• Journal of Information Processing Systems
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• v.6 no.4
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• pp.553-562
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• 2010

The core services in cloud computing environment are SaaS (Software as a Service), Paas (Platform as a Service) and IaaS (Infrastructure as a Service). Among these three core services server virtualization belongs to IaaS and is a service technology to reduce the server maintenance expenses. Normally, the primary purpose of sever virtualization is building and maintaining a new well functioning server rather than using several existing servers, and in improving the various system performances. Often times this presents an issue in that there might be a need to increase expenses in order to build a new server. This study intends to use grid service architecture for a form of server virtualization which utilizes the existing servers rather than introducing a new server. More specifically, the proposed system is to enhance system performance and to reduce the corresponding expenses, by adopting a scheduling algorithm among the distributed servers and the constituents for grid computing thereby supporting the server virtualization service. Furthermore, the proposed server virtualization system will minimize power management by adopting the sleep severs, the subsidized servers and the grid infrastructure. The power maintenance expenses for the sleep servers will be lowered by utilizing the ACPI (Advanced Configuration & Power Interface) standards with the purpose of overcoming the limits of server performance.

• 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.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.11-18
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• 2000

In this paper we present a new extensible model based upon the concept of subtransactions in real-time transaction systems. The nested transaction model originally proposed by J. Moss is extended for real-time uniprocessor transaction systems by adding explicit timing constraints. Based upon the model, an integrated concurrency control and scheduling algorithm is developed, that not only guarantees timing constraints of a set of real-time transactions but also maintains consistency of the database. The algorithm is based on the priority ceiling protocol of Sha et al. We prove that the Real-Time Nested Priority Ceiling Protocol prevents unbounded blocking and deadlock, and maintains the serializability of a set of real-time transactions. We use the upper bound on the duration that a transaction can be blocked to show that it is possible to analyze the schedulability of a transaction set using rate-monotonic priority assignment. This work is viewed as a step toward multiprocessor and distributed real-time nested transaction systems. Also, it is possible to be extended to include the real-time multimedia transactions in the emerging web-based database application areas.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.22-32
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• 2008

To overcome the weakness of the image retrieval system using the existing Ontology and the distributed image based on the database having a simple structure, HERMES was suggested to ensure the self-control of various image suppliers and support the image retrieval based on semantic, the mentioned framework could not solve the problems which are not considered the deterioration in the capacity and scalability when many users connect to broker server simultaneously. In this paper the tables are written which in the case numerous users connect at the same time to the supply analogous level of services without the deterioration in the capacity installs Broker servers and then measures the performance time of each inner Broker Component through Monitoring System and saved and decides the ranking in saved data. As many Query performances are dispersed into several Servers User inputted from the users Interface with reference to Broker Ranking Table, Load Balancing system improving reliability in capacity is proposed. Through the experiment, the scheduling technique has proved that this schedule is faster than existing techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.116-120
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• 2011

In this paper, we have designed and implemented the integrated protocol gateway for the integration of CAN and Profibus networks. To do that, we used the Switched Ethernet as Backbone network, and each fieldbus network is connected by CAN/Ethernet or Profibus/Ethernet gateway, and each gateway perform the translation between fieldbus and Ethernet frames. Futhermore, we realized the real-time features in the environment of the Switched Ethernet by applying the distributed hard real-time scheduling algorithm among each gateways. To implement tht CAN/Ethernet and Profibus/Ethernet gateways, we used the Linux of kernel 2.6.31.12 real-time patched version(PREEMTED_RT), and we could verify successful message translation and real-time features through real implementation.