• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권8호
• /
• pp.1825-1842
• /
• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• ETRI Journal
• /
• 제32권4호
• /
• pp.634-637
• /
• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권12호
• /
• pp.5723-5743
• /
• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• Journal of Korean Institute of Industrial Engineers
• /
• 제21권1호
• /
• pp.85-101
• /
• 1995

Automated Guided Vehicles(AGVs) are widely used in computer integrated manufacturing(CIM) systems for material handling purposes. Although automated guided vehicles provide higher levels of flexibility and computer integrability, the installations are limited in number and one of the critical reasons lies in the complexity involved in the operation. The main objective of this research is to alleviate this problem by proposing efficient integrated operational control methods for AGV-based CIM systems. Particularly, this research is concerned with the mixed problem of dispatching automated guided vehicles and scheduling machines operation. The proposed dynamic heuristic algorithm uses various priority schemes and relevant information concerning the load of the system, the status of queues, and the position of AGVs in the scheduling process. The scheduling decision process is hierarchical in the sense that different decision criteria are applied sequentially to identify the most appropriate part to be served. This algorithm consists of two sections, the section of part selection by AGVs for the next service whenever an AGV completes the current assignment, and the section of part selection by machines for next service whenever a machine completes the current operation. The proposed algorithm has been compared with other scheduling schemes using the performance measure of mean flow-time and mean tardiness. Simulation results indicate that the proposed algorithm can reduce the mean flow-time and mean tardiness significantly.

• Journal of Korea Multimedia Society
• /
• 제20권1호
• /
• pp.1-9
• /
• 2017

Explosive deployment of smart mobile devices such as smart phones, and tablets along with expansion of wireless internet bandwidth have enabled the deployment of mobile video streaming such that video traffic becomes the most important service in wireless networks. Recently, for more efficient video streaming services, the ISO MPEG group standardized a protocol called DASH (Dynamic Adaptive Streaming over HTTP) and the standard has been quickly adopted by many service providers such as YouTube and Netflix. Despite of the convenience of mobile streaming services, users also suffer from low QoE(Quality of Experience) due to dynamic channel fluctuations and unnecessary downloading due to high churning rates. This paper proposes a noble efficient video rate selection algorithm considering user buffer level, channel condition and churning rate. Computer simulation based performance study showed that the proposed algorithm improved the QoE significantly compared to a method that determines the video rate based on current channel conditions. Especially, the proposed method reduced the rebuffering rate, one of the most important performance factors of the QoE, to a nonnegligible level.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 한국산업정보학회 2008년도 추계 공동 국제학술대회
• /
• pp.634-642
• /
• 2008

Radio wave is the valuable resources in $21^{st}$ century. It will be widely used in various applications such as DMB, USN, telematics, and home network as well as mobile and wireless communications. Cognitive Radio technology is devised to maximize the utilization of radio resources by sensing near-by spectrum and dynamic and allocating free resources dynamically and adaptively. Wireless links for the secondary user need to be frequently switched to idle frequencies during the transmission of multimedia data in the cognitive radio based system. This may cause delay and information loss, and QoS degradations occur inevitably. The efficient frequency allocation scheme is necessary to support the seamless multimedia service to the secondary user while maintaining QoS of the primary user. This paper suggests a frequency selection scheme which considers other parameters such as cell load, data rate, and available bandwidth than just received signal strength during the frequency selection process. The performance of our proposed scheme is analyzed by simulation.

• Journal of KIISE:Software and Applications
• /
• 제36권1호
• /
• pp.1-9
• /
• 2009

In heterogeneous and distributed computing environments, with an increasing number of Web services providing similar functionalities, the reliability of Web services is a critical decision factor. To fulfill the open business model such as cooperation among enterprises, several Web services can be composed into the upper level business transaction. In Web services composition, the reliability of services is more and more critical. Though each unit Web service can be reliable, the reliability of the composed service is not guaranteed. Thus a way to efficiently assess and select composed Web services is needed. In this paper, we define new metrics for measuring the trust value of Web services, and propose an evaluation method to predict the trustworthy degree of the composed services based on the metrics. We also define a conceptual framework to support optimal Web services selection based on the proposed trust evaluation method. By selecting using the quantitative measurement rather than intuitive selection of the service user, it allows the service users to select the high reliable service meeting their quality requirements well.

• Journal of the Korean Operations Research and Management Science Society
• /
• 제33권2호
• /
• pp.27-44
• /
• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권2호
• /
• pp.312-334
• /
• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• 제8권3호
• /
• pp.100-111
• /
• 2009

Cognitive radio is an advanced technology for efficient utilization of under-utilized spectrum via spectrum sensing. CR users should move from current allocating channel to empty channel to avoid the interference to the primary user if the primary user is allocating that channel. Thus, CR system cannot support the CR user's QoS(Quaiity of Service). In this paper, we propose dynamic frequency selection method based on Genetic Algorithm with power control. It is to find the optimization channel for satisfying various CR user's needs with the power control method to minimize the CR user's interference to the primary user. And, we propose the Genetic Algorithm(GA) which determines the best configuration for CR communication systems. The computer simulation results show that the proposed method guaranteed the primary user's decodability and the optimized solution for various channel status.