• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.288-297
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• 2003

The fast retransmit and fast recovery algorithm of TCP Reno, when multiple packets in the same window are lost, cannot recover them without RTO (Retransmission Timeout). TCP New-Reno can recover multiple lost packets by extending fast recovery using partial acknowledgement. If the retransmitted packet is lost again during fast recovery, however, RTO cannot be avoided. In this paper, we propose an algorithm called "Duplicate Acknowledgement Counting(DAC)" to alleviate this problem. DAC can detect the retransmitted packet loss by counting duplicate ACKs. Conditions that a lost packet can be recovered by loss recovery of TCP Reno, TCP New-Reno and TCP New-Reno using DAC are derived by modeling loss recovery behavior of each TCP. We calculate the loss recovery probability for random packet loss probability numerically, and show that DAC can improve loss recovery behavior of TCP New-Reno.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.13-28
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• 2009

Routing protocols in Delay/Disruption Tolerant Networks(DTN) are important to enhance the performance of transmission delay and delivery success ratio. In this paper, we propose an efficient DTN routing algorithm, called "Nobility Pattern based Routing(MPR)", that controls the total number of transferred message copies based on mobility patterns of mobile nodes. We consider a realistic "Levy walk" mobility pattern that has a super-diffusive property which well represents human mobility pattern. We implemented a DTN simulator using ONE simulator for the proposed MPR algorithm and Levy walk mobility pattern. Simulation results show that mobility patterns are very important for accurate evaluation of DTN routing performance, and the proposed MPR enhances the routing performance of delivery delay and success delivery ratio under realistic mobility pattern.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.527-534
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• 2023

Triple modular redundancy (TMR) systems can continue their mission by virtue of their structural redundancy even if one processor is attacked by faults. In this paper, we propose a new fault tolerance strategy by introducing checkpoints into the TMR system in which data saving and fault detection processes are separated while they corporate together in the conventional checkpoints. Faults in one processor are tolerated by synchronizing the state of three processors upon detecting faults. Simultaneous faults occurring to more than one processor are tolerated by re-executing the task from the latest checkpoint. We propose the checkpoint placement and fault detection strategy to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for the TMR system having the proposed checkpoint strategy, and derive the optimal fault detection and checkpoint interval.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.1-14
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• 2002

The most important issue in providing multimedia traffic on a mobile computing environments is to guarantee the mobile host(client) with consistent QoS(Quality of Service). However, the QoS negotiated between the client and network in one cell may not be honored due to client mobility, causing hand-offs between cells. In this paper, a call admission control mechanism is proposed to provide consistent QoS guarantees for multimedia traffics in a mobile computing environment. Each cell can reserve fractional bandwidths for hand-off calls to its adjacent cells. It is important to determine the right amount of reserved bandwidth for hand-off calls because the blocking probability of new calls may increase if the amount of reserved bandwidth is more than necessary. An adaptive bandwidth reservation based on an MPP(Mobility Pattern Profile) and a 2-tier cell structure has been proposed to determine the amount of bandwidth to be reserved in the cell and to control dynamically its amount based on its network condition. We also propose a call admission control based on this bandwidth reservation and "next-cell prediction" scheme using an MPP. In order to evaluate the performance of our call admission control mechanism, we measure the metrics such as the blocking probability of our call admission control mechanism, we measure the metrics such as the blocking probability of new calls, dropping probability of hand-off calls, and bandwidth utilization. The simulation results show that the performance of our mechanism is superior to that of the existing mechanisms such as NR-CAT1, FR-CAT1, and AR-CAT1.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.548-549
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• 2015

무인 잠수정은 자율 무인잠수정(이하 'AUV' 또는 '자율무인잠수정'을 혼용)과 원격조정잠수정(이하 'ROV'로 지칭)으로 분류를 할 수 있다. ROV는 테더 게이블로 인한 작업 범위의 한계와 운동성능 효율이 떨어지는 단점을 지니고 있어, 테더 케이블이 필요 없는 AUV에 대한 필요성이 증대되고 있다. 추측 항법 시스템인 관성 항법 시스템(inertial navigation system, 이하 'INS'로 지칭)은 외부 도움없이 관성측정 장치(inertial measurement unit, 이하 'IMU'로 지칭)를 활용하여 구성된 시스템을 말한다. IMU는 자이로 스코프(gyroscope), 가속도계(accelerometer), 지자기(magnetic)센서로 구성된 측정 장치로 3개의 센서를 사용하여 상호 보정을 통한 기동 체의 위치, 속도 및 자세 정보를 제공한다. 복합항법시스템은 추측항법시스템이 가지는 누적오차와 측위 항법시스템이 가지는 외부환경에 대한 단점을 상호 보완하는 방법으로 연구가 진행 중이다. 하지만 심해서 또는 해양의 특성에 따라 측위 시스템이 사용되지 못하기 때문에 추측 항법시스템의 다양한 관성 센서를 활용한 상로 보완과 신호처리 방법을 통한 연구 개발이 진행 중이다. 다양한 센서 정보를 통합하는 목적으로 칼만 필터와 같은 최적 필터기법이 보편적으로 사용되고 있다. 칼만 필터는 확률 선형 시스템에 대하여 공정잡음 및 측정 잡음이 가우시안 확률 분포를 따를 때 최적의 추정자가 된다. 또한 가우시안 조건을 만족하지 않는 경우에도 선형 추정자 중에 추정 오차의 분산이 가장 작은 추정자이다. 칼만 필터가 최상의 성능을 발휘 하려면 공정잡음과 측정 잡음의 실제 값을 정확히 알아내는 것이 중요하다. 잡음 수준에 대한 정보가 부정확 할 경우 칼만 필터는 발산 할 수 있기 때문에 시스템에서 잡음 수준의 공산은 칼만 필터의 최적 이득을 결정하는 중요한 요소로 추정치에 큰 영향을 준다. 따라서 칼만 필터를 추측항법시스템에 적용 시킬 경우 실제 모텔의 잡음 공분산을 정확히 추정할 수 있는 기법이 요구된다. 추측항법시스템은 다양한 센서를 활용하기 때문에 움직이는 기동 표적에 적용시 잡음공분상이 변하기 때문에 항법시스템이 저하 될 수 있다. 본 연구에서는 다양한 센서를 융합하여 해양 생체 로봇의 정밀 자세 제어가 가능한 시스템을 제안하고자 한다.

• 전자공학회논문지 IE
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• v.43 no.3
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• pp.41-48
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• 2006

In this paper, we propose a new active queue management (AQM) scheme by utilizing the predictability of the Internet traffic. The proposed scheme predicts future traffic input rate by using the auto-regressive (AR) time series model and determines the future congestion level by comparing the predicted input rate with the service rate. If the congestion is expected, the packet drop probability is dynamically adjusted to avoid the anticipated congestion level. Unlike the previous AQM schemes which use the queue length variation as the congestion measure, the proposed scheme uses the variation of the traffic input rate as the congestion measure. By predicting the network congestion level, the proposed scheme can adapt more rapidly to the changing network condition and stabilize the average queue length and its variation even if the traffic input level varies widely. Through ns-2 simulation study in varying network environments, we compare the performance among RED, Adaptive RED (ARED), REM, Predicted AQM (PAQM) and the proposed scheme in terms of average queue length and packet drop rate, and show that the proposed scheme is more adaptive to the varying network conditions and has shorter response time.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.137-146
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• 2008

Fault localization plays a significant role in enormous distributed system because it can identify root cause of observed faults automatically, supporting self-managing which remains an open topic in managing and controlling complex distributed systems to improve system reliability. Although many Artificial Intelligent techniques have been introduced in support of fault localization in recent research especially in increasing complex ubiquitous environment, the provided functions such as diagnosis and prediction are limited. In this paper, we propose fault localization for self-managing in performance evaluation in order to improve system reliability via learning and analyzing real-time streams of system performance events. We use probabilistic reasoning functions based on the basic Bayes' rule to provide effective mechanism for managing and evaluating system performance parameters automatically, and hence the system reliability is improved. Moreover, due to large number of considered factors in diverse and complex fault reasoning domains, we develop an efficient method which extracts relevant parameters having high relationships with observing problems and ranks them orderly. The selected node ordering lists will be used in network modeling, and hence improving learning efficiency. Using the approach enables us to diagnose the most probable causal factor with responsibility for the underlying performance problems and predict system situation to avoid potential abnormities via posting treatments or pretreatments respectively. The experimental application of system performance analysis by using the proposed approach and various estimations on efficiency and accuracy show that the availability of the proposed approach in performance evaluation domain is optimistic.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.53-63
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• 2008

Reader collision may occur when neighboring RFID readers use the same channel at the same time. Especially when the readers are operated in dense mode, even though many channels are available, because of frequent reader collisions we can not guarantee the performance of RFID readers. Conventional solutions such as FH(Frequency Hopping) or LBT(Listen Before Talk) are not effective in this situation because they can not schedule RFID readers effectively when RFID readers are operated in multi-channel, dense reader mode, In this paper, we propose a new RFID reader anti-collision algorithm which employs LBT, random backoff before channel access, and probabilistic channel hopping at the same time. While LBT and Random backoff before channel access reduces collisions between competing readers, probabilistic channel hopping increases channel utilization by adaptively changing the hopping probability by reflecting the reader density and utilization. Simulation results shows that our algorithm outperforms conventional methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.1-10
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• 2011

As requirements of embedded system get complicated, the tool for analyzing the reliability of embedded software is being needed. A probabilistic modeling is used as the way of analyzing the reliability of a software and to apply it to embedded software controlling multiple devices. So, it is necessary to specialize that to embedded software. Also, existing reliability analyzers should measure the transition probability of each condition in different ways and doesn't consider reusing the model once used. In this paper, we suggest a reliability analyzer for embedded software using embedded software Markov chin model and a unit testing tool. Embedded software Markov chain model is model specializing Markov chain model which is used for analyzing reliability to an embedded software. And a unit testing tool has host-target structure which is appropriate to development environment of embedded software. This tool can analyze the reliability more easily than existing tool by automatically measuring the transition probability between units for analyzing reliability from the result of unit testing. It can also directly apply the test result updated by unit testing tool by representing software model as a XML oriented document and has the advantage that many developers can access easily using the web oriented interface and SVN store. In this paper, we show reliability analyzing of a example by so doing show usefulness of reliability analyzer.