• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.31-36
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• 2022

Interval caching is one of the representative caching strategies used in multimedia streaming systems. However, there has been no theoretical analysis on interval caching. In this paper, we present an optimality proof of the interval caching policy. Specifically, we propose a caching performance model for multimedia streaming systems and show the optimality of the interval caching policy based on this model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.9-13
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• 2023

Multimedia streaming data is very large in size and accessed sequentially, making the LRU(Least Recently Used) algorithm widely used to improve I/O performance in traditional caching environments ineffective. Experimental analysis of this has shown the superiority of interval-based caching over LRU, but the theoretical basis has not been proven. In this paper, we design a cache performance model to analyze the optimality of caching for multimedia streaming environments and design a theoretically optimal caching algorithm based on interval caching. Then, we show that the algorithm we design is an optimal algorithm that minimizes cache misses of streaming data based on the proposed model.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.4
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• pp.420-430
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• 2000

Several caching schemes for realtime multimedia systems have been proposed, but they focus only on increasing the hit ratio without providing any means to utilize the saved disk bandwidth due to cache hits. One of the most important metrics in multimedia systems is the number of clients that the systems can service simultaneously guaranteeing Quality of Service(QoS). Preemptive but Safe Interval Caching(PSIC) was proposed as a caching scheme which makes it possible to provide deterministic QoS.. However, it has no ability to adapt to the change of system environments since it has no mechanism to change the cache size. In this paper, we present a new caching scheme, Dynamic Interval Caching(DIC), which maximizes the performance, regardless of the change of system environments, providing hiccup-free service, by managing memory buffers dynamically. And it is demonstrated that DIC allocates buffer cache optimally, by comparing with PSIC through trace-driven simulations.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3642-3651
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• 1999

In this paper, we propose a new caching scheme for continuous media data where the buffer allocation unit is divided into two modes : interval and object. All of objects' access patterns are monitored and based on the results of monitoring, a request for an object is decided to cache its data with either interval mode or object mode. The results of our simulation show that our proposed caching scheme is better than the existing caching algorithms such as interval caching where the access patterns of the objects are changed with time.

• Journal of Computing Science and Engineering
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• v.9 no.3
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• pp.134-141
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• 2015

In on-demand multimedia streaming systems, streaming techniques are usually combined with proxy caching to obtain better performance. The patch streaming technique has no start-up latency inherent to it, but requires extra bandwidth to deliver the media data in patch streams. This paper proposes a proxy caching technique which aims at reducing the bandwidth cost of the patch streaming technique. The proposed approach determines media prefixes with high patching cost and caches the appropriate media prefix at the proxy/local server. Herein the scheme is evaluated using a synthetically generated media access workload and its performance is compared with that of the popularity and prefix-aware interval caching scheme (the prefix part) and with that of patch streaming with no caching. The bandwidth saving, hit ratio and concurrent number of clients are used to compare the performance, and the proposed scheme is found to perform better for different caching capacities of the proxy server.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.4
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• pp.138-144
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• 2007

With recent proliferation of video-on-demand services, caching in a multimedia streaming server is becoming increasingly important. Previous studies have shown that request interval based caching and its extension for considering different video popularity performs well in various streaming environments. In this paper, we show that block level refinement of this existing scheme can further improve the performance of streaming servers. Trace driven simulations with real world VOD traces have shown that the proposed scheme improves the cache hit rate and the startup latency.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1083-1092
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• 2003

This paper propose method to minimize service delay time based in popularity when service video stream in internet Result that measure performance of algorithm that propose considering correlation of cache space all of access frequency and each servers showed performance elevation of degree of triple than elevation of cache practical use rate 15% and interval caching about service laytency than agent caching scheme.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.709-718
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• 2002

Cluster based VOD systems require elaborate load balancing and buffer management techniques in order to ensure real-time display for multiuser concurrently. In this paper, we propose a new load balancing technique based on the dynamic buffer partitioning in cluster based VOD servers. The proposed technique evenly distribute the user requests into each service node according to its available buffer capacity and disk access rate. In each node, the dynamic buffer partitioning technique dynamically partitions the buffer to minimize the average waiting time for the requests that access the same continuous media. The simulation results show that our proposed technique decreases the average waiting time by evenly distributing the user requests compared with the exiting techniques and then increases the throughput in each node. Particularly under the overloaded condition in the cluster server, the simulation probes that the performance of the proposed technique is better two times than the Generalized Interval Caching based technique.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.775-782
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• 2005

In this paper, we propose multicast technique in order to reduce the required network bandwidth by n times, by merging the adjacent multicasts depending on the number of HENs (Head-End-Nodes) n that request the same video. Allowing new clients to immediately join an existing multicast through patching improves the efficiency of the multicast and offers services without any initial latency. A client might have to download data through two channels simultaneously, one for multicast and the other for patching. The more the frequency of requesting the video is, the higher the probability of caching it among HENs increases. Therefore, the requests for the cached video data can be served by HENs. Multicast from server is generated when the playback time exceeds the amount of cached video data. Since the interval of multicast can be dynamically expanded according to the popularity of videos, it can be reduced the server's workload and the network bandwidth. We perform simulations to compare its performance with that of conventional multicast. From simulation results, we confirm that the Proposed multicast technique offers substantially better performance.