• Title/Summary/Keyword: Static Routing

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Adaptive Mobile Sink Path Based Energy Efficient Routing Protocol for Wireless Sensor Network (무선 센서 네트워크에서 에너지 효율을 고려한 모바일 sink의 적응적 경로설정 방법)

  • Kim, Hyun-Duk;Yoon, Yeo-Woong;Choi, Won-Ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.12A
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    • pp.994-1005
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    • 2011
  • In this paper, we propose a novel approach to optimize the movement of mobile sink node, called AMSP(Adaptive Mobile Sink Path) for mobile sensor network environments. Currently available studies usually suffer from unnecessary data transmission resulting from random way point approach. To address the problem, we propose a method which uses the Hilbert curve to create a path. The proposed method guarantees shorten transmission distance between the sink node and each sensor node by assigning orders of the curve according to sensor node density. Furthermore, The schedule of the sink node is informed to all of the sensing nodes so that the Duty Cycle helps the network be more energy efficient. In our experiments, the proposed method outperforms the existing works such as TTDD and CBPER by up to 80% in energy consumption.

Efficient Route Determination Technique in LBS System

  • Kim, Sung-Soo;Kim, Kwang-Soo;Kim, Jae-Chul;Lee, Jong-Hun
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.843-845
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    • 2003
  • Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is the route determination service, where various kinds of shortest path problems need to be solved in location-based service. Our research aim is to propose a route technique in real-time locationbased service (LBS) environments according to user’s route preferences such as shortest, fastest, easiest and so on. Turn costs modeling and computation are important procedures in route planning. There are major two kinds of cost parameters in route planning. One is static cost parameter which can be pre-computed such as distance and number of traffic-lane. The other is dynamic cost parameter which can be computed in run-time such as number of turns and risk of congestion. In this paper, we propose a new cost modeling method for turn costs which are traditionally attached to edges in a graph. Our proposed route determination technique also has an advantage that can provide service interoperability by implementing XML web service for the OpenLS route determination service specification. In addition to, describing the details of our shortest path algorithms, we present a location-based service system by using proposed routing algorithms.

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Estimation of ship operational efficiency from AIS data using big data technology

  • Kim, Seong-Hoon;Roh, Myung-Il;Oh, Min-Jae;Park, Sung-Woo;Kim, In-Il
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.440-454
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    • 2020
  • To prevent pollution from ships, the Energy Efficiency Design Index (EEDI) is a mandatory guideline for all new ships. The Ship Energy Efficiency Management Plan (SEEMP) has also been applied by MARPOL to all existing ships. SEEMP provides the Energy Efficiency Operational Indicator (EEOI) for monitoring the operational efficiency of a ship. By monitoring the EEOI, the shipowner or operator can establish strategic plans, such as routing, hull cleaning, decommissioning, new building, etc. The key parameter in calculating EEOI is Fuel Oil Consumption (FOC). It can be measured on board while a ship is operating. This means that only the shipowner or operator can calculate the EEOI of their own ships. If the EEOI can be calculated without the actual FOC, however, then the other stakeholders, such as the shipbuilding company and Class, or others who don't have the measured FOC, can check how efficiently their ships are operating compared to other ships. In this study, we propose a method to estimate the EEOI without requiring the actual FOC. The Automatic Identification System (AIS) data, ship static data, and environment data that can be publicly obtained are used to calculate the EEOI. Since the public data are of large capacity, big data technologies, specifically Hadoop and Spark, are used. We verify the proposed method using actual data, and the result shows that the proposed method can estimate EEOI from public data without actual FOC.

A Study on Hierarchical Overlay Multicast Architecture in Mobile Ad Hoc Networks (Mobile Ad Hoc 네트워크를 위한 계층적 오버레이 멀티캐스트 구조 연구)

  • Kim, Kap-Dong;Park, Jun-Hee;Lee, Kwang-Il;Kim, Hag-Young;Kim, Sang-Ha
    • The KIPS Transactions:PartC
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    • v.13C no.5 s.108
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    • pp.627-634
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    • 2006
  • Overlay network eliminates the need to change the application-layer tree when the underlying network changes and enables the overlay network to survive in environments where nonmember nodes do not support multicast functionality. An overlay protocol monitors group dynamics, while underlying unicast protocols track network dynamics, resulting in more stable protocol operation and low control overhead even in a highly dynamic environment. But, if overlay multicast protocols does not know the location information of node, this makes it very difficult to build an efficient multicasting tree. So, we propose a Hierarchical Overlay Multicast Architecture (HOMA) with the location information. Because proposed architecture makes static region-based dynamic group by multicast members, it is 2-tired overlay multicasts of application layer that higher layer forms overlay multicast network between members that represent group, and support multicast between multicast members belonging to region at lower layer. This use GPS, take advantage of geographical region, and realizes a region-sensitive higher layer overlay multicast tree which is impervious to the movements of nodes. The simulation results show that our approach solves the efficiency problem effectively.