• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1174-1185
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• 2012

This paper proposes a call admission control scheme for delay guarantee in the wireless mesh networks. The admission of a new call is determined based on the expected delay inferred from the class level available bandwidth at nodes on the path. All nodes under the effects of the new call are considered in designing the call admission control scheme to maintain the delay guarantee of the pre-existing traffic. An effective technique for estimating the available bandwidth of the neighbor nodes is proposed with no addition of message interchanges. The class-level delay control is mainly performed by the queueing discipline while keeping the MAC operation simple. Simulations are performed to show the validity of the proposals. We observe acceptable performances in delay expectation with the addition of new calls. We also show that the proposed call admission control is helpful in guaranteeing the delay performances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1685-1690
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• 2006

The future mobile communication system should be operated with hierarchical cellular system for providing high quality multimedia services within limited wireless resources. In this paper, we have studied a call admission control scheme applied in hierarchical CDMA cellular system nested with macro, macro, and pico cells. When the proposed call admission control algorithm was applied we got 20% more system capacity than no admission control was applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1112-1122
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• 2008

This paper reviews the Parlay X and proposes SIP multimedia session control mechanism which is able to be implemented over IMS using Extended Call Control APIs of Parlay X. Parlay X is one of the industrial standards of Open API in the telecommunication to open network resources and capabilities to third party service providers. In this paper, SIP session control mechanism is described by depicting call flows of basic and essential session handling methods including session initiation, transfer, restoration, and termination. We also show how easy Parlay X Extended Call Control APIs can be used for the purpose of complicated calls handling in the IT applications. To verify feasibility of the blended services based on convergence of telecommunication and internet with regard to performance, we accomplish experimental performance of Extended Call Control APIs from IT application through open service gateway. We show Open API could be applied to next generation network based on IMS without serious degradation of the network performance.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.698-712
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• 2004

DiffServ network architecture does not define a call admission control procedure explicitly. In this paper, a new DiffServ QoS control mechanism is suggested which, after the call admission control, can execute packet process according to the class while, at the same time, executing on the flow based call admission control in the DiffServ network. Routers on the path from the source to the destination estimate the aggregated class traffic of the existing flows and the new incoming flow and then, perform a call admission control in accordance with the type of classes efficiently based on the required bandwidth per each class that can meet the user's QoS requirements. In order to facilitate the packet process according to the class after the flow based call admission control, a mechanism is suggested that can adjust the network resources to classes dynamically. The performance analysis on this mechanism is carried out through a simulation.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.440-445
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• 2016

There is a scheme where secondary users (SU) use predicted spectrum holes for primary users (PU) not to utilize for efficient utilization of the limited spectrum resources in cognitive radio networks. In this paper, we propose an adaptive call admission control framework that minimizes spectrum hopping call dropped probability (SHDP) for satisfying SU quality of service (QoS). The scheme is based on a call admission control (CAC), bandwidth prediction and adaptive bandwidth assignment. The prediction model predicts not only the number of spectrum holes, but requested bandwidth of SU spectrum hopping call, and then the CAC minimizes SHDP via an adaptive bandwidth assignment in resources not being enough for reservation. We bring Wiener prediction model to predict the resources. Simulations are conducted to compare the performance of proposed scheme with an existing, and show its ability of minimizing the SHDP.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.347-352
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• 2014

In this paper, we propose a Markovian queueing model(M/M/1)-based call admission control to reduce forced terminating rate of non-real secondary user's call for Multi-services Cognitive Radio Networks. A existing control has a problem that the forced terminating rate increases because of adopting a policy of spectrum priority allocation to real calls. In our scheme the rate can be reduced as the call that has no useful spectrum waits in a queue until getting an available spectrum. Our scheme use a neural-net based prediction of primary user's reappearance. Through the simulation, we analysis the call forced terminating rate, access delay and spectrum utilization efficiency, and then show that our scheme can more reduce the forced terminating rate of the call, compared to that of the existing algorithm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2188-2195
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• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.28-34
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• 1998

In most switching system, the processing unit is designed to work efficiently even at relatively high loads, but when the offered traffic exceeds a particular level, the rate of completed calls can fall drastically. A single call handled by the switching system consists of a sequence of events or messages that has to be processed by the control unit. The control unit is not only incapable of handling all of the offered calls, but also its call handling capability can drop as the offered load increases. The real time available for call processing is a critical resource that requires careful management. Therefore, the overloading of this resource must be detected by a subscriber in the from of a dial tone delay or an uncompleted call which is either blocked or mishandled. The subscriber may respond by either dialing prematurely or by re-attempting a call. This action can further escalate the processors load, which is spent for uncompleted calls. Unless a proper control is used, the switching system can finally break down. In this paper, we paper, we propose a fuzzy overload detection and control method for switching systems, which can by generating fuzzy rules via fuzzy aggregation networks. Simulation results involving a switching system is given.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.881-893
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• 2020

CFI(Control Flow Integrity) is a mitigation mechanism that protects programs by verifying control flows. IFCC(Indirect Function Call Checks) and SCS(Shadow Call Stack), CFI supported by LLVM Clang compiler, were introduced to protect applications in Android. IFCC protects function calls and SCS protects function returns. In this paper, we propose attacks to bypass CFI on the application environment with IFCC and SCS. Even if IFCC and SCS were applied to user applications, it was confirmed that there were many code segments not protected by IFCC and SCS in the application memory. We execute code in CFI unprotected segments to construct 1) bypassing IFCC to call a protected function, 2) modulating return address via SCS bypass. We identify code segments not protected by IFCC and SCS in Android10 QP1A. 191005.007.A3. We also implement proof-of-concept exploits to demonstrate that modulation of control flow is possible in an environment where IFCC and SCS are applied.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2070-2079
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• 1997

In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.