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49th Asilomar Conference on Signals, Systems and Computers

作者： Krishnan, Shankar Dhillon, Harpreet S. Virginia Tech Dept ECE Wireless VT Blacksburg VA USA

ISBN: (纸本)9781467385763

Increasing spatio-temporal correlation in the data demand makes it attractive to cache popular content directly on the user devices so that it can be delivered on demand to the neighboring devices through device-to-device (D2D) communications. Due to the limited storage capacity, each device can only cache a part of the popular content resulting in a distributed caching network. With device locations modeled as a Poisson Point Process (PPP), we assume that the file of interest for a typical device is partitioned into several file portions with each device caching one of the portions randomly. Two equivalent viewpoints for the analysis of coverage probability and average delay in a distributed caching network are discussed for varying cache probabilities and device activity factors.

关键词： distributed caching D2D network stochastic geometry Poisson point process coverage probability delay

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distributed caching Popular Services by Using Deep Q-Learning in Converged Networks 90

Distributed Caching Popular Services by Using Deep Q-Learnin...

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90th IEEE Vehicular Technology Conference (IEEE VTC-Fall)

作者： Fang, Yuzhe Xiong, Jian Cheng, Peng Zhang, Wei Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Univ Sydney Sch Elect & Informat Engn Sydney NSW Australia

ISBN: (纸本)9781728112206

Content caching offers an effective solution to reduce the traffic load and alleviate the burden on backhaul links in future wireless networks. In this paper, we study the converged networks to push and cache the popular services. The popular services are delivered by the broadcasting networks, and cached in the router nodes in a distributed cache network. Due to the limited storage capacity of the router node, we formulate the service scheduling problem as a Markov Decision Process (MDP), aiming to maximize the equivalent throughput. Considering the large state space involved in the distributed cache network, it is great challenge to obtain a tractable solution by the classical optimization algorithm. To tackle this problem, we propose a service scheduling strategy based on deep Q-learning. Simulation results demonstrate that the proposed scheme can significantly improve the equivalent throughput of the converged networks.

关键词： Converged network distributed caching traffic offloading markov decision process deep Q-learning

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distributed caching of Scientific Workflows in Multisite Cloud 31st

Distributed Caching of Scientific Workflows in Multisite Clo...

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31st International Conference on Database and Expert Systems Applications (DEXA)

作者： Heidsieck, Gaetan de Oliveira, Daniel Pacitti, Esther Pradal, Christophe Tardieu, Francois Valduriez, Patrick Univ Montpellier INRIA Montpellier France Univ Montpellier LIRMM Montpellier France Univ Montpellier CIRAD Montpellier France Univ Montpellier AGAP Montpellier France Univ Montpellier INRAE Montpellier France Univ Montpellier LEPSE Montpellier France Univ Fed Fluminense Niteroi RJ Brazil

ISBN: (纸本)9783030590512;9783030590505

Many scientific experiments are performed using scientific workflows, which are becoming more and more data-intensive. We consider the efficient execution of such workflows in the cloud, leveraging the heterogeneous resources available at multiple cloud sites (geo-distributed data centers). Since it is common for workflow users to reuse code or data from other workflows, a promising approach for efficient workflow execution is to cache intermediate data in order to avoid re-executing entire workflows. In this paper, we propose a solution for distributed caching of scientific workflows in a multisite cloud. We implemented our solution in the OpenAlea workflow system, together with cache-aware distributed scheduling algorithms. Our experimental evaluation on a three-site cloud with a data-intensive application in plant phenotyping shows that our solution can yield major performance gains, reducing total time up to 42% with 60% of same input data for each new execution.

关键词： Multisite cloud distributed caching Scientific workflow Workflow system Workflow scheduling

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A P2P streaming service architecture with distributed caching

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2007年第4期8卷 605-614页

作者： GUO Pan-hong YANG Yang LI Xin-you Department of Computer Science and Technology University of Science and Technology Beijing Beijing 100083 China China State Information Center Beijing 100045 China

Multimedia streaming served through peer-to-peer (P2P) networks is booming nowadays. However, the end-to-end streaming quality is generally unstable due to the variability of the state of serve-peers. On the other hand, proxy caching is a bandwidth-efficient scheme for streaming over the Internet, whereas it is a substantially expensive method needing dedicated powerful proxy servers. In this paper, we present a P2P cooperative streaming architecture combined with the advantages of both P2P networks and multimedia proxy caching techniques to improve the streaming quality of participating clients. In this frame- work, a client will simultaneously retrieve contents from the server and other peers that have viewed and cached the same title before. In the meantime, the client will also selectively cache the aggregated video content so as to serve still future clients. The associate protocol to facilitate the multi-path streaming and a distributed utility-based partial caching scheme are detailedly dis- cussed. We demonstrate the effectiveness of this proposed architecture through extensive simulation experiments on large, Inter- net-like topologies.

关键词： Cooperative steaming Peer-to-peer networks Partial caching scheme distributed caching

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IEICE TRANSACTIONS ON COMMUNICATIONS 2024年第5期E107B卷 398-407页

作者： Yoshida, Mikiya Ito, Yusuke Sato, Yurino Koga, Hiroyuki Okayama Univ Ctr Informat Technol & Management Okayama 7008530 Japan Univ Kitakyushu Grad Sch Environm Engn Kitakyushu 8080135 Japan Sasebo Coll Natl Inst Technol KOSEN Dept Control Engn Sasebo 8571193 Japan

Information -centric networking (ICN) provides lowlatency content delivery with in -network caching, but delivery latency depends on cache distance from consumers. To reduce delivery latency, a scheme to cluster domains and retain the main popular content in each cluster with a cache distribution range has been proposed, which enables consumers to retrieve content from neighboring clusters/caches. However, when the distribution of content popularity changes, all content caches may not be distributed adequately in a cluster, so consumers cannot retrieve them from nearby caches. We therefore propose a dynamic clustering scheme to adjust the cache distribution range in accordance with the change in content popularity and evaluate the effectiveness of the proposed scheme through simulation.

关键词： ICN distributed caching dynamic clustering

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A QoE centric distributed caching approach for vehicular video streaming in cellular networks

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2016年第12期16卷 1612-1624页

作者： Sun, Fei Liu, Bo Hou, Fen Zhou, Haibo Chen, Jiacheng Rui, Yun Gui, Lin Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Deakin Univ Sch Informat Technol Burwood Vic Australia Univ Macau Fac Sci & Technol Macau Peoples R China Univ Waterloo Broadband Commun Res BBCR Grp Waterloo ON N2L 3G1 Canada Chinese Acad Sci Shanghai Adv Res Inst Beijing Peoples R China

distributed caching-empowered wireless networks can greatly improve the efficiency of data storage and transmission and thereby the users' quality of experience (QoE). However, how this technology can alleviate the network access pressure while ensuring the consistency of content delivery is still an open question, especially in the case where the users are in fast motion. Therefore, in this paper, we investigate the caching issue emerging from a forthcoming scenario where vehicular video streaming is performed under cellular networks. Specifically, a QoE centric distributed caching approach is proposed to fulfill as many users' requests as possible, considering the limited caching space of base stations and basic user experience guarantee. Firstly, a QoE evaluation model is established using verified empirical data. Also, the mathematic relationship between the streaming bit rate and actual storage space is developed. Then, the distributed caching management for vehicular video streaming is formulated as a constrained optimization problem and solved with the generalized-reduced gradient method. Simulation results indicate that our approach can improve the users' satisfaction ratio by up to 40%. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： distributed caching QoE vehicular video streaming cellular network

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Smart-Cluster-Based distributed caching for Fog-IoT Networks

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IEEE INTERNET OF THINGS JOURNAL 2021年第5期8卷 3875-3884页

作者： Abkenar, Forough Shirin Khan, Komal S. Jamalipour, Abbas Univ Sydney Sch Elect & Informat Engn WiNG Lab Sydney NSW 2006 Australia

The idea of co-operative caching in a cache-enabled wireless network has gained much interest due to its services in terms of short service delay and improved transmission rate at the user end. In this article, we consider a co-operative caching mechanism for a fog-enabled Internet of Things (IoT) network. We propose a delay-minimizing policy for fog nodes (FNs), where the goal is to reduce the service delay for the IoT nodes, also known as terminal nodes (TNs). To this end, a novel smart clustering mechanism is proposed, aiming to efficiently assign FNs to the TNs while improving the network benefit by finding a tradeoff between the delay and the network's energy consumption. We perform mathematical analysis and extensive simulations to highlight the potential gain and the proposed policy.

关键词： Delay distributed caching energy consumption network benefit smart clustering (SC)

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Blockchain Storage Optimisation With Multi-Level distributed caching

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2022年第4期19卷 3724-3736页

作者： Heo, Jun Wook Ramachandran, Gowri Sankar Dorri, Ali Jurdak, Raja Queensland Univ Technol Sch Comp Sci Brisbane Qld 4000 Australia

Distribution, security, and immutability have led to the great success of blockchain in many applications, while contributing to major increases in ledger size. The storage challenge is one of the major barriers to the adoption of blockchain in the Internet of Things (IoT), which consists of many resource constrained devices. In this paper, we propose Multi-Level distributed caching (MLDC) for blockchain storage optimisation which reduces data replication based on data access patterns in a decentralised manner. For storage optimisation of data-centric blockchains, MLDC introduces a hierarchical storage class (SC), in which every node is assigned to an SC with its own Access Frequency (AF) threshold based on node availability. To reduce the number of replications shared among participant nodes, each node in a SC continues to remove unaccessed data from local storage based on a threshold time determined by the AF threshold of the SC, while maintaining all block hashes for consistency. Eventually, all nodes in MLDC store the most frequently accessed data in their local storage, so MLDC effectively reduces the storage and query costs while minimising network overhead. We also analyse the security of MLDC and quantitatively evaluate its performance for both the uniform access and exponentially decaying access patterns. The evaluation was carried out on a representative blockchain simulator with 15 storage nodes. Our results from 11 hours of experiments producing 6667 blocks and 39997 transactions show good performance for MLDC. The results of the experimentation for the exponentially decaying assess pattern show that MLDC can reduce the total storage cost by 83% compared to conventional blockchain systems, while maintaining blockchain consistency and data availability with a slight increase in network overhead and query cost.

关键词： Blockchains Security Optimization Costs Internet of Things Computer science Australia Blockchain Internet of Things (IoT) storage optimisation distributed caching

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Optimal Online Algorithms for File-Bundle caching and Generalization to distributed caching

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ACM TRANSACTIONS ON MODELING AND PERFORMANCE EVALUATION OF COMPUTING SYSTEMS 2021年第1期6卷 1–23页

作者： Qin, Tiancheng Etesami, S. Rasoul Univ Illinois Dept Ind & Syst Engn 104 S Mathews Ave Urbana IL 61801 USA Univ Illinois Dept Ind & Syst Engn Coordinated Sci Lab 104 S Mathews Ave Urbana IL 61801 USA

We consider a generalization of the standard cache problem called file-bundle caching, where different queries (tasks), each containing l >= 1 files, sequentially arrive. An online algorithm that does not know the sequence of queries ahead of time must adaptively decide on what files to keep in the cache to incur the minimum number of cache misses. Here a cache miss refers to the case where at least one file in a query is missing among the cache files. In the special case where l = 1, this problem reduces to the standard cache problem. We first analyze the performance of the classic least recently used (LRU) algorithm in this setting and show that LRU is a near-optimal online deterministic algorithm for file-bundle caching with regard to competitive ratio. We then extend our results to a generalized (h, k)-paging problem in this file-bundle setting, where the performance of the online algorithm with a cache size k is compared to an optimal offline benchmark of a smaller cache size h < k. In this latter case, we provide a randomized O(l ln k/k-h)-competitive algorithm for our generalized (h, k)-paging problem, which can be viewed as an extension of the classic marking algorithm. We complete this result by providing a matching lower bound for the competitive ratio, indicating that the performance of this modified marking algorithm is within a factor of 2 of any randomized online algorithm. Finally, we look at the distributed version of the file-bundle caching problem where there are m >= 1 identical caches in the system. In this case, we show that for m = l + 1 caches, there is a deterministic distributed caching algorithm that is (l(2) + l)-competitive and a randomized distributed caching algorithm that is O(l ln(2l + 1))-competitive when l >= 2. We also provide a general framework to devise other efficient algorithms for the distributed file-bundle caching problem and evaluate the performance of our results through simulations.

关键词： File-bundle caching generalized (h, k)-paging distributed caching LRU algorithm marking algorithm online algorithms competitive ratio

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Effect of User Mobility on the Performance of Device-to-Device Networks With distributed caching

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IEEE WIRELESS COMMUNICATIONS LETTERS 2017年第2期6卷 194-197页

作者： Krishnan, Shankar Dhillon, Harpreet S. Virginia Tech Dept ECE Wireless VT Blacksburg VA 24061 USA

We consider a distributed caching device-to-device network in which a user's file of interest is cached as several portions in the storage of other devices in the network. Assuming that the user needs to obtain all these file portions, the portions cached farther away naturally become the performance bottleneck. This is due to the fact that dominant interferers may be closer to the receiver than the serving device. Using a simple stochastic geometry model, we concretely demonstrate that this bottleneck can be loosened if the users are mobile. Gains obtained from mobility are quantified in terms of coverage probability.

关键词： Stochastic geometry distributed caching D2D network mobility Poisson point process coverage probability

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