topology setting the capacity under unidirectional transmission model is lager than that under bidirectional transmission model. However, compared with some work under unidirectional transmission model, the capacity of MLSA is improved about 28% to 45%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.11-20
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• 2004

Proportional Fair (PF) share policy has been adopted as a downlink scheduling scheme in CDMA2000 l×EV-DO standard. Although It offers optimal performance in aggregate throughput conditioned on equal time share among users, it cannot provide a bandwidth guarantee and a strict delay bound. which is essential requirements of real-time (RT) applications. In this study, we propose a new scheduling policy that provides quality-of-service (QoS) guarantees to a variety of traffic types demanding diverse service requirements. In our policy data traffic is categorized Into three classes, depending on sensitivity of Its performance to delay or throughput. And the primary components of our policy, namely, Proportional Fair (PF), Weighted Fair Queuing (WFQ), and delay-based prioritized scheme are intelligently combined to satisfy QoS requirements of each traffic type. In our policy all the traffic categories run on the PF policy as a basis. However the level of emphasis on each of those ingredient policies is changed in an adaptive manner by taking into account the channel conditions and QoS requirements. Such flexibility of our proposed policy leads to offering QoS guarantees effectively and. at the same time, maximizing the throughput. Simulations are used to verify the performance of the proposed scheduling policy. Experimental results show that our proposal can provide guaranteed throughput and maximum delay bound more efficiently compared to other policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5465-5480
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• 2018

Energy-efficient task scheduling on multi-core server is a fundamental issue in green cloud computing. Multi-core processors are widely used in mobile devices, personal computers, and servers. Existing energy efficient task scheduling methods chiefly focus on reducing the energy consumption of the processor itself, and assume that the cores of the processor are controlled independently. However, the cores of some processors in the market are divided into several voltage islands, in each of which the cores must operate on the same status, and the cost of the server includes not only energy cost of the processor but also the energy of other components of the server and the cost of user waiting time. In this paper, we propose a cost-aware scheduling algorithm ICAS for computation intensive tasks on multi-core server. Tasks are first allocated to cores, and optimal frequency of each core is computed, and the frequency of each voltage island is finally determined. The experiments' results show the cost of ICAS is much lower than the existing method.