• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.324-330
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• 2011

To avoid collisions, IEEE 802.11 medium access control (MAC) uses predetermined inter-frame spaces and the random back-off process. However, the retransmission strategy of IEEE 802.11 MAC results in considerable time wastage. The hidden node problem is well known in wireless networks; it aggravates the consequences of time wastage for retransmission. Many collision prevention and recovery approaches have been proposed to solve the hidden node problem, but all of them have complex control overhead. In this paper, we propose a fast retransmission scheme as a recovery approach. The proposed scheme identifies collisions caused by hidden nodes and then allows retransmission without collision. Analysis and simulations show that the proposed scheme has greater throughput than request-to-send and clear-to-send (RTS/CTS) and a shorter average waiting time.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.17-32
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• 2023

Centralized hierarchical routing protocols are often used to solve the problems of uneven energy consumption and short network life in wireless sensor networks (WSNs). Clustering and cluster head election have become the focuses of WSNs. In this paper, an energy balanced clustering routing algorithm optimized by sine cosine algorithm (SCA) is proposed. Firstly, optimal cluster head number per round is determined according to surviving node, and the candidate cluster head set is formed by selecting high-energy node. Secondly, a random population with a certain scale is constructed to represent a group of cluster head selection scheme, and fitness function is designed according to inter-cluster distance. Thirdly, the SCA algorithm is improved by using monotone decreasing convex function, and then a certain number of iterations are carried out to select a group of individuals with the minimum fitness function value. From simulation experiments, the process from the first death node to 80% only needs about 30 rounds. This improved algorithm balances the energy consumption among nodes and avoids premature death of some nodes. And it greatly improves the energy utilization and extends the effective life of the whole network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1404-1415
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• 2022

The 2-dimensional arrangement method of nodes has been used in most of RF (Radio Frequency) based communication network simulations. However, this method is not useful for the an none-obstacle 3-dimensional space networks in which the propagation delay speed in communication is very slow and, moreover, the values of performance factors such as the communication speed and the error rate change on the depth of node. Such a typical example is an underwater communication network. The 2-dimensional arrangement method is also not useful for the RF based network like some WSNs (Wireless Sensor Networks), IBSs (Intelligent Building Systems), or smart homes, in which the distance between nodes is short or some of nodes can be arranged overlapping with their different heights in similar planar location. In such cases, the 2-dimensional network simulation results are highly inaccurate and unbelievable so that they lead to user's erroneous predictions and judgments. For these reasons, in this paper, we propose a method to place uniformly and randomly communication nodes in 3-dimensional network space, making the wireless link with neighbor node possible. In this method, based on the communication rage of the node, blocks are generated to construct the 3-dimensional network and a node per one block is generated and placed within a block area. In this paper, we also introduce an algorithm based on this method and we show the performance results and evaluations on the average time in a node generation and arrangement, and the arrangement time and scatter-plotted visualization time of all nodes according to the number of them. In addition, comparison with previous studies is conducted. As a result of evaluating the performance of the algorithm, it was found that the processing time of the algorithm was proportional to the number of nodes to be created, and the average generation time of one node was between 0.238 and 0.28 us. ultimately, There is no problem even if a simulation network with a large number of nodes is created, so it can be sufficiently introduced at the time of simulation.

• 한국정보통신학회논문지
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• 제23권5호
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• pp.581-588
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• 2019

본 논문에서는 슬롯화된 ALOHA 센서 네트워크에서 노드의 전송 공평성을 향상하기 위한 변형된 백오프 알고리즘을 제안한다. 계층화된 네트워크 구조에서 하위 노드들에 의해 전송된 데이터를 종합하여 처리해야하는 경우 하위 특정 노드의 성능 저하는 전체 시스템의 성능 저하를 야기할 수 있다. 따라서 네트워크에 참여하는 모든 노드에게 공평한 전송 성능을 보장하는 것이 중요하다. 제안하는 기법에서는 현재의 전송 결과 뿐 아니라 과거의 전송 결과를 고려하여 노드의 전송 대기 시간을 선정한다. 또한 연속적으로 전송에 실패한 노드에게는 점차 짧은 대기시간을 부여하고 연속적으로 전송한 성공한 노드에게는 점차 긴 대기시간을 부여한다. 이를 통해 전송 공평성을 향상시킨다. 시뮬레이션을 통해 제안하는 기법의 성능을 대표적인 백오프 알고리즘인 BEB(binary exponential back-off) 알고리즘과 비교, 분석한다. 실험 결과 제안하는 기법을 적용했을 때 BEB에 비해 전송용량은 다소 저하(최대 5.8%, 최소 2.0%, 평균 3.0%)되지만 공평성은 크게 향상(최대 13.4%, 최소 3.6%, 평균 9.0%)됨을 확인하였다.

• International Journal of Contents
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• 제7권4호
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• pp.35-43
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• 2011

USN is a technology to detect human external environment. It is an important factor in buildinga ubiquitous computing environment. In this thesis, an authentication method was proposed to allow the sensor nodes, which have weak computing operation capability, to safely communicate with each other in USN and guarantee the anonymity of users for their privacy. In the proposed authentication method that takes into account the characteristics of sensor network, sensor nodes based on a symmetric key algorithm do not transfer keys directly, instead, they mix the random numbers received from AS to generate keys necessary for communications, having a master key and a pseudo-random number generator.In addition, in this thesis, TA was adopted to minimize the leakage of users' information, and a scheme through which virtual IDs received from AS are delivered to sensor nodes was applied to improve anonymity.

• Smart Structures and Systems
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• 제20권1호
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• 대한산업공학회지
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• 제41권4호
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• pp.338-343
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• 2015

We suggest a method to configure feature functions of continuous conditional random field (C-CRF). Regression tree and similarity analysis are introduced to construct the first and second feature functions of C-CRF, respectively. Rules from the regression tree are transformed to logic functions. If a logic in the set of rules is true for a data then it returns the corresponding value of leaf node and zero, otherwise. We build an Euclidean similarity matrix to define neighborhood, which constitute the second feature function. Using two feature functions, we make a C-CRF model and an illustrate example is provided.

• Communications for Statistical Applications and Methods
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• 제29권5호
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• pp.561-589
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• 2022

When multiple classifications and regression trees are combined, tree-based ensemble models, such as random forest (RF) and Bayesian additive regression trees (BART), are produced. We compare the model structures and performances of various ensemble models for regression settings in this study. RF learns bootstrapped samples and selects a splitting variable from predictors gathered at each node. The BART model is specified as the sum of trees and is calculated using the Bayesian backfitting algorithm. Throughout the extensive simulation studies, the strengths and drawbacks of the two methods in the presence of missing data, high-dimensional data, or highly correlated data are investigated. In the presence of missing data, BART performs well in general, whereas RF provides adequate coverage. The BART outperforms in high dimensional, highly correlated data. However, in all of the scenarios considered, the RF has a shorter computation time. The performance of the two methods is also compared using two real data sets that represent the aforementioned situations, and the same conclusion is reached.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.55-62
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• 2023

Slotted-Aloha (S-Aloha) has been widely employed in random access networks owing to its simple implementation in a distributed manner. To enhance the throughput performance of the S-Aloha, connection-based slotted-Aloha (CS-Aloha) has been proposed in recent years. The fundamental principle of the CS-Aloha is to establish a connection with a short-sized request packet before transmitting data packets. Subsequently, the connected node transmits long-sized data packets in a batch of size M. This approach efficiently reduces collisions, resulting in improved throughput compared to the S-Aloha, particularly for a large M. In this paper, we address the short-term fairness of the CS-Aloha, as quantified by Jain's fairness index. Specifically, we evaluate how equitably the CS-Aloha allocatestime slots to all nodes in the network within a finite time interval. Through simulation studies, we identify the impact of system parameters on the short-term fairness of the CS-Aloha and propose an optimal transmission probability to support short-term fairness.