간행물

한국인터넷정보학회> KSII Transactions on Internet and Information Systems (TIIS)

KSII Transactions on Internet and Information Systems (TIIS) update

  • : 한국인터넷정보학회
  • : 공학분야  >  기타(공학)
  • : KCI등재
  • : SCI,SCOPUS
  • : 연속간행물
  • : 월간
  • : 1976-7277
  • :
  • :

수록정보
수록범위 : 1권1호(2007)~13권12호(2019) |수록논문 수 : 2,522
KSII Transactions on Internet and Information Systems (TIIS)
13권12호(2019년 12월) 수록논문
최근 권호 논문
| | | |

KCI등재 SCI SCOPUS

1Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance

저자 : Xingjuan Cai , Shaojin Geng , Penghong Wang , Lei Wang , Qidi Wu

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5785-5804 (20 pages)

다운로드

(기관인증 필요)

초록보기

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

KCI등재 SCI SCOPUS

2Weighted Adaptive Opportunistic Scheduling Framework for Smartphone Sensor Data Collection in IoT

저자 : Thejaswini M , Bong Jun Choi

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5805-5825 (21 pages)

다운로드

(기관인증 필요)

초록보기

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

KCI등재 SCI SCOPUS

3Tensor-based tag emotion aware recommendation with probabilistic ranking

저자 : Hyewon Lim , Hyoung-joo Kim

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5826-5841 (16 pages)

다운로드

(기관인증 필요)

초록보기

In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

KCI등재 SCI SCOPUS

4An Optimal Driving Support Strategy(ODSS) for Autonomous Vehicles based on an Genetic Algorithm

저자 : Surak Son , Yina Jeong , Byungkwan Lee

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5842-5861 (20 pages)

다운로드

(기관인증 필요)

초록보기

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes “An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles” which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

KCI등재 SCI SCOPUS

5Exact Outage Probability of Two-Way Decode-and-Forward NOMA Scheme with Opportunistic Relay Selection

저자 : Tan-phuoc Huynh , Pham Ngoc Son , Miroslav Voznak

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5862-5887 (26 pages)

다운로드

(기관인증 필요)

초록보기

In this paper, we propose a two-way relaying scheme using non-orthogonal multiple access (NOMA) technology. In this scheme, two sources transmit packets with each other under the assistance of the decode-and-forward (DF) relays, called as a TWDFNOMA protocol. The cooperative relays exploit successive interference cancellation (SIC) technique to decode sequentially the data packets from received summation signals, and then use the digital network coding (DNC) technique to encrypt received data from two sources. A max-min criterion of end-to-end signal-to-interference-plus-noise ratios (SINRs) is used to select a best relay in the proposed TWDFNOMA protocol. Outage probabilities are analyzed to achieve exact closed-form expressions and then, the system performance of the proposed TWDFNOMA protocol is evaluated by these probabilities. Simulation and analysis results discover that the system performance of the proposed TWDFNOMA protocol is improved when compared with a conventional three-timeslot two-way relaying scheme using DNC (denoted as a TWDNC protocol), a four-timeslot two-way relaying scheme without using DNC (denoted as a TWNDNC protocol) and a two-timeslot two-way relaying scheme with amplify-and-forward operations (denoted as a TWANC protocol). Particularly, the proposed TWDFNOMA protocol achieves best performances at two optimal locations of the best relay whereas the midpoint one is the optimal location of the TWDNC and TWNDNC protocols. Finally, the probability analyses are justified by executing Monte Carlo simulations.

KCI등재 SCI SCOPUS

6ValueRank: Keyword Search of Object Summaries Considering Values

저자 : Cai Zhi , Lan Xu , Su Xing , Lang Kun , Cao Yang

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5888-5903 (16 pages)

다운로드

(기관인증 필요)

초록보기

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.

KCI등재 SCI SCOPUS

7An Efficient Artificial Intelligence Hybrid Approach for Energy Management in Intelligent Buildings

저자 : Fazli Wahid , Lokman Hakim Ismail , Rozaida Ghazali , Muhammad Aamir

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5904-5927 (24 pages)

다운로드

(기관인증 필요)

초록보기

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

KCI등재 SCI SCOPUS

8Efficient routing in multicast mesh by using forwarding nodes and weighted cost function

저자 : Kapila Vyas , Ajay Khuteta , Amit Chaturvedi

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5928-5947 (20 pages)

다운로드

(기관인증 필요)

초록보기

Multicast Mesh based Mobile Ad-hoc NETworks (MANETs) provide efficient data transmission in energy restraint areas without a fixed infrastructure. In this paper, the authors present an improved version of protocol SLIMMER developed by them earlier, and name it SLIMMER-SN. Most mesh-based protocols suffer from redundancy; however, the proposed protocol controls redundancy through the concept of forwarding nodes. The proposed protocol uses remaining energy of a node to decide its energy efficiency. For measuring stability, a new metric called Stability of Node (SN) has been introduced which depends on transmission range, node density and node velocity. For data transfer, a weighted cost function selects the most energy efficient nodes / most stable nodes or a weighted combination of both. This makes the node selection criteria more dynamic. The protocol works in two steps: (1) calculating SN and (2) using SN value in the weighted cost function for selection of nodes.
The study compared the proposed protocol, with other mesh-based protocols PUMA and SLIMMER, based on packet delivery ratio (PDR), throughput, end-to-end delay and average energy consumption under different simulation conditions. Results clearly demonstrate that SLIMMER-SN outperformed both PUMA and SLIMMER.

KCI등재 SCI SCOPUS

9Strengthening Packet Loss Measurement from the Network Intermediate Point

저자 : Haoliang Lan , Wei Ding , Yumei Zhang

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5948-5971 (24 pages)

다운로드

(기관인증 필요)

초록보기

Estimating loss rates with the packet traces captured from some point in the middle of the network has received much attention within the research community. Meanwhile, existing intermediate-point methods like [1] require the capturing system to capture all the TCP traffic that crosses the border of an access network (typically Gigabit network) destined to or coming from the Internet. However, limited to the performance of current hardware and software, capturing network traffic in a Gigabit environment is still a challenging task. The uncaptured packets will affect the total number of captured packets and the estimated number of packet losses, which eventually affects the accuracy of the estimated loss rate. Therefore, to obtain more accurate loss rate, a method of strengthening packet loss measurement from the network intermediate point is proposed in this paper. Through constructing a series of heuristic rules and leveraging the binomial distribution principle, the proposed method realizes the compensation for the estimated loss rate. Also, experiment results show that although there is no increase in the proportion of accurate estimates, the compensation makes the majority of estimates closer to the accurate ones.

KCI등재 SCI SCOPUS

10A Hybrid Mechanism of Particle Swarm Optimization and Differential Evolution Algorithms based on Spark

저자 : Debin Fan , Jaewan Lee

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 12호 발행 연도 : 2019 페이지 : pp. 5972-5989 (18 pages)

다운로드

(기관인증 필요)

초록보기

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

123
권호별 보기
가장 많이 인용된 논문

(자료제공: 네이버학술정보)

가장 많이 인용된 논문
| | | |
1연안해역에서 석유오염물질의 세균학적 분해에 관한 연구

(2006)홍길동 외 1명심리학41회 피인용

다운로드

2미국의 비트코인 규제

(2006)홍길동심리학41회 피인용

다운로드

가장 많이 참고한 논문

(자료제공: 네이버학술정보)

가장 많이 참고한 논문

다운로드

2미국의 비트코인 규제

(2006)홍길동41회 피인용

다운로드

해당 간행물 관심 구독기관

고려대학교 서강대학교 University of British Columbia(CANADA) 한양대학교 American University Library
 6
 5
 5
 4
 3
  • 1 고려대학교 (6건)
  • 2 서강대학교 (5건)
  • 3 University of British Columbia(CANADA) (5건)
  • 4 한양대학교 (4건)
  • 5 American University Library (3건)
  • 6 단국대학교 (2건)
  • 7 아주대학교 (2건)
  • 8 SK 주식회사(구 SK C&C) (2건)
  • 9 성균관대학교 (2건)
  • 10 전북대학교 (2건)

내가 찾은 최근 검색어

최근 열람 자료

맞춤 논문

보관함

내 보관함
공유한 보관함

1:1문의

닫기