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On a hierarchical Content caching and Asynchronous Updating Scheme for Non-Terrestrial Network-Assisted Connected Automated Vehicles

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第1期43卷 64-74页

作者： Mao, Bomin Liu, Yangbo Guo, Hongzhi Xun, Yijie Wang, Jiadai Liu, Jiajia Kato, Nei Northwestern Polytech Univ Res & Dev Inst Natl Engn Lab Integrated Aerosp Ground Ocean Big D Shenzhen 518057 Peoples R China Northwestern Polytech Univ Yangtze River Delta Res Inst Taicang 215400 Peoples R China Northwestern Polytech Univ Sch Cybersecur Xian 710129 Peoples R China Tohoku Univ Grad Sch Informat Sci Sendai 9808579 Japan

With the advantages of seamless coverage and ubiquitous connections, Non-Terrestrial Networks (NTNs) composed of Low Earth Orbit (LEO) satellites and Unmanned Aerial Vehicles (UAVs) can provide content caching services for future Connected Automated Vehicles (CAVs) to satisfy onboard collaborative viewing, traffic sensing, and metaverse entertainments in remote areas. However, the heterogeneous caching hardware, communication environments, and frequent network dynamics make the optimization of content caching policy highly complicated. Firstly, considering all LEO satellites as caching satellites can lead to content duplication and radio interference, causing storage waste and NTN transmission quality deterioration. Secondly, how to provide customized QoS by intra-layer and inter-layer cooperative caching in such complicated environments remains an open issue. Thus, we propose a Delay-Motivated Ant Colony Optimization (DM-ACO) scheme to select caching LEO satellites with reduced system propagation delay. Then, the Multi-Agent Deep Reinforcement Learning-based hierarchical caching and Asynchronous Updating (MADRL-HCAU) strategy is designed to manage the caching capacity of LEO satellites and UAVs, providing customized services for CAVs and dispensing the peak traffic. Simulation results illustrate that the proposed scheme can not only effectively accelerate the caching refreshing and content downloading process but also significantly reduce the packet drop and improve the cache hit ratio.

关键词： Satellites Low earth orbit satellites Delays Quality of service Satellite broadcasting Mathematical models Optimization Non-terrestrial networks hierarchical caching asynchronous updating ant colony optimization multi-agent deep reinforcement learning

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hierarchical caching Resource Sharing in 5G Cellular Networks with Virtualization

Hierarchical Caching Resource Sharing in 5G Cellular Network...

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IEEE International Conference on Communications (ICC) / Workshop on Integrating UAVs into 5G

作者： Xie, Renchao Wang, Rui Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Technol Beijing Adv Innovat Ctr Future Internet Technol Beijing 100124 Peoples R China

ISBN: (纸本)9781538643280

In the forthcoming fifth generation (5G) cellular networks, caching and virtualization have been considered as promising techniques. In this paper, we consider a hierarchical caching architecture that core network and radio access network (RAN) have caching capability with virtualization. Thus how to share caching resources among mobile virtual network operators (MVNOs) is an important issue, which is formulated as a competitive game to maximize their expected revenues based on the oligopoly market model. We decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.

关键词： hierarchical caching Resource Sharing Game Theory Oligopoly Market Model 5G Networks

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Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2020年 172卷

作者： Baccour, Emna Erbad, Aiman Mohamed, Amr Guizani, Mohsen Hamdi, Mounir Hamad Bin Khalifa Univ Coll Sci & Engn Ar Rayyan Qatar Qatar Univ Coll Engn CSE Dept Doha Qatar

To support multimedia applications, Mobile Edge Computing (MEC) servers offer storage and computing ca-pacities to handle videos close to end-users. However, the high load in peak hours consumes the limited available bandwidth of existing cellular and backhaul links leading to low network performance. Hence, an elastic system model is required to maintain the high Quality of Experience (QoE) as the resource demands increase. caching popular videos at mobile devices is considered a promising technique for content delivery. Yet, mobile users offer small capacities that are not adequate for large-sized video sharing. In this paper, we extend the collaborative caching and processing framework in edge networks (Collaborative Edge CE) to include the users' mobile video sharing (Device-to-Device D2D). We propose a caching strategy to cache only the chunks of videos to be watched and instead of offloading one video content by one edge node, helpers (MEC servers and users) will collaborate to store and share different chunks to optimize the storage/transmission resources usage. To only cache popular contents, we designed a D2D-aware proactive chunks caching on users' devices based on our chunks popularity model. Next, we formulate this CE-D2D collaborative problem as a linear program. Due to the NP-hardness of the problem, we introduce a sub-optimal relaxation and an online heuristic using the proactive caching and presenting a near optimal data offloading and a profitable payment determination, with polynomial time complexity. The simulation results show that our policies and heuristics outperform other edge caching approaches by more than 10% in terms of hit ratio, average delay, and cost.

关键词： MEC D2D VoD hierarchical caching Collaborative offloading Adaptive bitrate Incentive VCG mechanism

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Cooperative hierarchical caching and Request Scheduling in a Cloud Radio Access Network

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2018年第12期17卷 2729-2743页

作者： Tran, Tuyen X. Le, Duc V. Yue, Guosen Pompili, Dario Rutgers State Univ Dept Elect & Comp Engn New Brunswick NJ 08901 USA Univ Twente Dept Comp Sci NL-7522 Enschede Netherlands Futurewei Technol Huawei R&D Bridgewater NJ 08807 USA

In this article, we propose a novel cooperative hierarchical caching framework in a Cloud Radio Access Network (C-RAN), in which a new cloud-cache at Cloud Processing Unit (CPU) is envisioned to bridge the storage-capacity/delay-performance gap between the traditional edge-based and core-based caching paradigms. A delay-cost model is introduced and the cache placement problem is formulated that aims at minimizing the average delay-cost of content delivery in the network. Given the NP-completeness of the cache placement problem, we propose a low-complexity heuristic cache-management strategy comprising of a proactive cache-distribution algorithm and a reactive cache-replacement algorithm. Furthermore, a Cache-Aware Request Scheduling (CARS) algorithm is devised in order to optimize online the tradeoff between content download rate and content access delay. Via extensive numerical simulations-carried out using both real-world YouTube video requests and synthetic content requests-it is demonstrated that the proposed cache-management strategy outperforms traditional caching strategies in terms of cache hit ratio, average content access delay, and backhaul traffic load. Additionally, it is shown that the proposed CARS algorithm achieves superior tradeoff performance over traditional approaches that optimize either users' rate or access delay alone.

关键词： Cooperative caching hierarchical caching content request scheduling 5G cloud radio access networks optimization

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Neyman-Pearson Criterion Based Optimal hierarchical caching Over D2D Wireless Ad-Hoc Networks

Neyman-Pearson Criterion Based Optimal Hierarchical Caching ...

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IEEE Global Communications Conference (IEEE GLOBECOM)

作者： Zhang, Xi Zhu, Qixuan Poor, H. Vincent Texas A&M Univ Dept Elect & Comp Engn Networking & Informat Syst Lab College Stn TX 77843 USA Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

ISBN: (纸本)9781728109626

caching in mobile devices is a new paradigm to revolutionize the traditional data content (i.e., files) sharing methods in wireless cellular networks. By caching popular data content items in mobile devices and disseminating them through device-to-device (D2D) communications, the wireless cellular network can improve its area spectral efficiency, save the base station bandwidth consumption, and reduce the transmission delay of downloading. caching is closely related to data popularity prediction, but how to accurately predict the future popularity profile has not been well understood. Moreover, although the hierarchical caching architecture has been shown to yield more benefits than flat caching strategies, the challenge of designing an optimal hierarchical caching scheme has not been thoroughly addressed. In this paper, we use a Neyman-Pearson hypothesis testing mechanism to predict the future data popularity, and also develop optimal hierarchical caching schemes over D2D wireless ad-hoc networks. The key of Neyman-Pearson hypothesis testing in our proposed scheme is to derive a closed form expression for the decision threshold, which is a function of costs of choosing the incorrect hypothesis. We formulate these costs as sums of time durations for content placement and content delivery phases. We derive closed form expressions for these two phases respectively and obtain a closed form of an optimal decision rule, which maximizes the cache hitting probability and upper-bounds the prediction error probability. Finally, we evaluate and validate our proposed Neyman-Pearson hypothesis testing based hierarchical caching schemes through numerical analyses.

关键词： hierarchical caching D2D communications ad-hoc wireless networks Neyman-Pearson hypothesis testing cost function Zipf distribution degree of freedom

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A high performance hierarchical caching framework for mobile edge computing environments

A high performance hierarchical caching framework for mobile...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Ghosh, Saibal Agrawal, Dharma P. Univ Cincinnati Ctr Distributed & Mobile Comp Cincinnati OH 45221 USA

ISBN: (纸本)9781728195056

Mobile Edge Computing (MEC) has been in the forefront recently for its ability to supplement cloud computing. MEC servers are deployed closer to the users at the network edge in order to reduce the latency and computation load on the cloud. Edge caching plays a dominant role in the MEC paradigm. Popular content is cached in the MEC nodes thereby reducing user access latencies. However, the cache capacity of MEC nodes are limited and therefore efficient caching mechanisms are required to make optimum utilization of MEC node caches. In this work we propose a novel, scalable, hierarchical size and access frequency aware caching policy for mobile edge computing. Our experiments show that the policy outperforms traditional caching policies at the cloud and is scalable with the next generation of workloads in MEC environments.

关键词： mobile edge computing hierarchical caching content popularity metrics internet of things

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An Intelligent hierarchical caching and Asynchronous Updating Scheme for 6G Non-Terrestrial Networks 25

An Intelligent Hierarchical Caching and Asynchronous Updatin...

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IEEE Wireless Communications and Networking Conference (IEEE WCNC)

作者： Liu, Yangbo Mao, Bomin Guo, Hongzhi Liu, Jiajia Northwestern Polytech Univ Sch Cybersecur Xian 710072 Peoples R China Northwestern Polytech Univ Yangtze River Delta Res Inst Taicang 215400 Jiangsu Peoples R China Northwestern Polytech Univ Shenzhen Res Inst Shenzhen 518057 Guangdong Peoples R China

ISBN: (纸本)9798350303582;9798350303599

With the advantages of seamless coverage and ubiquitous connections, Non-Terrestrial Networks (NTNs) composed of Low Earth Orbit (LEO) satellites and Unmanned Aerial Vehicles (UAVs) can provide content caching services to reduce End-to-End (E2E) delay and alleviate the network traffic for future 6G applications including autonomous driving, eHealth, and metaverse. However, the ultra-density of LEO satellites complicates the selection of caching nodes, while the heterogeneous caching hardware and communication environments make optimization of content deployment highly difficult. To address these issues, we propose an intelligent hierarchical caching and asynchronous updating scheme. Specifically, a Delay-Motivated Ant Colony Optimization (DM-ACO) scheme is first adopted to select the caching LEO satellites to reduce the system propagation delay. Then, the Multi-Agent Reinforcement Learning-based hierarchical caching and Asynchronous Updating (MARL-HCAU) strategy is proposed to meet caching service demands. Simulation results illustrate that compared with the benchmarks, the overall cache hit ratio increases by 14.2% with the reduced packet drop rate and transmission delay by 8.78% and 0.94s, respectively.

关键词： Non-Terrestrial Networks hierarchical caching ant colony optimization reinforcement learning

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Octopus: A Cooperative hierarchical caching Strategy for Cloud Radio Access Networks 13

Octopus: A Cooperative Hierarchical Caching Strategy for Clo...

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13th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (IEEE MASS)

作者： Tran, Tuyen X. Pompili, Dario Rutgers State Univ Dept Elect & Comp Engn New Brunswick NJ 08903 USA

ISBN: (纸本)9781509028337

Recently, implementing Radio Access Network (RAN) functionalities on cloud-based computing platform has become an emerging solution that leverages the many advantages of cloud infrastructure, such as shared computing resources and storage capacity, while lowering the operational cost. In this paper, we propose a novel caching framework aimed at fully exploiting the potential of such Cloud-based RAN (C-RAN) systems through cooperative hierarchical caching which minimizes the network costs of content delivery and improves users' Quality of Experience (QoE). In particular, we consider the cloud-cache in the cloud processing unit (CPU) as a new layer in the RAN cache hierarchy, bridging the capacity performance gap between the traditional edge-based and core based caching schemes. A delay cost model is introduced to characterize and formulate the cache placement optimization problem, which is shown to be NP-complete. As such, a low complexity, heuristic cache management strategy is proposed, constituting of a proactive cache distribution algorithm and a reactive cache replacement algorithm. Extensive numerical simulations are carried out using both real-world YouTube video requests and synthetic content requests. It is demonstrated that our proposed Octopus caching strategy significantly outperforms the traditional caching strategies in terms of cache hit ratio, average content access delay and backhaul traffic load.

关键词： hierarchical caching cooperative caching cloud Radio Access Networks C-RAN

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Layered hierarchical caching for SVC-based HTTP adaptive streaming over C-RAN

Layered hierarchical caching for SVC-based HTTP adaptive str...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Zhang, Zhilong Liu, Danpu Yuan, Yaxiong Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst Architecture & Conve Beijing Lab Adv Informat Network Beijing 100876 Peoples R China

ISBN: (纸本)9781509041831

In recent decade, wireless networks face a large challenge of delivering HTTP adaptive streaming (HAS) due to the dramatic increase of traffic. Content caching is an effective method to relieve the burden of networks and has attracted considerable attention. Although some schemes have been investigated for content caching in cloud-based radio access networks (C-RAN), most of them were not designed for HAS. In this paper, we address the caching problem for SVC-based HAS over C-RAN. We propose a caching strategy with considering the layered property of video, the hierarchical caching architecture of C-RAN and the distribution of downloading rates. To our knowledge, no one has designed a caching scheme from such a perspective. A 0-1 programming problem is formulated to minimize the amount of backhaul traffic. Base on theoretical analysis and problem solving, a layered hierarchical caching algorithm is proposed which can provide an approximate ratio of 1/2. Simulation results are illustrated to show the effectiveness of our proposed method.

关键词： C-RAN hierarchical caching HTTP adaptive streaming SVC

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hierarchical web caching systems: Modeling, design and experimental results

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2002年第7期20卷 1305-1314页

作者： Che, H Tung, Y Wang, ZJ Santera Syst Inc Plano TX 75074 USA Univ S Alabama Mobile AL 36688 USA Univ Texas Arlington TX 76019 USA

This paper aims at finding fundamental design principles for hierarchical web caching. An analytical modeling technique is developed to characterize an uncooperative two-level hierarchical caching system where the least recently used (LRU) algorithm is locally run at each cache. With this modeling technique, we are able to identify a characteristic time for each cache, which plays a fundamental role in understanding the caching processes. In particular, a cache can be viewed roughly as a low-pass filter with its cutoff frequency equal to the inverse of the characteristic time. Documents with access frequencies lower than this cutoff frequency have good chances to pass through the cache without cache hits. This viewpoint enables us to take any branch of the cache tree as a tandem of low-pass filters at different cutoff frequencies, which further results in the finding of two fundamental design principles. Finally, to demonstrate how to use the, principles to guide the caching algorithm design, we propose a cooperative hierarchical web caching architecture based on these,principles. Both model-based and real trace simulation studies show that the proposed cooperative architecture results in more than 50% memory saving and substantial central processing unit (CPU) power saving for the management and update of cache entries compared with the traditional uncooperative hierarchical caching architecture.

关键词： cache replacement algorithms hierarchical caching least recently used (LRU) web caching

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