• 제목/요약/키워드: trend algorithm

검색결과 431건 처리시간 0.029초

SVC 멀티캐스트 메커니즘에 관한 설계 (A Design of SVC Multicast Mechanism)

  • 고휘;이형옥;곽용완;남지승
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 추계학술발표대회
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    • pp.573-576
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    • 2011
  • Research on 4A(Any-time, Any-where, Any-device, Any-contents) services for the next-generation multimedia services is developed with the trend of the integration of wire and wireless networks and the convergence of telecommunications and broadcasting. In this paper we proposed a design of SVC(Scalable Video Coding) overlay multicast mechanism which can provide typical next-generation multimedia services such as SVC streaming. A novel overlay multicast algorithm called ACK-Flow tree optimization algorithm is proposed to guarantee SVC streaming with high efficiency.

Ensuring Data Confidentiality and Privacy in the Cloud using Non-Deterministic Cryptographic Scheme

  • John Kwao Dawson;Frimpong Twum;James Benjamin Hayfron Acquah;Yaw Missah
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.49-60
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    • 2023
  • The amount of data generated by electronic systems through e-commerce, social networks, and data computation has risen. However, the security of data has always been a challenge. The problem is not with the quantity of data but how to secure the data by ensuring its confidentiality and privacy. Though there are several research on cloud data security, this study proposes a security scheme with the lowest execution time. The approach employs a non-linear time complexity to achieve data confidentiality and privacy. A symmetric algorithm dubbed the Non-Deterministic Cryptographic Scheme (NCS) is proposed to address the increased execution time of existing cryptographic schemes. NCS has linear time complexity with a low and unpredicted trend of execution times. It achieves confidentiality and privacy of data on the cloud by converting the plaintext into Ciphertext with a small number of iterations thereby decreasing the execution time but with high security. The algorithm is based on Good Prime Numbers, Linear Congruential Generator (LGC), Sliding Window Algorithm (SWA), and XOR gate. For the implementation in C, thirty different execution times were performed and their average was taken. A comparative analysis of the NCS was performed against AES, DES, and RSA algorithms based on key sizes of 128kb, 256kb, and 512kb using the dataset from Kaggle. The results showed the proposed NCS execution times were lower in comparison to AES, which had better execution time than DES with RSA having the longest. Contrary, to existing knowledge that execution time is relative to data size, the results obtained from the experiment indicated otherwise for the proposed NCS algorithm. With data sizes of 128kb, 256kb, and 512kb, the execution times in milliseconds were 38, 711, and 378 respectively. This validates the NCS as a Non-Deterministic Cryptographic Algorithm. The study findings hence are in support of the argument that data size does not determine the execution.

EEDARS: An Energy-Efficient Dual-Sink Algorithm with Role Switching Mechanism for Event-Driven Wireless Sensor Networks

  • Eslaminejad, Mohammadreza;Razak, Shukor Abd;Ismail, Abdul Samad Haji
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권10호
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    • pp.2473-2492
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    • 2012
  • Energy conservation is a vital issue in wireless sensor networks. Recently, employing mobile sinks for data gathering become a pervasive trend to deal with this problem. The sink can follow stochastic or pre-defined paths; however the controlled mobility pattern nowadays is taken more into consideration. In this method, the sink moves across the network autonomously and changes its position based on the energy factors. Although the sink mobility would reduce nodes' energy consumption and enhance the network lifetime, the overhead caused by topological changes could waste unnecessary power through the sensor field. In this paper, we proposed EEDARS, an energy-efficient dual-sink algorithm with role switching mechanism which utilizes both static and mobile sinks. The static sink is engaged to avoid any periodic flooding for sink localization, while the mobile sink adaptively moves towards the event region for data collection. Furthermore, a role switching mechanism is applied to the protocol in order to send the nearest sink to the recent event area, hence shorten the path. This algorithm could be employed in event-driven and multi-hop scenarios. Analytical model and extensive simulation results for EEDARS demonstrate a significant improvement on the network metrics especially the lifetime, the load and the end-to-end delay.

Sequential Pattern Mining for Intrusion Detection System with Feature Selection on Big Data

  • Fidalcastro, A;Baburaj, E
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.5023-5038
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    • 2017
  • Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

A modified simulated annealing search algorithm for scheduling of chemical batch processes with CIS policy

  • Kim, Hyung-Joon;Jung, Jae-Hak
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.319-322
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    • 1995
  • As a trend toward multi-product batch processes is increasing in Chemical Process Industry (CPI), multi-product batch scheduling has been actively studied. But the optimal production scheduling problems for multi-product batch processes are known as NP-complete. Recently Ku and Karimi [5] have studied Simulated Annealing(SA) and Jung et al.[6] have developed Modified Simulated Annealing (MSA) method which was composed of two stage search algorithms for scheduling of batch processes with UIS and NIS. Jung et al.[9] also have studied the Common Intermediate Storage(CIS) policy which have accepted as a high efficient intermediate storage policy. It can be also applied to pipeless mobile intermediate storage pacilities. In spite of these above researches, there have been no contribution of scheduling of CIS policy for chemical batch processes. In this paper, we have developed another MSA for scheduling chemical batch processes with searching the suitable control parameters for CIS policy and have tested the this algorithm with randomly generated various scheduling problems. From these tests, MSA is outperformed to general SA for CIS batch process system.

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수정된 선형계획법을 이용한 다물체 탄성 접촉 문제 해석 (Multibody Elastic Contact Analysis by Modified Linear Programming)

  • 이대희;전범준;최동훈;임장근;윤갑영
    • 대한기계학회논문집
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    • 제13권1호
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    • pp.1-8
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    • 1989
  • 본 연구에서는 마찰을 무시할 수 있는 경우의 일반적인 다물체 탄성 접촉 문제를 수식화하고 이를 최적화 문제로 변환한 후 수정된 선형 계획법을 이용하여 임의 형상의 다물체간의 접촉 문제를 해석할 수 있는 산법을 제시하였다.

Tradeoff between Energy-Efficiency and Spectral-Efficiency by Cooperative Rate Splitting

  • Yang, Chungang;Yue, Jian;Sheng, Min;Li, Jiandong
    • Journal of Communications and Networks
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    • 제16권2호
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    • pp.121-129
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    • 2014
  • The trend of an increasing demand for a high-quality user experience, coupled with a shortage of radio resources, has necessitated more advanced wireless techniques to cooperatively achieve the required quality-of-experience enhancement. In this study, we investigate the critical problem of rate splitting in heterogeneous cellular networks, where concurrent transmission, for instance, the coordinated multipoint transmission and reception of LTE-A systems, shows promise for improvement of network-wide capacity and the user experience. Unlike most current studies, which only deal with spectral efficiency enhancement, we implement an optimal rate splitting strategy to improve both spectral efficiency and energy efficiency by exploring and exploiting cooperation diversity. First, we introduce the motivation for our proposed algorithm, and then employ the typical cooperative bargaining game to formulate the problem. Next, we derive the best response function by analyzing the dual problem of the defined primal problem. The existence and uniqueness of the proposed cooperative bargaining equilibrium are proved, and more importantly, a distributed algorithm is designed to approach the optimal unique solution under mild conditions. Finally, numerical results show a performance improvement for our proposed distributed cooperative rate splitting algorithm.

인공지능 기반 에너지 효율화 방안 연구: 혼합적 연구방법론 중심으로 (A Study on Energy Efficiency Plan based on Artificial Intelligence: Focusing on Mixed Research Methodology)

  • 이문범;마태영
    • 한국IT서비스학회지
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    • 제21권5호
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    • pp.81-94
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    • 2022
  • This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

Emotion-aware Task Scheduling for Autonomous Vehicles in Software-defined Edge Networks

  • Sun, Mengmeng;Zhang, Lianming;Mei, Jing;Dong, Pingping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3523-3543
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    • 2022
  • Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

한강수질 평가를 위한 COD (화학적 산소 요구량) 모델 평가 (Chemical Oxygen Demand (COD) Model for the Assessment of Water Quality in the Han River, Korea)

  • Kim, Jae Hyoun;Jo, Jinnam
    • 한국환경보건학회지
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    • 제42권4호
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    • pp.280-292
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    • 2016
  • Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.