• Proceedings of the IEEK Conference
• /
• 2002.06c
• /
• pp.153-156
• /
• 2002

As the use of world wide web is increasing, the number of connections to servers is increasing also. These interactions increase the load of networks and servers. therefore efficient caching strategies for web documents are needed to reduce server load and network traffics by migrating copies of server files closer to the clients that use those files. As One idea of caching policy, we propose a Weighted Disk Cache Replacement Policy(WDCRP) which analyses user's interaction to WWW and adds weight value to each web document. Especially the WDCRP takes account of the history data of cache log, the characteristics of Web requests and the importance of user interactive-actions.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.8
• /
• pp.27-36
• /
• 1997

In this paper, we propose a locating strategy using a cache based on the distributed call processing stucture. In our stategy, each originating call server, withc is responsible for call setup, has a cache to memorize the service ratio of call server which serves the called terminal.We present performance comparison of the proposed strategy with the existing strategy via simulation. We can reduce the cost for call setup because the originating call server can simpley establish a call without tracing the location of the called terminal. The proposed strategy also reduceds network loads caused by signaling at call setup time and lessens the frequency of queries for the database systems which can be a bottleneck when it serves many subscriber.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.658-667
• /
• 2017

The demand for large-scale storage systems has continued to grow due to the emergence of multimedia, social-network, and big-data services. In order to improve the response time and reduce the load of such large-scale storage systems, DRAM-based in-memory cache systems are becoming popular. However, the high cost of DRAM severely restricts their capacity. While the method of compressing cache entries has been proposed to deal with the capacity limitation issue, compression and decompression, which are technically difficult to parallelize, induce significant processing overhead and in turn retard the response time. A selective compression scheme is proposed in this paper for in-memory file system caches that rapidly estimates the compression ratio of incoming cache entries with their Shannon entropies and compresses cache entries with low compression ratio. In addition, a description is provided of the design and implementation of an in-kernel in-memory file system cache with the proposed selective compression scheme. The evaluation showed that the proposed scheme reduced the execution time of benchmarks by approximately 18% in comparison to the conventional non-compressing in-memory cache scheme. It also provided a cache hit ratio similar to the all-compressing counterpart and reduced 7.5% of the execution time by reducing the compression overhead. In addition, it was shown that the selective compression scheme can reduce the CPU time used for compression by 28% compared to the case of the all-compressing scheme.

• Journal of KIISE:Information Networking
• /
• v.32 no.3
• /
• pp.415-426
• /
• 2005

Wireless internet, which becomes a hot social issue, has limitations due to the following characteristics, as different from wired internet. It has low bandwidth, frequent disconnection, low computing power, and small screen in user terminal. Also, it has technical issues to Improve in terms of user mobility, network protocol, security, and etc. Wireless internet server should be scalable to handle a large scale traffic due to rapidly growing users. In this paper, wireless internet proxy server clusters are used for the wireless Internet because their caching, distillation, and clustering functions are helpful to overcome the above limitations and needs. TranSend was proposed as a clustering based wireless internet proxy server but it has disadvantages; 1) its scalability is difficult to achieve because there is no systematic way to do it and 2) its structure is complex because of the inefficient communication structure among modules. In our former research, we proposed the All-in-one structure which can be scalable in a systematic way but it also has disadvantages; 1) data sharing among cache servers is not allowed and 2) its communication structure among modules is complex. In this paper, we proposed its improved scheme which has an efficient communication structure among modules and allows data to be shared among cache servers. We performed experiments using 16 PCs and experimental results show 54.86$\%$ and 4.70$\%$ performance improvement of the proposed system compared to TranSend and All-in-one system respectively Due to data sharing amount cache servers, the proposed scheme has an advantage of keeping a fixed size of the total cache memory regardless of cache server numbers. On the contrary, in All-in-one, the total cache memory size increases proportional to the number of cache servers since each cache server should keep all cache data, respectively.

• Journal of Advanced Navigation Technology
• /
• v.20 no.1
• /
• pp.79-85
• /
• 2016

Network traffic is increased rapidly, due to mobile and social network, such as smartphones and facebook, in recent web environment. In this paper, we improved web response time of existing system using direct buffer of NIO and DMA. This solved the disadvantage of JAVA, such as CPU performance reduction due to the blocking of I/O, garbage collection of buffer. Key values circulated many data due to priority change put on a hash map operated easily and apply a priority modification algorithm. Large response data is separated and stored at a fast direct buffer and improved performance. This paper showed that the proposed method using NIO was much improved performance, in many test situations of cache hit and cache miss.

• Journal of Digital Convergence
• /
• v.15 no.2
• /
• pp.327-334
• /
• 2017

For enhancing network efficiency, various applications/services like CDN and P2P try to utilize content which have previously been cached somewhere. Content-centric networking (CCN) also utilizes data caching functionality. However, dislike CDN/P2P, CCN implements such a function on network nodes. Then, any intermediated nodes can directly respond to request messages for cached data. Hence, it is essential which content is cached as well as which nodes cache transmitted content. Basically, CCN propose for every nodes on the path from the content publisher of transmitted object to a requester to cache the object. However, such an approach is inefficient considering the utilization of cached objects as well as the storage overhead of each node. Hence, various caching mechanisms are proposed to enhance the storage efficiency of a node. In this paper, we analyze the performance of such mechanisms and compare the characteristics of such mechanisms. Also, we analyze content utilization patterns and apply such pattern to caching mechanisms to analyze the practicalism of the caching mechanisms.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.687-692
• /
• 2004

In this paper, we proposed an efficient cache hoarding method in mobile computing environments using collaborative filtering. This method is used for solving the difficult problem of mobile computing, which is the vacuum of information service depending on low bandwidth, long delay, and frequent network disconnection. Many previous researches have been studied a cache hoarding approach for solving these problems of mobile client. But, the research of history information of mobile client did not support all informative requests for mobile clients. In our research, collaborative filtering model using history information and location data of mobile client is proposed. This proposed model supports an efficient service of necessary items for client's requirement. For the performance evaluation of proposed model, we make an experiment of simulation data using SAS enterprise miner. According to objective evaluation using cache hit ratio, we show that our model has a good result.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1084-1089
• /
• 2004

This paper describes the improvement of web cache server by scoping in replacement algorithm of data which are collected from the clients. We have found that each replacement algorithm is suitable for each type of data in the web pages. Therefore, we introduce the mechanism to select the replacement algorithm depending on the size of data called the Replacement Algorithm Selection Mechanism (RASM). RASM allows the web cache server to have the suitable replacement algorithm for each type of data. As the result, the byte hit ratio of web cache server can be increased and the congestion in the network can be alleviated.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2151-2159
• /
• 2015

Unlike an existing IP routing methods, the Content Centric Network(CCN) is new networking paradigm to find the contents by content name. The CCN can effectively process the content requested repeatedly by the user because of the cache which can be storing a content. This paper proposes a popularity based cache replacement scheme. The proposed scheme improves the hit rate better than a existing scheme. Accordingly reducing the load of server and Round Trip Time(RTT).

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.12
• /
• pp.433-442
• /
• 2014

In this paper, we introduce the client side cache of distributed file system for enhancing read performance by eliminating the network latency and decreasing the back-end storage burden. This performance enhancement can expand the fields of distributed file system to not only cloud storage service but also high performance storage service. This paper shows that the distributed file system with client side SSD cache can satisfy the requirements of VDI(Virtual Desktop Infrastructure) storage. The experimental results show that full-clone is more than 2 times faster and boot time is more than 3 times faster than NFS.