• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.4
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• pp.31-51
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• 2008

Predicting the preferences of users and providing the personalized services/products based on users' preferences is one of the important issues. However, the research considering users' preferences on context-aware computing is a relatively insufficient research field. Hence, this paper aims to propose a framework for providing the personalized services based on context history in context-aware computing. Based on this framework, we have implemented a prototype system to show the feasibility of the framework. Previous researches have reasoned the preferences of the user considering only the user's input, but this research provides the personalized services using the relationship between users' profile and services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1282-1301
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• 2015

Traditional infrastructure has been superseded by cloud computing, due to its cost-effective and ubiquitous computing model. Cloud computing not only brings multitude of opportunities, but it also bears some challenges. One of the key challenges it faces is recovery of computing nodes, when an Information Technology (IT) failure occurs. Since cloud computing mainly depends upon its nodes, physical servers, that makes it very crucial to recover a failed node in time and seamlessly, so that the customer gets an expected level of service. Work has already been done in this regard, but it has still proved to be trivial. In this study, we present a Cost-Time aware Genetic scheduling algorithm, referred to as CTaG, not only to globally optimize the performance of the cloud system, but also perform recovery of failed nodes efficiently. While modeling our work, we have particularly taken into account the factors of network bandwidth and customer's monetary cost. We have implemented our algorithm and justify it through extensive simulations and comparison with similar existing studies. The results show performance gain of our work over the others, in some particular scenarios.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.304-318
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• 2007

Grid computing is a service that share geographically distributed computing resources through high speed network. In this paper, we propose hybrid scheduling scheme which considers not only meta-scheduling scheme to distribute the job between the nodes of grid computing system but also the job scheduling to distribute the job within the local nodes. According to the number of processors needed and expected execution time, the job with high priority is allocated to job queue while the one with low priority and remote job are allocated to backfill queue. We evaluate the proposing scheme through the various experiments and the results show that the utilization of grid computing system increases and the job slowdown decreases.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.2
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• pp.27-32
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• 2018

One of the crucial issues in mobile edge cloud computing environments is to monitor mobile devices. Due to the inherit properties of mobile devices, they are prone to unstable behavior that leads to failures. In order to satisfy the service level agreement (SLA), the mobile edge cloud administrators should take appropriate measures through a monitoring scheme. In this paper, we propose a monitoring scheme of mobile devices based on artificial intelligence in mobile edge cloud computing environments. The proposed monitoring scheme is able to measure faults of mobile devices based on previous and current monitoring information. To this end, we adapt the hidden markov chain model, one of the artificial intelligence technologies, to monitor mobile devices. We validate our monitoring scheme based on the hidden markov chain model. The proposed monitoring scheme can also be used in general cloud computing environments to monitor virtual machines.

• The Journal of Korean Association of Computer Education
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• v.13 no.5
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• pp.103-110
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• 2010

If an exterior computer wants to join the Grid/cloud computing platform for a while, all of the related firewalls' filtering rule should be immediately updated. As the platform of Internet application is gradually evolving into the Grid/Cloud environment, the R&D requirement for the dynamic traversing of the multiple firewalls by a single try is also increasing. In this paper, we introduce the new mechanism for the dynamic traversing of the multiple firewalls using the concept of the one-time master key that can dynamically unlock the tiers of firewalls simultaneously instead of the existed filtering rule based method like a lock management at each firewall. The proposed master keys are like one-time password, consisted of IP addresses, port numbers, and TCP's initial sequence numbers, and generated by end users not administrators. They're exchanged mutually in advance and used to make a hole at local-side firewalls for the other's packet incoming. Therefore, the proposed mechanism can function regardless of the number or type of firewalls.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.21-26
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• 2008

It was already realized at a current technological level of home network systems that the systems recognizes a user's simple order and carry out the order in the ubiquitous computing environment. However home is not a simple environment consisting into a large number of family members, so various order and situation would be needed accordingly. From now on we need to reach the technological level to infer that how is the user's behavior patterns and what kinds of service is the fittest to user who belong to the ubiquitous computing environment by using the result of the context interpreter. In this regards, active inferred-model needs to be suggested upgrading user's command into one step more higher level than the simple one adapting diversified feature. This study would like to suggest this active model recognizing context, which is user's environmental information applying basic network and inferring Context-based Service that user wants through the recognized result This study proposes a new method that can infer the user's desire in ubiquitous computing environment. First of all, we define a context as user's information of ubiquitous computing environment situation that user belongs to and we classify the context into 4W1H(Where, Who, When, What) formats. We construct Bayesian network and put the factor of context use as Bayesian network nodes. As a result, we can infer the user's behavior pattern and most proper service for user in the intelligent space from the probabilistic result of Bayesian network.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.491-494
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• 1998

This paper describes the design and implementation of file system which allows the collaborative computing in mobile environment. The design goal is to make a logically one file system in the distributed computer systems. The characteristics of frequent, foreseeable and variable disconnections in a mobile environment wrer taken into consideration. We introduce an auto-hoarding system that provides the availability of large number of nodes which are weakly and intermittently connected. The data consistency problems in distributed or replicated mobile data are also discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.521-524
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• 2003

In this paper, we propose a design process of 'personalized' classification with soft computing techniques. Based on human's thinking way, a construction methodology for personalized classifier is mentioned. Here, two fuzzy similarity measures and ensemble of classifiers are effectively used. As one of the possible applications, facial expression recognition problem is discussed. The numerical result shows that the proposed method is very useful for on-line learning, reusability of previous knowledge and so on.

• Journal of Communications and Networks
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• v.10 no.3
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• pp.316-330
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• 2008

This paper proposes a novel method for transporting various types of user traffic effectively over the next generation network called integrated services digital network 3 (ISDN3) (or quantum network) using quantum packets. Basically, a quantum packet comprises one or more 53-byte quanta as generated by a "quantumization" process. While connection-oriented traffic is supported by fixed-size quantum packets each with one quantum to emulate circuit switching, connectionless traffic (e.g., IP packets and active packets) is carried by variable-size quantum packets with multiple quanta to support store-and-forward switching/routing. Our aim is to provide frame-like or datagram-like services while enabling cell-based multiplexing. The quantum packet method also establishes a flexible and extensible framework that caters for future packetization needs while maintaining backward compatibility with ATM. In this paper, we discuss the design of the quantum packet method, including its format, the "quantumization" process, and support for different types of user traffic. We also present an analytical model to evaluate the consumption of network resources (or network costs) when quantum packets are employed to transfer loss-sensitive data using three different approaches: cut-through, store-and-forward and ideal. Close form mathematical expressions are obtained for some situations. In particular, in terms of network cost, we discover two interesting equivalence phenomena for the cut-through and store-and-forward approaches under certain conditions and assumptions. Furthermore, analytical and simulation results are presented to study the system behavior. Our analysis provides valuable insights into the. design of the ISDN3/quantum network.