• Title/Summary/Keyword: routing summary algorithm

Search Result 4, Processing Time 0.036 seconds

Methodology for the efficiency of routing summary algorithms in discontiguous networks (Discontiguous Network에서 라우팅 축약 알고리즘의 효율화에 대한 방법론)

  • Hwang, Seong-kyu
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.23 no.12
    • /
    • pp.1720-1725
    • /
    • 2019
  • In this paper, we consider the efficiency of the scheme for for routing summary algorithms in discontiguous networks. Router than updating and transmitting the entire subnet information in the routing protocol, only the shortened update information is sent and the routing table is shortened to make the router resources more efficient and improve network stability and performance. However, if a discontiguous network is formed in the network design process, a problem arises due to the network contraction function and does not bring about the result of fundamental router efficiency. Using different major networks subnets one major network, causing problems in communication and routing information exchange if the configuration is incorrect. The algorithm proposed in this paper removes only the auto-summary algorithm from the existing algorithm, which increases the complexity and stability of the routing table and reduces the CPU utilization of network equipment from 16.5% to 6.5% Confirmed.

Forecasting Air Freight Demand in Air forces by Time Series Analysis and Optimizing Air Routing Problem with One Depot (군 항공화물수요 시계열 추정과 수송기 최적화 노선배정)

  • Jung, Byung-Ho;Kim, Ik-Ki
    • Journal of Korean Society of Transportation
    • /
    • v.22 no.5
    • /
    • pp.89-97
    • /
    • 2004
  • The Korea Air Force(KAF) has operated freight flights based on the prefixed time and route schedule, which is adjusted once in a month. The major purpose of the operation of freight flights in the KAF is to distribute necessary supplies from the home air base to other air bases. The secondary purpose is to train the young pilots to get more experiences in navigation. Each freight flight starts from and returned to the home air base everyday except holidays, while it visits several other air bases to accomplish its missions. The study aims to forecast freight demand at each base by using time series analysis, and then it tried to optimize the cost of operating flights by solving vehicle routing problem. For more specifically, first, several constraints in operating cargos were defined by reviewing the Korea Air Force manuals and regulation. With such constraints, an integer programming problem was formulated for this specific routing problem allowing several visits in a tour with limitation of maximum number of visits. Then, an algorithm to solve the routing problem was developed. Second, the time series analysis method was applied to find out the freight demand at each air base from the mother air base in the next month. With the forecasted demands and the developed solution algorithm, the oprimum routes are calculated for each flight. Finally, the study compared the solved routing system by the developed algorithm with the existing routing system of the Korea Air Force. Through this comparison, the study proved that the proposed method can provide more (economically) efficient routing system than the existing system in terms of computing and monetary cost. In summary, the study suggested objective criteria for air routing plan in the KAF. It also developed the methods which could forecast properly the freight demands at each bases by using time series analysis and which could find the optimum routing which minimizes number of cargo needed. Finally, the study showed the economical savings with the optimized routing system by using real case example.

Comparison of Three Evolutionary Algorithms: GA, PSO, and DE

  • Kachitvichyanukul, Voratas
    • Industrial Engineering and Management Systems
    • /
    • v.11 no.3
    • /
    • pp.215-223
    • /
    • 2012
  • This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The general observations on the similarities and differences among the three algorithms based on computational steps are discussed, contrasting the basic performances of algorithms. Summary of relevant literatures is given on job shop, flexible job shop, vehicle routing, location-allocation, and multimode resource constrained project scheduling problems.

Research on a Mobile-aware Service Model in the Internet of Things

  • An, Jian;Gui, Xiao-Lin;Yang, Jian-Wei;Zhang, Wen-Dong;Jiang, Jin-Hua
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.7 no.5
    • /
    • pp.1146-1165
    • /
    • 2013
  • Collaborative awareness between persons with various smart multimedia devices is a new trend in the Internet of Things (IoT). Because of the mobility, randomness, and complexity of persons, it is difficult to achieve complete data awareness and data transmission in IoT. Therefore, research must be conducted on mobile-aware service models. In this work, we first discuss and quantify the social relationships of mobile nodes from multiple perspectives based on a summary of social characteristics. We then define various decision factors (DFs). Next, we construct a directed and weighted community by analyzing the activity patterns of mobile nodes. Finally, a mobile-aware service routing algorithm (MSRA) is proposed to determine appropriate service nodes through a trusted chain and optimal path tree. The simulation results indicate that the model has superior dynamic adaptability and service discovery efficiency compared to the existing models. The mobile-aware service model could be used to improve date acquisition techniques and the quality of mobile-aware service in the IoT.