• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.27-33
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• 2006

To guarantee QoS (Quality of Service), routers should determine routing paths satisfying service requirements, based on link state information as well as network topology. Link status database (LSD) in routers should be efficiently managed to effectively reflect the current state of all links. However, there is a trade off between the exact reflection of the current link status and its update cost. For exactly reflecting the current link status, each router immediately notifies its neighbors that link state information is changed. This may degrade performance of the router due to the processing of link state update messages. On the other side, if the current link state information is not updated appropriately, a route setup request can be rejected because of the discrepancy between the current link state information and previously updated link state information in LSD. In this paper, we propose a traffic variation based link state update algorithm for adaptively controlling the generation of link state update messages and compare its performance with those of four existing algorithms by intensive simulations.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.275-279
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• 2008

본 논문은 제주 택시 텔레매틱스 사업의 운영 결과 축적된 히스토리 정보를 기반으로 택시들의 운행기록을 분석하여 승객들이 택시를 찾는 지점을 분석하는 기법을 제시하고 이를 바탕으로 시간별 지역별 링크별 승차 패턴을 분석한다. 이를 위하여 택시의 상태도 천이에서 승차지점을 추출하였으며 해당 데이터를 데이터베이스 테이블에 저장하였다. 이후 승차지점들을 그루핑하여 승차 패턴의 추이를 발견하고 이에 대한 분석을 수행하였다. 이 분석 데이터는 택시들을 지역별 시간대별로 승객이 많이 찾는 위치로 이동시키고 택시의 공차 운행율을 감소시키는 배차 방식을 개발하여 택시의 영업 수익 증대와 승객의 택시 대기시간 감소를 기할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.566-576
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• 2017

Key-value stores proved its superiority by being applied to various NoSQL databases such as Redis, Memcached. Lookup performance is important because key-value store applications performs more lookup than insert operations in most environments. However, in traditional applications, lookup may be slow because hash tables are constructed out of linked-list. Therefore, cuckoo hashing has been getting attention from the academia for constant lookup time, and bucketized cuckoo hashing (BCH) has been proposed since it can achieve high load factor. In this paper, we introduce Sorting Cuckoo which inserts data using insertion sort in BCH structure. Sorting Cuckoo determines the existence of a key with a relatively small memory access because data are sorted in each buckets. In particular, the higher memory load factor, the better lookup performance than BCH's. Experimental results show that Sorting Cuckoo has smaller memory access than BCH's as many as about 19 million (25%) in 10 million negative lookup operations (key is not in the table), about 4 million times (10%) in 10 million positive lookup operations (where it is) with load factor 95%.