Byte-hit Ratio Research Articles

DeCa360: Deadline-aware edge caching for two-tier 360° video streaming

Two-tier 360° video streaming provides a robust solution for handling inaccurate viewport prediction and varying network conditions. Within this paradigm, the client employs a dual-buffer mechanism consisting of a long buffer for panoramic basic-quality segments and a short buffer for high-quality tiles. However, designing an efficient edge caching strategy for two-tier 360° videos is non-trivial. First, as basic-quality segments and high-quality tiles possess different delivery deadlines as well as content popularity, ignoring these discrepancies may result in inefficient edge caching. Second, accurately predicting the popularity of 360° videos at a fine granularity of video segments and tiles remains a challenge. To address these issues, we present DeCa360, a deadline-aware edge caching framework for 360° videos. Specifically, we introduce a lightweight runtime cache partitioning approach to achieve a careful balance between improving the cache hit ratio and guaranteeing more on-time delivery of objects. Moreover, we design a content popularity prediction method for two-tier 360° videos that combines a learning-based prediction model with domain knowledge of video streaming, leading to improved prediction accuracy and efficient cache replacement. Extensive experimental evaluations demonstrate that DeCa360 outperforms all baseline algorithms in terms of byte-hit ratio and on-time delivery ratio, making it a promising approach for efficient edge caching of 360° videos.

INTELLIGENT COOPERATIVE WEB CACHING POLICIES FOR MEDIA OBJECTS BASED ON J48 DECISION TREE AND NAÏVE BAYES SUPERVISED MACHINE LEARNING ALGORITHMS IN STRUCTURED PEER-TO-PEER SYSTEMS

Web caching plays a key role in delivering web items to end users in World Wide Web (WWW).On the other hand, cache size is considered as a limitation of web caching.Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naive Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies. Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies.

Improved Performance by Combining Web Pre-Fetching Using Clustering with Web Caching Based on SVM Learning Method

Combining Web caching and Web pre-fetching results in improving the bandwidth utilization, reducing the load on the origin server and reducing the delay incurred in accessing information. Web pre-fetching is the process of fetching the Web objects from the origin server which has more likelihood of being used in future. The fetched contents are stored in the cache. Web caching is the process of storing the popular objects ”closer” to the user so that they can be retrieved faster. In the literature many interesting works have been carried out separately for Web caching and Web pre-fetching. In this work, clustering technique is used for pre-fetching and SVM-LRU technique forWeb caching and the performance is measured in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). With the help of real data, it is demonstrated that the above approach is superior to the method of combining clustering based prefetching technique with traditional LRU page replacement method for Web caching.

INTELLIGENT COOPERATIVE WEB CACHING POLICIES FOR MEDIA OBJECTS BASED ON J48 DECISION TREE AND NAÏVE BAYES SUPERVISED MACHINE LEARNING ALGORITHMS IN STRUCTURED PEER-TO-PEER SYSTEMS

Web caching plays a key role in delivering web items to end users in World Wide Web (WWW). On the other hand, cache size is considered as a limitation of web caching. Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies.

An adaptive caching algorithm suitable for time-varying user accesses in VOD systems

With the fast progresses of network technology, Video-On-Demand (VOD) service has found more and more applications. The transmission of multimedia files places heavy burdens on the Internet owing to their large sizes. To resolve this issue, caching servers are deployed at the edge of the Internet to meet most needs of local users by caching some popular videos. This paper provides an approach to choose the cached videos under the time-varying user behavior. Our approach estimates the average access intervals of a video with an Exponential Weighted Moving Average (EWMA) approach and furthermore predicts the video's future popularity based on its historical access intervals. The forgetting and predicting operations enable the algorithm to not only track the change of the time-varying user accesses, but also reduce the effects of the randomness of a single user access on the caching performance. In addition, we propose a new segmentation approach, which makes the storage granularity independent from the management granularity and can make a better use of the cache space. Simulation results show that our segmentation approach has a higher Byte-Hit Ratio than uniform segmentation and chunk segmentation, and our caching algorithm outperforms Least Recently Used (LRU), Least Frequently Used (LFU) and EWMA.

WINDOWS WEB PROXY CACHING SIMULATION: A TOOL FOR SIMULATING WEB PROXY CACHING UNDER WINDOWS OPERATING SYSTEMS

Web caching plays a key role in improving the performance of the web by reducing the latency of delivering web objects to the users. On the other hand, a simulation tool plays a key role in studying the behavior of any network such as studying the effects of web caching on the performance of the network. The aim of this work is to present a tool for simulating a web proxy caching for windows operating systems since there is no existing well-compatible simulation tool for windows operating systems that can simulate Hit Ratio (HR) and Byte Hit Ratio (BHR) for traditional caching policies. The proposed simulation tool is called Windows Web Proxy Caching Simulation (WWPCS). The results show the performance of traditional web caching policies for different cache’s sizes. Moreover, in order to show the efficiency of WWPCS, the results of running WWPCS are compared to the results of running a Unix-based tool.

Least cache value replacement algorithm

In order to improve the performance of cache for search applications,this paper proposed a new replacement algorithm — the Least Cache Value(LCV) algorithm.The algorithm took into account the object access frequency and size of the object.The set of objects in the cache which has the minimum contribution to Byte Hit Ratio(BHR) should have priority to be replaced.Moreover,the selection of optimal replacement set of objects was transformed into classical 0-1 knapsack problems and a rapid approximate solution and the data structure of algorithm were given.The experiment proves that the LCV algorithm has better performance in increasing BHR and reducing Average Latency Time(ALT) than algorithms of LRU(Least Recently Used),FIFO(First-In First-Out) and GD-Size(Greed Dual-Size).

Neuro-fuzzy system in partitioned client-side Web cache

This paper proposes a novel contribution in Web caching area, especially in Web cache replacement, so-called intelligent client-side Web caching scheme (ICWCS). This approach is developed by splitting the client-side cache into two caches: short-term cache that receives the Web objects from the Internet directly, and long-term cache that receives the Web objects from the short-term cache. The objects in short-term cache are removed by least recently used (LRU) algorithm as short-term cache is full. More significantly, when the long-term cache saturates, the neuro-fuzzy system is employed efficiently in managing contents of the long-term cache. The proposed solution is validated by implementing trace-driven simulation and the results are compared with least recently used (LRU) and least frequently used (LFU) algorithms; the most common policies of evaluating Web caching performance. The simulation results have revealed that the proposed approach improves the performance of Web caching in terms of hit ratio (HR), up to 14.8% and 17.9% over LRU and LFU. In terms of byte hit ratio (BHR), the Web caching performance is improved up to 2.57% and 26.25%, and for latency saving ratio (LSR), the performance is better with 8.3% and 18.9% over LRU and LFU, respectively.

Degraded Quality Service Policy with Bitrate based Segmentation in a Transcoding Proxy

To support various bandwidth requirements for many kinds of devices such as PC, notebook, PDA, cellular phone, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. Due to huge size of streaming media, we proposed the 3 kinds of segmentation - PT-2, uniform, bitrate-based segmentation. And to reduce the CPU cost of transcoding video, we proposed the DQS service policy. In this paper, we simulate the combined our previous two researches that are bitrate-based segmentation and DQS(Degraded Quality Service) policy. Experimental results show that the combined policy outperforms companion schemes in terms of the byte-hit ratios and delay saving ratios.

트랜스코딩 프록시에서 세그먼트 기반 캐쉬 교체 정책

최근 스트리밍 미디어는 인터넷 상의 많은 트래픽을 유발하고 있다. 기존의 웹을 위한 객체와 마찬가지로 스트리밍 객체 또한 프록시 시스템을 사용하게 되면 여러 이점이 있긴 하지만, 스트리밍 미디어를 캐슁 하는 방법은 기존의 웹을 위한 객체보다 매우 크고 높은 대역폭을 요구하기 때문에 고려해야 할 점이 많다. 또한 많은 종류의 단말들의 다양한 대역폭을 적절히 서비스 하기 위해서 프록시 기능과 트랜스코딩 기능을 함께 할 수 있는 트랜스코딩 프록시가 유용하다. 기존의 프록시는 객체가 프록시 서버에 저장되어 있거나, 그렇지 않은 경우로만 고려되었으나, 트랜스코딩 프록시에서는 같은 객체의 다양한 버전에 대해서 종합적인 효과를 고려하여 최적의 버전 집합을 저장 해야 한다. 또한 최근의 멀티미디어 캐슁 시스템들은 접근 빈도가 높은 앞부분을 캐슁하여 지연 시간을 줄이고 높은 효율을 얻을 수 있도록 하는 방법을 사용한다. 한편 많은 연구에서 멀티미디어 데이터의 효율적인 저장 관리를 위해서 객체를 세그먼트로 나누어 관리하는 방법을 사용하고 있다. 본 논문에서는 부분 캐슁을 사용하는 트랜스코딩 프록시에서 사용자 요청에 따른 후속 작업을 결정하기 위해 4개의 기본 이벤트를 이용하여 9개의 이벤트로 정의한다. 또한 트랜스코딩 프록시 시스템을 위하여 세그먼트 기반의 관리정책을 제안한다. 실험결과는 제안하는 방법이 사용자 지연시간, BHR와 트랜스코딩 데이터의 양이 적음을 보여준다. Streaming media has contributed to a significant amount of today's Internet Traffic. Like traditional web objects, rich media objects can benefit from proxy caching, but caching streaming media is more of challenging than caching simple web objects, because the streaming media have features such as huge size and high bandwidth. And to support various bandwidth requirements for the heterogeneous ubiquitous devices, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we define the 9-events of transcoding proxy using 4-atomic events. According to these events, the transcoding proxy can define the next actions. Then, we also propose the segment-based caching policy for the transcoding proxy system. The performance results show that the proposing policy have a low delayed start time, high byte-hit ratio and less transcoding data.

Efficient segment-based video transcoding proxy for mobile multimedia services

To support various bandwidth requirements for mobile multimedia services for future heterogeneous mobile environments, such as portable notebooks, personal digital assistants (PDAs), and 3G cellular phones, a transcoding video proxy is usually necessary to provide mobile clients with adapted video streams by not only transcoding videos to meet different needs on demand, but also caching them for later use. Traditional proxy technology is not applicable to a video proxy because it is less cost-effective to cache the complete videos to fit all kinds of clients in the proxy. Since transcoded video objects have inheritance dependency between different bit-rate versions, we can use this property to amortize the retransmission overhead from transcoding other objects cached in the proxy. In this paper, we propose the object relation graph (ORG) to manage the static relationships between video versions and an efficient replacement algorithm to dynamically manage video segments cached in the proxy. Specifically, we formulate a transcoding time constrained profit function to evaluate the profit from caching each version of an object. The profit function considers not only the sum of the costs of caching individual versions of an object, but also the transcoding relationship among these versions. In addition, an effective data structure, cached object relation tree (CORT), is designed to facilitate the management of multiple versions of different objects cached in the transcoding proxy. Experimental results show that the proposed algorithm outperforms companion schemes in terms of the byte-hit ratios and the startup latency.

Aggregate Profit-Based Caching Replacement Algorithms for Streaming Media Transcoding Proxy Systems

This work derives a generalized video object profit function from the extended weighted transcoding graph to calculate the individual cache profit of certain versions of a video object, and the aggregate profit from caching multiple versions of the same video object. This proposed function takes into account the popularity of certain versions of an object, the transcoding delay among versions, and the average duration of access of each version. Based on the profit function, cache-replacement algorithms are proposed to reduce the startup delay and network traffic by efficiently caching video objects with the most profits. Two kinds of simulations were conducted to evaluate the performance of the proposed algorithms. These simulations exploit partial viewing traces and complete viewing traces, separately. The results demonstrate that the proposed algorithms outperform the competing algorithms by 15%-39% in delay saving ratio and 5%-10% in byte-hit ratio

Fragmental Proxy Caching for Streaming Multimedia Objects

In this paper, a fragmental proxy-caching scheme that efficiently manages the streaming multimedia data in proxy cache is proposed to improve the quality of streaming multimedia services. The novel data-fragmentation method in this scheme not only provides finer granularity caching units to allow more effective cache replacement, but also offers a unique and natural way of handling the interactive VCR functions in the proxy-caching environment. Furthermore, a cache-replacement scheme, based on user request arrival rates for different multimedia objects and the playback rates of these objects, is proposed to address the drawbacks in existing cache-replacement schemes, most of which consider only the user access frequencies in their cache-replacement decisions. In this cache-replacement scheme, a sliding history window is employed to monitor the dynamic user request arrivals, and a tunable-victimization procedure is used to provide an excellent method of managing the cached multimedia data in accordance with different quality-of-service requirements of the streaming multimedia applications. Performance studies demonstrate that the fragmental proxy-caching scheme significantly outperforms other caching schemes, in terms of byte-hit ratio and the number of delayed starts and can be tuned to either maximize the byte-hit ratio or minimize the number of delayed starts

Frequency-based cache management policies for collaborative and non-collaborative topologies of segment based video caching proxies

This paper examines a novel cache management policy applied to non-collaborative and collaborative environments of more than one proxy server that serve homogeneous or even heterogeneous client requests for video streaming over the Internet. This cache management policy, which we call LRLFU because of a combination between an LRU and an LFU policy, is capable of capturing the changing popularities of the various videos by attaching a caching value to every video according to how recently and how frequently the video was requested, and decides to cache the most `valuable' videos. Our event-driven simulations have shown that LRLFU when applied to a simple non-collaborative topology of proxies and compared with previous work in this area (1) improve the byte-hit ratio (BHR), (2) significantly reduce the fraction of user requests with delayed starts and (3) require less CPU overhead. Furthermore, our simulation results have shown that the collaborative hierarchical tree topology of proxies that we examine achieves a much higher BHR when using the same overall cache capacity with the simple topology and in general provides better performance characteristics.

An SPN-Based Integrated Model for Web Prefetching and Caching

The World Wide Web has become the primary means for information dissemination. Due to the limited resources of the network bandwidth, users always suffer from long time waiting. Web prefetching and web caching are the primary approaches to reducing the user perceived access latency and improving the quality of services. In this paper, a Stochastic Petri Nets (SPN) based integrated web prefetching and caching model (IWPCM) is presented and the performance evaluation of IWPCM is made. The performance metrics, access latency, throughput, HR (hit ratio) and BHR (byte hit ratio) are analyzed and discussed. Simulations show that compared with caching only model (CM), IWPCM can further improve the throughput, HR and BHR efficiently and reduce the access latency. The performance evaluation based on the SPN model can provide a basis for implementation of web prefetching and caching and the combination of web prefetching and caching holds the promise of improving the QoS of web systems.

Replacing media caches in streaming proxy servers

This paper presents a cache replacement policy which has specifically been developed for the efficient media caching in streaming media cache servers. For efficient media caching, the proposed policy takes into account the periodic patterns of users' requests in addition to the parameters such as reference count, amount of media contents delivered to the clients, and reference time. These values are collected at run-time for each cached object. In order to adequately and promptly adopt to the changing characteristics of users preferences, the policy introduces, in particular, the concept of weighted-window for replacement with which higher priorities are given to more recently referenced media contents and consequently they are less likely to be replaced. We present and analyze the simulation results showing that the proposed policy has outperformed the conventional replacement policies such as LRU, LFU, and SEG in terms of hit ratio, byte-hit ratio, delayed start, and cache input.

Study of the Impact of Replacement Granularity and Associated Strategies on Video Caching

Partial caching of large media objects such as video files has been proposed recently as the caching of entire objects can easily exhaust the storage resources of a proxy server. In this paper the idea of segmenting video files into chunks and applying replacement decisions at the chunk level rather than on entire videos is examined. It is shown that a higher byte hit ratio (BHR) can be achieved by appropriately adjusting the replacement granularity. The price paid for the improved BHR performance is that the replacement algorithm takes a longer time to converge to the steady state BHR. For the segmentation of video into chunks two methods are presented. The Fixed Chunk Size segmentation scheme that is rather simple and reveals the basic trade-off between byte hit ratio (BHR) and responsiveness to changes of popularity; the Variable Chunk Size segmentation scheme that uses the request frequencies to dynamically adjust the size of the chunk and is shown to be capable of combining a small response time with high BHR. Moreover, a variation of the fixed chunk size segmentation scheme is presented, which is shown to improve its performance by switching between different chunk sizes. Video segmentation is also considered as a mechanism to provide for caching differentiation based on access costs. By employing access cost dependent chunk sizes an overall access cost reduction is demonstrated.

Segmentation of Multimedia Streams for Proxy Caching

Proxy caching of large multimedia objects on the edge of the Internet has become increasingly important for reducing network latency. For a large media object, such as a two-hour video, treating the whole media as a single object for caching is not appropriate. In this paper, we study three media segmentation approaches to proxy caching: fixed, pyramid, and skyscraper. Blocks of a media stream are grouped into various segments for cache management. The cache admission and replacement policies attach different caching priorities to individual segments, taking into account the access frequency of the media object and the segment distance from the start of the media. These caching policies give preferential treatment to the beginning segments. As such, most user requests can be quickly played back from the proxy servers without delay. Event-driven simulations are conducted to evaluate the segmentation approaches and compare them with whole media caching. The results show that: 1) compared with whole media caching, segmentation-based caching is more effective not only in increased byte-hit ratio but also in lowered fraction of requests that requires delayed start; 2) pyramid segmentation, where segment size increases exponentially, is the best segmentation approach; and 3) segmentation-based caching is especially advantageous when the cache size is limited, when the set of hot media objects changes over time, when the media file size is large, and when there are a large number of distinct media objects.

A Client-Side Cloud Cache Replacement Policy

To deliver data-centric cloud computing services heavily relies on data networks between cloud providers and consumer premises. The continuous and rapid growth of data hosted in external private clouds accelerates downstream network-bandwidth saturation and public cloud data-out overspends. The consumer-initiated replication of cloud data to consumer locality is a solution and known as clientside cloud caching. This paper presents the core mechanism of the cloud caching, called Cloud cache replacement policy. Simulations shown that 1) Cloud saved network bandwidth, data-out charge and data loading time; 2) even Clouds performance minima outperformed three well-known web cache replacement policies across all performance metrics for almost all test cases; 3) Cloud importantly attain optimal hit and byte-hit ratios without sacrificing one to the other.