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Journal articles on the topic 'Caching'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Prasad, M., P. R. Sudha Rani, Raja Rao PBV, et al. "Blockchain-Enabled On-Path Caching for Efficient and Reliable Content Delivery in Information-Centric Networks." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 358–63. http://dx.doi.org/10.17762/ijritcc.v11i9.8397.

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As the demand for online content continues to grow, traditional Content Distribution Networks (CDNs) are facing significant challenges in terms of scalability and performance. Information-Centric Networking (ICN) is a promising new approach to content delivery that aims to address these issues by placing content at the center of the network architecture. One of the key features of ICNs is on-path caching, which allows content to be cached at intermediate routers along the path from the source to the destination. On-path caching in ICNs still faces some challenges, such as the scalability of th

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Shuai, Ziqi, Zhenbang Chen, Kelin Ma, et al. "Partial Solution Based Constraint Solving Cache in Symbolic Execution." Proceedings of the ACM on Software Engineering 1, FSE (2024): 2493–514. http://dx.doi.org/10.1145/3660817.

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Constraint solving is one of the main challenges for symbolic execution. Caching is an effective mechanism to reduce the number of the solver invocations in symbolic execution and is adopted by many mainstream symbolic execution engines. However, caching can not perform well on all programs. How to improve caching’s effectiveness is challenging in general. In this work, we propose a partial solution-based caching method for improving caching’s effectiveness. Our key idea is to utilize the partial solutions inside the constraint solving to generate more cache entries. A partial solution may sat

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Zhou, Mo, Bo Ji, Kun Peng Han, and Hong Sheng Xi. "A Cooperative Hybrid Caching Strategy for P2P Mobile Network." Applied Mechanics and Materials 347-350 (August 2013): 1992–96. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1992.

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Recently mobile network technologies develop quickly. To meet the increasing demand of wireless users, many multimedia proxies have been deployed over wireless networks. The caching nodes constitute a wireless caching system with an architecture of P2P and provide better service to mobile users. In this paper, we formulate the caching system to optimize the consumption of network bandwidth and guarantee the response time of mobile users. Two strategies: single greedy caching strategy and cooperative hybrid caching strategy are proposed to achieve this goal. Single greedy caching aims to reduce

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M, Kannan, and Aboorva S. "ENHANCEMENT OF FOG CACHING USING NATURE INSPIRATION OPTIMIZATION TECHNIQUE BASED ON CLOUD COMPUTING." International Journal of Advanced Research 13, no. 05 (2025): 388–94. https://doi.org/10.21474/ijar01/20914.

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An new concept called fog computing brings cloud computing closer to the network edge, allowing for data processing, storage, and application execution near end users. Nonetheless, effective fog node managementâ€”especially with regard to cachingâ€”remains a significant obstacle. Caching techniques are essential for boosting fog computing's overall performance since they lower latency, use less bandwidth, and make apps more responsive.

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Dinh, Ngocthanh, and Younghan Kim. "An Energy Reward-Based Caching Mechanism for Information-Centric Internet of Things." Sensors 22, no. 3 (2022): 743. http://dx.doi.org/10.3390/s22030743.

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Existing information-centric networking (ICN) designs for Internet of Things (IoT) mostly make caching decisions based on probability or content popularity. From the energy-efficient perspective, those strategies may not always be energy efficient in resource-constrained IoT because without considering the energy reward of caching decisions, inappropriate routers and content objects may be selected for caching, which may lead to negative energy rewards. In this paper, we analyze the energy consumption of content caching and content retrieval in resource-constrained IoT and calculate caching en

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Wang, Yali, and Jiachao Chen. "Collaborative Caching in Edge Computing via Federated Learning and Deep Reinforcement Learning." Wireless Communications and Mobile Computing 2022 (December 22, 2022): 1–15. http://dx.doi.org/10.1155/2022/7212984.

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By deploying resources in the vicinity of users, edge caching can substantially reduce the latency for users to retrieve content and relieve the pressure on the backbone network. Due to the capacity limitation of caching and the dynamic nature of user requests, how to allocate caching resources reasonably must be considered. Some edge caching studies improve network performance by predicting content popularity and actively caching the most popular content, thereby ignoring the privacy and security issues caused by the need to collect user information at the central unit. To this end, a collabo

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Li, Feng, Kwok-Yan Lam, Li Wang, Zhenyu Na, Xin Liu, and Qing Pan. "Caching Efficiency Enhancement at Wireless Edges with Concerns on User’s Quality of Experience." Wireless Communications and Mobile Computing 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/1680641.

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Content caching is a promising approach to enhancing bandwidth utilization and minimizing delivery delay for new-generation Internet applications. The design of content caching is based on the principles that popular contents are cached at appropriate network edges in order to reduce transmission delay and avoid backhaul bottleneck. In this paper, we propose a cooperative caching replacement and efficiency optimization scheme for IP-based wireless networks. Wireless edges are designed to establish a one-hop scope of caching information table for caching replacement in cases when there is not e

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Santhanakrishnan, Ganesh, Ahmed Amer, and Panos K. Chrysanthis. "Self-tuning caching: the Universal Caching algorithm." Software: Practice and Experience 36, no. 11-12 (2006): 1179–88. http://dx.doi.org/10.1002/spe.755.

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Han, Luchao, Zhichuan Guo, and Xuewen Zeng. "Research on Multicore Key-Value Storage System for Domain Name Storage." Applied Sciences 11, no. 16 (2021): 7425. http://dx.doi.org/10.3390/app11167425.

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This article proposes a domain name caching method for the multicore network-traffic capture system, which significantly improves insert latency, throughput and hit rate. The caching method is composed of caching replacement algorithm, cache set method. The method is easy to implement, low in deployment cost, and suitable for various multicore caching systems. Moreover, it can reduce the use of locks by changing data structures and algorithms. Experimental results show that compared with other caching system, our proposed method reaches the highest throughput under multiple cores, which indica

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Soleimani, Somayeh, and Xiaofeng Tao. "Caching and Placement for In-Network Caching in Device-to-Device Communications." Wireless Communications and Mobile Computing 2018 (September 26, 2018): 1–9. http://dx.doi.org/10.1155/2018/9539502.

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Caching content by users constitutes a promising solution to decrease the costly transmissions with going through the base stations (BSs). To improve the performance of in-network caching in device-to-device (D2D) communications, caching placement and content delivery should be jointly optimized. To this end, we jointly optimize caching decision and content discovery strategies by considering the successful content delivery in D2D links for maximizing the in-network caching gain through D2D communications. Moreover, an in-network caching placement problem is formulated as an integer nonlinear

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11

Naeem, Nor, Hassan, and Kim. "Compound Popular Content Caching Strategy in Named Data Networking." Electronics 8, no. 7 (2019): 771. http://dx.doi.org/10.3390/electronics8070771.

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The aim of named data networking (NDN) is to develop an efficient data dissemination approach by implementing a cache module within the network. Caching is one of the most prominent modules of NDN that significantly enhances the Internet architecture. NDN-cache can reduce the expected flood of global data traffic by providing cache storage at intermediate nodes for transmitted contents, making data broadcasting in efficient way. It also reduces the content delivery time by caching popular content close to consumers. In this study, a new content caching mechanism named the compound popular cont

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12

Wang, Yantong, and Vasilis Friderikos. "A Survey of Deep Learning for Data Caching in Edge Network." Informatics 7, no. 4 (2020): 43. http://dx.doi.org/10.3390/informatics7040043.

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The concept of edge caching provision in emerging 5G and beyond mobile networks is a promising method to deal both with the traffic congestion problem in the core network, as well as reducing latency to access popular content. In that respect, end user demand for popular content can be satisfied by proactively caching it at the network edge, i.e., at close proximity to the users. In addition to model-based caching schemes, learning-based edge caching optimizations have recently attracted significant attention, and the aim hereafter is to capture these recent advances for both model-based and d

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Rim, Minjoong. "Mixed Micro/Macro Cache for Device-to-Device Caching Systems in Multi-Operator Environments." Sensors 24, no. 14 (2024): 4518. http://dx.doi.org/10.3390/s24144518.

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In a device-to-device (D2D) caching system that utilizes a device’s available storage space as a content cache, a device called a helper can provide content requested by neighboring devices, thereby reducing the burden on the wireless network. To enhance the efficiency of a limited-size cache, one can consider not only macro caching, which is content-based caching based on content popularity, but also micro caching, which is chunk-based sequential prefetching and stores content chunks slightly behind the one that a nearby device is currently viewing. If the content in a cache can be updated in

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14

Chae, Seong Ho, and Wan Choi. "Caching Placement in Stochastic Wireless Caching Helper Networks: Channel Selection Diversity via Caching." IEEE Transactions on Wireless Communications 15, no. 10 (2016): 6626–37. http://dx.doi.org/10.1109/twc.2016.2586841.

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15

Hao, Yixue, Min Chen, Donggang Cao, et al. "Cognitive-Caching: Cognitive Wireless Mobile Caching by Learning Fine-Grained Caching-Aware Indicators." IEEE Wireless Communications 27, no. 1 (2020): 100–106. http://dx.doi.org/10.1109/mwc.001.1900273.

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16

Bai, Jingpan, Silei Zhu, and Houling Ji. "Blockchain Based Decentralized and Proactive Caching Strategy in Mobile Edge Computing Environment." Sensors 24, no. 7 (2024): 2279. http://dx.doi.org/10.3390/s24072279.

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In the mobile edge computing (MEC) environment, the edge caching can provide the timely data response service for the intelligent scenarios. However, due to the limited storage capacity of edge nodes and the malicious node behavior, the question of how to select the cached contents and realize the decentralized security data caching faces challenges. In this paper, a blockchain-based decentralized and proactive caching strategy is proposed in an MEC environment to address this problem. The novelty is that the blockchain was adopted in an MEC environment with a proactive caching strategy based

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17

Nguyen, Quang Ngoc, Jiang Liu, Zhenni Pan, et al. "PPCS: A Progressive Popularity-Aware Caching Scheme for Edge-Based Cache Redundancy Avoidance in Information-Centric Networks." Sensors 19, no. 3 (2019): 694. http://dx.doi.org/10.3390/s19030694.

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This article proposes a novel chunk-based caching scheme known as the Progressive Popularity-Aware Caching Scheme (PPCS) to improve content availability and eliminate the cache redundancy issue of Information-Centric Networking (ICN). Particularly, the proposal considers both entire-object caching and partial-progressive caching for popular and non-popular content objects, respectively. In the case that the content is not popular enough, PPCS first caches initial chunks of the content at the edge node and then progressively continues caching subsequent chunks at upstream Content Nodes (CNs) al

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18

Piastou, Mikita. "Evaluating the Efficiency of Caching Strategies in Reducing Application Latency." Journal of Science & Technology 4, no. 6 (2023): 83–98. http://dx.doi.org/10.55662/jst.2023.4606.

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The paper discusses the efficiency of various caching strategies that can reduce application latency. A test application was developed for this purpose to measure latency from various conditions using logging and profiling tools. These scenario tests simulated high traffic loads, large data sets, and frequent access patterns. The simulation was done in Java; accordingly, T-tests and ANOVA were conducted in order to measure the significance of the results. The findings showed that the highest reduction in latency was achieved by in-memory caching: response time improved by up to 62.6% compared

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Yan, Li, and Yan Sheng Qu. "Research on Caching Mechanism Based on User Community." Applied Mechanics and Materials 672-674 (October 2014): 2013–16. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.2013.

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This paper produced a data caching system framework based on two-layer Chord. Caching is shared by users in domain and hot accessing information is shared by inter-domain users. It effectively reduces the caching system’s overhead. We also introduced cache replacement algorithm based on the user community, especially the user’s influence in the community and the information flow dynamics. The result of simulation and experiment of test-bed environment shows the caching scheme based on user community outperforms most existing distributed caching schemes.

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20

Li, Qi, Xiaoxiang Wang, Dongyu Wang, et al. "Analysis of an SDN-Based Cooperative Caching Network with Heterogeneous Contents." Electronics 8, no. 12 (2019): 1491. http://dx.doi.org/10.3390/electronics8121491.

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The ubiquity of data-enabled mobile devices and wireless-enabled data applications has fostered the rapid development of wireless content caching, which is an efficient approach to mitigating cellular traffic pressure. Considering the content characteristics and real caching circumstances, a software-defined network (SDN)-based cooperative caching system is presented. First, we define a new file block library with heterogeneous content attributes [file popularity, mobile user (MU) preference, file size]. An SDN-based three-tier caching network is presented in which the base station supplies co

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Al-Sayeh, Hani, Muhammad Attahir Jibril, Muhammad Waleed Bin Saeed, and Kai-Uwe Sattler. "SparkCAD." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3694–97. http://dx.doi.org/10.14778/3554821.3554877.

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Developers of Apache Spark applications can accelerate their workloads by caching suitable intermediate results in memory and reusing them rather than recomputing them all over again every time they are needed. However, as scientific workflows are becoming more complex, application developers are becoming more prone to making wrong caching decisions, which we refer to as caching anomalies , that lead to poor performance. We present and give a demonstration of Spark Caching Anomalies Detector (SparkCAD) , a developer decision support tool that visualizes the logical plan of Spark applications a

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22

Kuznetsov, O. V., L. E. Chala, and S. G. Udovenko. "Neural network data caching method." Bionics of Intelligence 1, no. 90 (2018): 84–90. https://doi.org/10.30837/bi.2018.1(90).12.

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Main existing types of caching and algorithms of saving cached data were analyzed. The new type of caching based on neural networks was proposed. results of proof of concept project were analyzed. Proposed type of caching was reviewed as a solution to a problem of Belady algorithm. The scale of subject area to use neural type of caching was determined.

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Naeem, Muhammad, Rashid Ali, Byung-Seo Kim, Shahrudin Nor, and Suhaidi Hassan. "A Periodic Caching Strategy Solution for the Smart City in Information-Centric Internet of Things." Sustainability 10, no. 7 (2018): 2576. http://dx.doi.org/10.3390/su10072576.

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Named Data Networking is an evolving network model of the Information-centric networking (ICN) paradigm which provides Named-based data contents. In-network caching is the responsible for dissemination of these contents in a scalable and cost-efficient way. Due to the rapid expansion of Internet of Things (IoT) traffic, ICN is envisioned to be an appropriate architecture to maintain the IoT networks. In fact, ICN offers unique naming, multicast communications and, most beneficially, in-network caching that minimizes the response latency and server load. IoT environment involves a study of ICN

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Krause, Douglas J., and Tracey L. Rogers. "Food caching by a marine apex predator, the leopard seal (Hydrurga leptonyx)." Canadian Journal of Zoology 97, no. 6 (2019): 573–78. http://dx.doi.org/10.1139/cjz-2018-0203.

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The foraging behaviors of apex predators can fundamentally alter ecosystems through cascading predator–prey interactions. Food caching is a widely studied, taxonomically diverse behavior that can modify competitive relationships and affect population viability. We address predictions that food caching would not be observed in the marine environment by summarizing recent caching reports from two marine mammal and one marine reptile species. We also provide multiple caching observations from disparate locations for a fourth marine predator, the leopard seal (Hydrurga leptonyx (de Blainville, 182

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Ma, Zhenjie, Haoran Wang, Ke Shi, and Xinda Wang. "Learning Automata Based Caching for Efficient Data Access in Delay Tolerant Networks." Wireless Communications and Mobile Computing 2018 (2018): 1–19. http://dx.doi.org/10.1155/2018/3806907.

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Effective data access is one of the major challenges in Delay Tolerant Networks (DTNs) that are characterized by intermittent network connectivity and unpredictable node mobility. Currently, different data caching schemes have been proposed to improve the performance of data access in DTNs. However, most existing data caching schemes perform poorly due to the lack of global network state information and the changing network topology in DTNs. In this paper, we propose a novel data caching scheme based on cooperative caching in DTNs, aiming at improving the successful rate of data access and red

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Keller, Robert M., and M. R. Sleep. "Applicative caching." ACM Transactions on Programming Languages and Systems 8, no. 1 (1986): 88–108. http://dx.doi.org/10.1145/5001.5004.

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DeBrabant, Justin, Andrew Pavlo, Stephen Tu, Michael Stonebraker, and Stan Zdonik. "Anti-caching." Proceedings of the VLDB Endowment 6, no. 14 (2013): 1942–53. http://dx.doi.org/10.14778/2556549.2556575.

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Gray, Howard Richard. "Geo-Caching." Journal of Museum Education 32, no. 3 (2007): 285–91. http://dx.doi.org/10.1080/10598650.2007.11510578.

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Englert, Matthias, Heiko Röglin, Jacob Spönemann, and Berthold Vöcking. "Economical Caching." ACM Transactions on Computation Theory 5, no. 2 (2013): 1–21. http://dx.doi.org/10.1145/2493246.2493247.

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Afek, Yehuda, Geoffrey Brown, and Michael Merritt. "Lazy caching." ACM Transactions on Programming Languages and Systems 15, no. 1 (1993): 182–205. http://dx.doi.org/10.1145/151646.151651.

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31

Barr, Thomas W., Alan L. Cox, and Scott Rixner. "Translation caching." ACM SIGARCH Computer Architecture News 38, no. 3 (2010): 48–59. http://dx.doi.org/10.1145/1816038.1815970.

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Srinath, Harsha, and Shiva Shankar Ramanna. "Web caching." Resonance 7, no. 7 (2002): 54–62. http://dx.doi.org/10.1007/bf02836754.

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Nanda, Pranay, Shamsher Singh, and G. L. Saini. "A Review of Web Caching Techniques and Caching Algorithms for Effective and Improved Caching." International Journal of Computer Applications 128, no. 10 (2015): 41–45. http://dx.doi.org/10.5120/ijca2015906656.

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Zhang, Jiaqi, Wenjing Liu, Li Zhang, and Jie Tian. "Enhanced In-Network Caching for Deep Learning in Edge Networks." Electronics 13, no. 23 (2024): 4632. http://dx.doi.org/10.3390/electronics13234632.

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With the deep integration of communication technology and Internet of Things technology, the edge network structure is becoming increasingly dense and heterogeneous. At the same time, in the edge network environment, characteristics such as wide-area differentiated services, decentralized deployment of computing and network resources, and highly dynamic network environment lead to the deployment of redundant or insufficient edge cache nodes, which restricts the efficiency of network service caching and resource allocation. In response to the above problems, research on the joint optimization o

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Kim, Yunkon, and Eui-Nam Huh. "EDCrammer: An Efficient Caching Rate-Control Algorithm for Streaming Data on Resource-Limited Edge Nodes." Applied Sciences 9, no. 12 (2019): 2560. http://dx.doi.org/10.3390/app9122560.

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This paper explores data caching as a key factor of edge computing. State-of-the-art research of data caching on edge nodes mainly considers reactive and proactive caching, and machine learning based caching, which could be a heavy task for edge nodes. However, edge nodes usually have relatively lower computing resources than cloud datacenters as those are geo-distributed from the administrator. Therefore, a caching algorithm should be lightweight for saving computing resources on edge nodes. In addition, the data caching should be agile because it has to support high-quality services on edge

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Man, Dapeng, Yao Wang, Hanbo Wang, et al. "Information-Centric Networking Cache Placement Method Based on Cache Node Status and Location." Wireless Communications and Mobile Computing 2021 (September 14, 2021): 1–13. http://dx.doi.org/10.1155/2021/5648765.

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Information-Centric Networking with caching is a very promising future network architecture. The research on its cache deployment strategy is divided into three categories, namely, noncooperative cache, explicit collaboration cache, and implicit collaboration cache. Noncooperative caching can cause problems such as high content repetition rate in the web cache space. Explicit collaboration caching generally reflects the best caching effect but requires a lot of communication to satisfy the exchange of cache node information and depends on the controller to perform the calculation. On this basi

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Zhou, Tianchi, Peng Sun, and Rui Han. "An Active Path-Associated Cache Scheme for Mobile Scenes." Future Internet 14, no. 2 (2022): 33. http://dx.doi.org/10.3390/fi14020033.

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With the widespread growth of mass content, information-centric networks (ICN) have become one of the research hotspots of future network architecture. One of the important features of ICN is ubiquitous in-network caching. In recent years, the explosive growth of mobile devices has brought content dynamics, which poses a new challenge to the original ICN caching mechanism. This paper focuses on the WiFi mobile scenario of ICN. We design a new path-associated active caching scheme to shorten the time delay of users obtaining content to enhance the user experience. In this article, based on the

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Zheng, Yi-fan, Ning Wei, and Yi Liu. "Collaborative Computation for Offloading and Caching Strategy Using Intelligent Edge Computing." Mobile Information Systems 2022 (July 30, 2022): 1–12. http://dx.doi.org/10.1155/2022/4840801.

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Computation offloading and caching strategy is a well-established concept for allowing mobile applications that are high in resources. Furthermore, the unloaded duties can be replicated when several customers are within easy access because of the rising mobile cooperation applications. However, the problematic characteristics of offloading and caching strategy delay bandwidth transfer from mobile computing devices to cloud computing. A new technical approach to restrict the issues and unwanted functions in offloading and caching is called the intellectual power computing framework (IPCF). IPCF

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Zhang, Xinyu, Zhigang Hu, Meiguang Zheng, et al. "LFDC: Low-Energy Federated Deep Reinforcement Learning for Caching Mechanism in Cloud–Edge Collaborative." Applied Sciences 13, no. 10 (2023): 6115. http://dx.doi.org/10.3390/app13106115.

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The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings. Deep reinforcement learning (DRL), with its ability to perceive the environment and develop intelligent policies online, has been widely employed for designing caching strategies. Recently, federated learning, when combined with DRL, has been in gaining popularity for optimizing caching strategies and protecting data training privacy from eavesdropping attacks. However, online fe

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Naeem, Muhammad Ali, Rehmat Ullah, Sushank Chudhary, and Yahui Meng. "A Critical Analysis of Cooperative Caching in Ad Hoc Wireless Communication Technologies: Current Challenges and Future Directions." Sensors 25, no. 4 (2025): 1258. https://doi.org/10.3390/s25041258.

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The exponential growth of wireless traffic has imposed new technical challenges on the Internet and defined new approaches to dealing with its intensive use. Caching, especially cooperative caching, has become a revolutionary paradigm shift to advance environments based on wireless technologies to enable efficient data distribution and support the mobility, scalability, and manageability of wireless networks. Mobile ad hoc networks (MANETs), wireless mesh networks (WMNs), Wireless Sensor Networks (WSNs), and Vehicular ad hoc Networks (VANETs) have adopted caching practices to overcome these hu

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Amey Pophali. "Distributed caching strategies to enhance E-commerce transaction speed." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1860–71. https://doi.org/10.30574/wjarr.2025.26.2.1809.

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Distributed caching represents a critical architectural strategy for enhancing transaction speed in e-commerce environments. This article examines how strategically positioning frequently accessed data across multiple networked nodes significantly reduces latency while decreasing database load. The assessment framework developed for evaluating caching technologies incorporates both quantitative performance metrics and practical implementation considerations specific to e-commerce workloads. Results demonstrate that in-memory solutions consistently outperform disk-based alternatives, with hybri

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Zulfa, Mulki Indana, Rudy Hartanto, and Adhistya Erna Permanasari. "Caching strategy for Web application – a systematic literature review." International Journal of Web Information Systems 16, no. 5 (2020): 545–69. http://dx.doi.org/10.1108/ijwis-06-2020-0032.

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Purpose Internet users and Web-based applications continue to grow every day. The response time on a Web application really determines the convenience of its users. Caching Web content is one strategy that can be used to speed up response time. This strategy is divided into three main techniques, namely, Web caching, Web prefetching and application-level caching. The purpose of this paper is to put forward a literature review of caching strategy research that can be used in Web-based applications. Design/methodology/approach The methods used in this paper were as follows: determined the review

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Hurly, T. Andrew, and Raleigh J. Robertson. "Scatterhoarding by territorial red squirrels: a test of the optimal density model." Canadian Journal of Zoology 65, no. 5 (1987): 1247–52. http://dx.doi.org/10.1139/z87-194.

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We observed a high degree of scatterhoarding in a population of red squirrels and tested two predictions of the Optimal Density Model (ODM): (1) large food items will be cached at a greater distance from their source than small items; and (2) caches will be uniformly distributed about their source. Caching experiments supported prediction 1. Red squirrels carried large food items farther than small items before caching them. Prediction 2 was not supported; caches were distributed nonuniformly about their source both within and among caching bouts. We present a simple null model for scatterhoar

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Park, Seongsoo, Minseop Jeong, and Hwansoo Han. "CCA: Cost-Capacity-Aware Caching for In-Memory Data Analytics Frameworks." Sensors 21, no. 7 (2021): 2321. http://dx.doi.org/10.3390/s21072321.

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To process data from IoTs and wearable devices, analysis tasks are often offloaded to the cloud. As the amount of sensing data ever increases, optimizing the data analytics frameworks is critical to the performance of processing sensed data. A key approach to speed up the performance of data analytics frameworks in the cloud is caching intermediate data, which is used repeatedly in iterative computations. Existing analytics engines implement caching with various approaches. Some use run-time mechanisms with dynamic profiling and others rely on programmers to decide data to cache. Even though c

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Sheraz, Muhammad, Shahryar Shafique, Sohail Imran, et al. "A Reinforcement Learning Based Data Caching in Wireless Networks." Applied Sciences 12, no. 11 (2022): 5692. http://dx.doi.org/10.3390/app12115692.

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Data caching has emerged as a promising technique to handle growing data traffic and backhaul congestion of wireless networks. However, there is a concern regarding how and where to place contents to optimize data access by the users. Data caching can be exploited close to users by deploying cache entities at Small Base Stations (SBSs). In this approach, SBSs cache contents through the core network during off-peak traffic hours. Then, SBSs provide cached contents to content-demanding users during peak traffic hours with low latency. In this paper, we exploit the potential of data caching at th

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Thodupunuri, Mohit. "Security and Performance in Modern CDN Caching: A Study of Akamai?s Caching Infrastructure." International Journal of Science and Research (IJSR) 14, no. 1 (2025): 715–18. https://doi.org/10.21275/sr25114224021.

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Dr., H. B. Patelpaik. "Machine Learning-Based Optimization of Web Caching: A Support Vector Machine Model." International Journal of Advance and Applied Research S6, no. 18 (2025): 282–88. https://doi.org/10.5281/zenodo.15259563.

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<em>In the era of information technology, the Internet serves as a critical medium for accessing information globally. The World Wide Web (WWW) facilitates a diverse range of Internet-based services, including e-commerce, online banking, entertainment, education, and e-governance. However, the exponential growth in web applications has led to a substantial increase in network traffic, causing congestion and elevating server loads. This, in turn, results in higher response times, thereby negatively impacting user experience. Web caching has emerged as an effective solution to mitigate latency i

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Yin, Jiliang, Congfeng Jiang, Hidetoshi Mino, and Christophe Cérin. "Popularity-Aware In-Network Caching for Edge Named Data Network." Wireless Communications and Mobile Computing 2021 (August 30, 2021): 1–13. http://dx.doi.org/10.1155/2021/3791859.

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The traditional centralized network architecture can lead to a bandwidth bottleneck in the core network. In contrast, in the information-centric network, decentralized in-network caching can alleviate the traffic flow pressure from the network center to the edge. In this paper, a popularity-aware in-network caching policy, namely, Pop, is proposed to achieve an optimal caching of network contents in the resource-constrained edge networks. Specifically, Pop senses content popularity and distributes content caching without adding additional hardware and traffic overhead. We conduct extensive per

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Jia, Qingmin, RenChao Xie, Tao Huang, Jiang Liu, and Yunjie Liu. "Caching Resource Sharing for Network Slicing in 5G Core Network." Journal of Organizational and End User Computing 31, no. 4 (2019): 1–18. http://dx.doi.org/10.4018/joeuc.2019100101.

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Network slicing has been considered a promising technology in next generation mobile networks (5G), which can create virtual networks and provide customized service on demand. Most existing works on network slicing mainly focus on virtualization technology, and have not considered in-network caching well. However, in-network caching, as the one of the key technologies for information-centric networking (ICN), has been considered as a significant approach in 5G network to cope with the traffic explosion and network challenges. In this article, the authors jointly consider in-network caching com

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Naeem, Muhammad Ali, Yahui Meng, and Sushank Chaudhary. "The Impact of Federated Learning on Improving the IoT-Based Network in a Sustainable Smart Cities." Electronics 13, no. 18 (2024): 3653. http://dx.doi.org/10.3390/electronics13183653.

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The caching mechanism of federated learning in smart cities is vital for improving data handling and communication in IoT environments. Because it facilitates learning among separately connected devices, federated learning makes it possible to quickly update caching strategies in response to data usage without invading users’ privacy. Federated learning caching promotes improved dynamism, effectiveness, and data reachability for smart city services to function properly. In this paper, a new caching strategy for Named Data Networking (NDN) based on federated learning in smart cities’ IoT contex

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