• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4864-4882
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• 2016

In this work, we consider the optimization problem of minimizing energy consumption for real-time multicast over wireless multi-hop networks. Previously, a distributed primal-dual subgradient algorithm was used for finding a solution to the optimization problem. However, the traditional subgradient algorithms have drawbacks in terms of i) sensitivity to iteration parameters; ii) need for saving previous iteration results for computing the optimization results at the current iteration. To overcome these drawbacks, using a joint network coding and scheduling optimization framework, we propose a novel distributed primal-dual Random Deflected Subgradient (RDS) algorithm for solving the optimization problem. Furthermore, we derive the corresponding recursive formulas for the proposed RDS algorithm, which are useful for practical applications. In comparison with the traditional subgradient algorithms, the illustrated performance results show that the proposed RDS algorithm can achieve an improved optimal solution. Moreover, the proposed algorithm is stable and robust against the choice of parameter values used in the algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3120-3137
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• 2021

Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.203-208
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• 2022

The occurrence of Type 2 Diabetes Mellitus (T2DM) is hoarding globally. All kinds of Diabetes Mellitus is controlled to disrupt over 415 million grownups worldwide. It was the seventh prime cause of demise widespread with a measured 1.6 million deaths right prompted by diabetes during 2016. Over 90% of diabetes cases are T2DM, with the utmost persons having at smallest one other chronic condition in UK. In valuation of contemporary applications of Big Data (BD) to Diabetes Medicare by sighted its upcoming abilities, it is compulsory to transmit out a bottomless revision over foremost theoretical literatures. The long-term growth in medicine and, in explicit, in the field of "Diabetology", is powerfully encroached to a sequence of differences and inventions. The medical and healthcare data from varied bases like analysis and treatment tactics which assistances healthcare workers to guess the actual perceptions about the development of Diabetes Medicare measures accessible by them. Apache Spark extracts "Resilient Distributed Dataset (RDD)", a vital data structure distributed finished a cluster on machines. Machine Learning (ML) deals a note-worthy method for building elegant and automatic algorithms. ML library involving of communal ML algorithms like Support Vector Classification and Random Forest are investigated in this projected work by using Jupiter Notebook - Python code, where significant quantity of result (Accuracy) is carried out by the models.

• 한국통신학회논문지
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• 제42권3호
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• pp.545-553
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• 2017

본 논문에서는 중앙제어 형 기반 시설 없이 단말 간 자율적인 협력을 통해 무선 통신을 수행하는 분산 네트워크에서 단말 간 동기 획득을 위한 분산 동기 알고리즘에 관해 연구하였다. 무선 통신을 수행하기 위해 단말 간 동기는 필수적으로 획득되어야 하고, 따라서 이를 위한 다양한 분산 동기 알고리즘들이 활발히 연구되어 왔다. 하지만 대부분의 분산 동기 알고리즘에 관한 연구는 네트워크에 속한 모든 단말이 예외 없이 규칙을 따르는 경우에 한정되어 있다. 이 때문에 하나 이상의 단말이 기능 고장을 일으켜 오작동을 유발하거나, 혹은 단말 간 동기 획득을 방해할 목적으로 의도적인 오작동을 일으키는 단말이 네트워크에 존재하는 경우 기존 분산 동기 알고리즘으로는 단말 간 동기 획득을 보장할 수 없다. 이에 본 논문에서는 오작동이 존재하는 분산 네트워크에서도 효과적으로 단말 간 동기를 획득할 수 있는 신뢰도 기반의 적응적 컨센서스 알고리즘을 제안하고 실험적으로 검증하였다.

• 한국통신학회논문지
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• 제24권6A호
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• pp.803-819
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• 1999

본 논문은 무선 ATM 서비스를 위한 CDMA WATM 시스템을 제시하며, 매체 접속 방식으로 전송 스케줄링과 슬롯 및 무선 링크 할당 알고리즘을 가진 중앙 제어 예약 접속 방식 (CRMA/TSDA)을 제안한다. 또한, 본 논문에서는 CDMA WATM 시스템을 위한 무선 접속 및 링크 제어 방식으로 지역정보 슬롯 및 링크 할당 알고리즘과 광역정보 슬롯 및 링크 할당 알고리즘을 제안하고, 모의 실험을 통하여 양방향 링크에서의 시스템 용량과 성능을 분석하였다. 제시된 접속 방식 및 제어 방식은 기존의 CDMA 랜덤 접속 방식에 비해 만족할 만한 성능을 보이며, ATM 서비스의 요구 품질을 만족시키며 수용할 수 있다. 특히, 지역 정보 제어 방식은 준최적의 광역 정보 방식에 견줄만한 성능을 갖는다.

• 산업공학
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• 제22권3호
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• pp.278-286
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• 2009

The anti-collision algorithms to identify a number of tags in real-time in RFID systems are divided into the anti-collision algorithms based on the Framed slotted ALOHA that randomly select multiple slots to identify the tags, and the anti-collision algorithms based on the Tree-based algorithm that repeat the questions and answer process to identify the tags. In the hybrid algorithm which is combined the advantages of these algorithms, tags are distributed over the frames by selecting one frame among them and then identified by using the Query tree frame by frame. In this hybrid algorithm, however, the time of identifying all tags may increase if many tags are concentrated in a few frames. In this study, to improve the performance of the hybrid algorithm, we suggest an improved algorithm that the tags select a specific group of frames based on the earlier bits of the tag ID so that the tags are distribute equally over the frames. By using the simulation and mathematical analysis, we show that the suggested algorithm outperforms traditional hybrid algorithm from the viewpoint of the number of queries per frame and the time of identifying all tags.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3293-3311
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• 2015

Cloud services are required to be composed as a single service to fulfill the workflow applications. Service composition in Cloud raises new challenges caused by the diversity of users with different QoS requirements and vague preferences, as well as the development of cloud computing having geographically distributed characteristics. So the selection of the best service composition is a complex problem and it faces trade-off among various QoS criteria. In this paper, we propose a Cloud service composition approach based on evolutionary algorithms, i.e., NSGA-II and MOPSO. We utilize the combination of multi-objective evolutionary approaches and Decision-Making method (AHP) to solve Cloud service composition optimization problem. The weights generated from AHP are applied to the Crowding Distance calculations of the above two evolutionary algorithms. Our algorithm beats single-objective algorithms on the optimization ability. And compared with general multi-objective algorithms, it is able to precisely capture the users' preferences. The results of the simulation also show that our approach can achieve a better scalability.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• 한국정보처리학회논문지
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• 제6권12호
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• pp.3456-3468
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• 1999

기존에 제안된 대부분의 병렬 조인 알고리즘들은 데이타베이스가 여러 처리 노드에 분할되어 저장되는 데이타베이스 분할 시스템을 가정하였다. 데이타베이스 분할 시스템은 다수의 노드들을 연결할 수 있으며 지리적으로 분산된 환경도 지원할 수 있다는 장점을 갖지만, 데이타베이스 공유 시스템에 비해 부하 분산이나 시스템 가용성이 떨어진다는 단점을 갖는다. 본 논문에서는 데이타베이스 공유 시스템의 특성을 이용한 동적 부하분산 기법을 제안하고, 제안한 동적 부하분산 기법을 이용하여 기존의 해쉬 조인 알고리즘들을 데이타베이스 공유 시스템에 확장한다. 그리고, 다양한 시스템 구성 및 데이터베이스 부하 환경에서 모의 실험을 수행함으로써 데이타베이스 공유 시스템에서 동적 부하분산 기법의 효과 및 해쉬 알고리즘들의 성능 차이를 정량적으로 분석한다.

• 한국통신학회논문지
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• 제38A권9호
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• pp.782-791
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• 2013

이 논문에서는 적외선 센서를 가진 다수의 감시 로봇에서 획득한 정보를 융합하여 분산되어있는 표적의 위치 좌표를 추정하는 기법을 제안한다. 방위각(azimuth)과 표적을 대응시키는 방법으로 최대-우도(maximum likelihood), 깊이-우선(depth-first), 너비-우선(breadth-first) 트리 탐색(tree search) 기법을 각각 적용하며, 후보선정 및 가지치기(pruning)에 사용하는 정보는 표적의 방위각과 적외선 센서 화면에서 표적의 픽셀 수만을 활용한다. 방위각과 표적이 대응된 후에는 하나의 표적을 가리키는 방위각들에 최소 제곱 오차(least square error) 알고리듬을 적용하여 최적 교점을 구함으로써 표적의 위치 좌표를 추정한다. 제안한 세 가지 탐색 기법 및 위치 추정 기법의 좌표 추정성능, 복잡도, 오차 성능을 모의실험으로 제시하여 성능을 비교한다.