• Title/Summary/Keyword: Routing Problem

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An Application of MapReduce Technique over Peer-to-Peer Network (P2P 네트워크상에서 MapReduce 기법 활용)

  • Ren, Jian-Ji;Lee, Jae-Kee
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.8
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    • pp.586-590
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    • 2009
  • The objective of this paper describes the design of MapReduce over Peer-to-Peer network for dynamic environments applications. MapReduce is a software framework used for Cloud Computing which processing large data sets in a highly-parallel way. Based on the Peer-to-Peer network character which node failures will happen anytime, we focus on using a DHT routing protocol which named Pastry to handle the problem of node failures. Our results are very promising and indicate that the framework could have a wide application in P2P network systems while maintaining good computational efficiency and scalability. We believe that, P2P networks and parallel computing emerge as very hot research and development topics in industry and academia for many years to come.

A Combination Method of Trajectory Data using Correlated Direction of Collected GPS Data (수집한 GPS데이터의 상호방향성을 이용한 경로데이터 조합방법)

  • Koo, Kwang Min;Park, Heemin
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1636-1645
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    • 2016
  • In navigation systems that use collected trajectory for routing, the number and diversity of trajectory data are crucial despite the infeasible limitation which is that all routes should be collected in person. This paper suggests an algorithm combining trajectories only by collected GPS data and generating new routes for solving this problem. Using distance between two trajectories, the algorithm estimates road intersection, in which it also predicts the correlated direction of them with geographical coordinates and makes a decision to combine them by the correlated direction. With combined and generated trajectory data, this combination way allows trajectory-based navigation to guide more and better routes. In our study, this solution has been introduced. However, the ways in which correlated direction is decided and post-process works have been revised to use the sequential pattern of triangles' area GPS information between two trajectories makes in road intersection and intersection among sets comprised of GPS points. This, as a result, reduces unnecessary combinations resulting redundant outputs and enhances the accuracy of estimating correlated direction than before.

An Energy Efficient Clustering Algorithm in Mobile Adhoc Network Using Ticket Id Based Clustering Manager

  • Venkatasubramanian, S.;Suhasini, A.;Vennila, C.
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.341-349
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    • 2021
  • Many emerging mobile ad-hoc network application communications are group-oriented. Multicast supports group-oriented applications efficiently, particularly in a mobile environment that has a limited bandwidth and limited power. Energy effectiveness along with safety are 2 key problem in MANET design. Within this paper, MANET is presented with a stable, energy-efficient clustering technique. In this proposed work advanced clustering in the networks with ticket ID cluster manager (TID-CMGR) has formed in MANET. The proposed routing scheme makes secure networking the shortest route possible. In this article, we propose a Cluster manager approach based on TICKET-ID to address energy consumption issues and reduce CH workload. TID-CMGR includes two mechanism including ticket ID controller, ticketing pool, route planning and other components. The CA (cluster agent) shall control and supervise the functions of nodes and inform to TID-CMGR. The CH conducts and transfers packets to the network nodes. As the CH energy level is depleted, CA elects the corresponding node with elevated energy values, and all new and old operations are simultaneously stored by CA at this time. A simulation trial for 20 to 100 nodes was performed to show the proposed scheme performance. The suggested approach is used to do experimental work using the NS- simulator. TIDCMGR is compared with TID BRM and PSO to calculate the utility of the work proposed. The assessment shows that the proposed TICKET-ID scheme achieves 90 percent more than other current systems.

Analysis of Cluster-based Truck-Drone Delivery Routing Models (군집 기반 트럭-드론 배송경로 모형의 효과분석)

  • Chang, Yong Sik
    • Journal of Information Technology Applications and Management
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    • v.26 no.1
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    • pp.53-64
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    • 2019
  • The purpose of this study is to find out the fast delivery route that several drones return a truck again after departing from it for delivery locations at each cluster while the truck goes through the cluster composed of several delivery locations. The main issue is to reduce the total delivery time composed of the delivery time by relatively slow trucks via clusters and the sum of maximum delivery times by relatively fast drones in each cluster. To solve this problem, we use a three-step heuristic approach. First, we cluster the nearby delivery locations with minimal number of clusters satisfying a constraint of drone flight distance to set delivery paths for drones in each cluster. Second, we set an optimal delivery route for a truck through centers of the clusters using the TSP model. Finally, we find out the moved centers of clusters while maintaining the delivery paths for the truck and drones and satisfying the constraint of drone flight. distance in the two-dimensional region to reduce the total delivery time. In order to analyze the effect of this study model according to the change of the number of delivery locations, we developed a R-based simulation prototype and compared the relative efficiency, and performed paired t-test between TSP model and the cluster-based models. This study showed its excellence through this experimentation.

iPEC: Design and Implementation of intelligent Personal Emergency Call System (iPEC: 지능형 개인 응급 호출 시스템 설계 및 구현)

  • Jung, Kyung Kwon;Kim, Joo Woong;Son, Dong Seol;Eom, Ki Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.1049-1052
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    • 2009
  • This paper develop a intelligent personal emergency call system using the wireless sensor network to resolve that a portable problem of established emergency call system. The proposed system is composed of a transmitter nodes for individuals, routing nodes for multihop communications, and a server part. The transmitters for patients are monitored for both low battery and operational status. The transmitters provide location of the person activating an emergency call using RSSI. The efficacy of the proposed system is verified by means of experiments. Experimental results are presented that show the effectiveness.

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Study of Integrated Production-Distribution Planning Using Simulation and Genetic Algorithm in Supply Chain Network (공급사슬네트워크에서 시뮬레이션과 유전알고리즘을 이용한 통합생산분배계획에 대한 연구)

  • Lim, Seok-Jin
    • Journal of the Korea Safety Management & Science
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    • v.22 no.4
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    • pp.65-74
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    • 2020
  • Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

Opportunity Coefficient for Cluster-Head Selection in LEACH Protocol

  • Soh, Ben;AlZain, Mohammed;Lozano-Claros, Diego;Adhikari, Basanta
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.6-11
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    • 2021
  • Routing protocols play a pivotal role in the energy management and lifespan of any Wireless Sensor Network. Lower network lifetime has been one of the biggest concerns in LEACH protocol due to dead nodes. The LEACH protocol suffers from uneven energy distribution problem due to random selection of a cluster head. The cluster head has much greater responsibility compared to other non- cluster head nodes and consumes greater energy for its roles. This results in early dead nodes due to energy lost for the role of cluster- head. This study proposes an approach to balance the energy consumption of the LEACH protocol by using a semi-deterministic opportunity coefficient to select the cluster head. This is calculated in each node with the battery energy level and node ID. Ultimately, based on the opportunity cost, cluster head will be selected and broadcasted for which other nodes with higher opportunity cost will agree. It minimizes the chances of nodes with lower battery level being elected as cluster head. Our simulation experiments demonstrate that cluster heads chosen using our proposed algorithm perform better than those using the legacy LEACH protocol.

Attention Capsule Network for Aspect-Level Sentiment Classification

  • Deng, Yu;Lei, Hang;Li, Xiaoyu;Lin, Yiou;Cheng, Wangchi;Yang, Shan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1275-1292
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    • 2021
  • As a fine-grained classification problem, aspect-level sentiment classification predicts the sentiment polarity for different aspects in context. To address this issue, researchers have widely used attention mechanisms to abstract the relationship between context and aspects. Still, it is difficult to effectively obtain a more profound semantic representation, and the strong correlation between local context features and the aspect-based sentiment is rarely considered. In this paper, a hybrid attention capsule network for aspect-level sentiment classification (ABASCap) was proposed. In this model, the multi-head self-attention was improved, and a context mask mechanism based on adjustable context window was proposed, so as to effectively obtain the internal association between aspects and context. Moreover, the dynamic routing algorithm and activation function in capsule network were optimized to meet the task requirements. Finally, sufficient experiments were conducted on three benchmark datasets in different domains. Compared with other baseline models, ABASCap achieved better classification results, and outperformed the state-of-the-art methods in this task after incorporating pre-training BERT.

An Energy Efficient Multi-hop Cluster-Head Election Strategy for Wireless Sensor Networks

  • Zhao, Liquan;Guo, Shuaichao
    • Journal of Information Processing Systems
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    • v.17 no.1
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    • pp.63-74
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    • 2021
  • According to the double-phase cluster-head election method (DCE), the final cluster heads (CHs) sometimes are located at the edge of cluster. They have a long distance from the base station (BS). Sensor data is directly transmitted to BS by CHs. This makes some nodes consume much energy for transmitting data and die earlier. To address this problem, energy efficient multi-hop cluster-head election strategy (EEMCE) is proposed in this paper. To avoid taking these nodes far from BS as CH, this strategy first introduces the distance from the sensor nodes to the BS into the tentative CH election. Subsequently, in the same cluster, the energy of tentative CH is compared with those of other nodes, and then the node that has more energy than the tentative CH and being nearest the tentative CH are taken as the final CH. Lastly, if the CH is located at the periphery of the network, the multi-hop method will be employed to reduce the energy that is consumed by CHs. The simulation results suggest that the proposed method exhibits higher energy efficiency, longer stability period and better scalability than other protocols.

Study on Delivery of Military Drones and Transport UGVs with Time Constraints Using Hybrid Genetic Algorithms (하이브리드 유전 알고리즘을 이용한 시간제약이 있는 군수 드론 및 수송 UGV 혼합배송 문제 연구)

  • Lee, Jeonghun;Kim, Suhwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.4
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    • pp.425-433
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    • 2022
  • This paper studies the method of delivering munitions using both drones and UGVs that are developing along with the 4th Industrial Revolution. While drones are more mobile than UGVs, their loading capacity is small, and UGVs have relatively less mobility than drones, but their loading capacity is better. Therefore, by simultaneously operating these two delivery means, each other's shortcomings may be compensated. In addition, on actual battlefields, time constraints are an important factor in delivering munitions. Therefore, assuming an actual battlefield environment with a time limit, we establish delivery routes that minimize delivery time by operating both drones and UGVs with different capacities and speeds. If the delivery is not completed within the time limit, penalties are imposed. We devised the hybrid genetic algorithm to find solutions to the proposed model, and as results of the experiment, we showed the algorithm we presented solved the actual size problems in a short time.