• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권8호
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• pp.1913-1925
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• 2012

In order to efficiently utilize limited radio resources, resource allocation schemes in OFDMA-based wireless networks have gained intensive attention recently. Instead of improving the throughput performance, the utility is adopted as the metric for resource allocation, which provides reasonable methods to build up the relationship between user experience and various quality-of-service (QoS) metrics. After formulating the optimization problem by using a weighted bipartite graph, a modified bipartite matching method is proposed to find a suboptimal solution for the resource allocation problem in OFDMA-based wireless systems with feasible computational complexity. Finally, simulation results are presented to validate the effectiveness of the proposed method.

• Journal of Information Processing Systems
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• 제7권4호
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• 대한임베디드공학회논문지
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• 제17권2호
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• pp.93-100
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• 2022

In this paper, we propose a machine learning-based method for supporting resource management of IoT software platforms in a multi-modal sensing scenario. We assume that an IoT device installed with a oneM2M-compatible software platform is connected with various sensors such as PIR, sound, dust, ambient light, ultrasonic, accelerometer, through different embedded system interfaces such as general purpose input output (GPIO), I2C, SPI, USB. Based on a collected dataset including CPU usage and user-defined priority, a machine learning model is trained to estimate the level of nice value required to adjust according to the resource usage patterns. The proposed method is validated by comparing with a rule-based control strategy, showing its practical capability in a multi-modal sensing scenario of IoT devices.

• 한국정보과학회논문지:시스템및이론
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• 제36권6호
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• pp.488-501
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• 2009

유비쿼터스 환경에서 모바일 단말기의 제한적인 자원 문제를 해결하기 위해 주변 자원을 실시간으로 공유하는 연구들이 진행되고 있다. 그리고 자원의 공유뿐만 아니라 상황 정보에 기반한 추론을 통해 개인 맞춤형 자원을 추천하는 연구도 활발히 진행되고 있다. 개인 맞춤형 자원 추천을 위하여 사용자의 기본 정보, 자원에 대한 선호도, 공유 대상이 되는 자원의 정보, 단말기의 위치, 시간과 같은 다양한 상황 정보는 효과적으로 공유 및 관리되어야 한다. 또한 신뢰성 있는 자원 추론을 위해 필요한 추론규칙을 검증하는 단계는 매우 중요하다. 이를 위해서 다양한 상황 정보를 구성하여 실제 단말기 상에서 자원 추론규칙이 올바르게 동작하는지 검증해야 하지만 이는 현실적으로 많은 비용과 시간이 필요하다. 따라서 본 논문애서는 이러한 문제점을 해결하기 위하석 추론 검증 도구를 제안한다. 제안하는 추론 검증도구는 편리한 그래픽 사용자 인터페이스를 제공하여 원하는 상황 정보를 쉽게 생성할 수 있고, 실제 단말기를 대신하여 동적인 상황 정보의 변경에 따른 추론을 정확하게 검증한다.

• 한국시뮬레이션학회논문지
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• 제23권1호
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• pp.1-10
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• 2014

클라우드 컴퓨팅은 분산 병렬 컴퓨팅의 일종으로 IT 자원을 가상화 하고 이를 사용자에게 제공한다. 그러나 사용자의 서비스 요청은 시간적 규칙성이 없으며, 이런 이유로 각 자원들은 가용성의 차이를 갖는다. 가용성의 차이는 클라우드 서비스 이용자의 QoS만족도 및 서비스 제공자 선택에 영향을 주게 된다. 본 논문에서는 클라우드 환경에서의 서비스 이용자의 요구에 따라 가상화된 IT자원 제공자의 효율적 선정을 위한 자원 가용성 기반 다중 경매 모델을 이용한 서비스 예약형 클라우드 자원거래 시스템을 제안한다. 제안한 시스템에서는 서비스 이용자의 서비스 요청 발생 시 두 번의 경매 모델을 사용하는 다중경매모델이며, 다중 경매 과정 중 단일 경매 단계에서 자원 가용성 평가 알고리즘 및 가변 큐를 이용한 서비스 예약방식을 적용하여 서비스 제공자의 자원 가용성을 평가하여 최적의 서비스 제공 자원을 찾는다. 제안모델은 QoS만족도 부분에서 앞서 작용한 자원 가용성 평가 알고리즘으로 인해 높은 성능을 보여주며, 작업 처리 시간활용도 면에서 QoS를 모두 고려한 상태로 안정적으로 더 많은 작업을 처리 할 수 있음을 입증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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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.

• IEIE Transactions on Smart Processing and Computing
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• 제2권3호
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• pp.160-167
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• 2013

Resource allocation based on quantized feedback plays a critical role in wireless mesh networks with a time division multiple access (TDMA) physical layer. In this study, a resource allocation problem was formulated based on quantized feedback for TDMA wireless mesh networks that minimize the total transmission power. Three steps were taken to solve the optimization problem. In the first step, the codebook of the power, rate and equivalent channel quantization threshold was designed. In the second step, the timeslot allocation criterion was deduced using the primal-dual method. In the third step, a resource allocation scheme was developed based on quantized feedback using the stochastic optimization tool. The simulation results show that the proposed scheme not only reduces the total transmission power, but also has the advantage of quantized feedback.

• 지식경영연구
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• 제7권2호
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• pp.35-52
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• 2006

Increasing competitive pressure, the constantly accelerating transformation of the economy, and a stronger focus on value creation have initiated the search for sustainable sources of competitive advantage in organizations. In this context, the concept of treating organizational knowledge as a valuable strategic resource has become quite popular recently. Knowledge has become the most critical component in the struggle for sustained competitive advantage and knowledge management (KM) has also been described for its possible role in creating sustainable competitive advantage. In order to examine the contingency between KM resources, KM strategies, and KM performance of organizations, a contingency model of KM, which is based on resource-based theory as well as knowledge-based theory, is developed from the information systems and strategic management literature in order to assess the following questions: (i) What KM resources affect the organization's KM strategies? (ii) Is there a relationship between KM strategies and organizational performance enhanced by KM? A detailed exploratory analysis of survey responses from 79 Korean companies provides the following significant findings: (i) This study found support for the proposed contingency model of KM; (ii) The organization's KM strategies are determined by social resources and its capabilities; (iii) An organization with a culture-based KM strategy is more likely to enhance organizational KM performance than an organization with a technology-based KM strategy.

• Journal of Information Processing Systems
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• 제7권1호
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• pp.173-186
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• 2011

Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.

• Journal of Computing Science and Engineering
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• 제7권1호
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• pp.44-52
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• 2013

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.