About me

I am a PhD Candidate and Research Assistant at UMN Networking Lab in Computer Science and Engineering Department at the University of Minnesota advised by Prof. Zhi-Li Zhang. My research interests lie broadly in Content Distribution Networks (CDN), Information-Centric Networks (ICN), Software Defined Networks (SDN), and 5G mobile networking. More specifically, my research includes improving content caching through new abstraction frameworks and applied machine learning, designing resilient routing protocols, understanding and improving the performance of emerging 5G Networks with the goal of enhancing the performance of the current infrastructure to be more scalable and reliable to support emerging applications with ultra-high bandwidth and low latency requirements.

I am a member of the Inclusiveness, Diversity, Equity, and Advocacy committee CS-IDEA at the Computer Science and Engineering (CS&E) Dept since Fall 2019, and nominated to be the CS&E Grad Coordinator for Inclusiveness, Diversity, Equity, and Advocacy since Fall 2020. I have been an officer for the Computer Science Graduate Student Association CSGSA from Fall 2018 to Summer 2020.

Publications

[1] 5G Tracker - A Crowdsourced Platform to Enable Research Using Commercial 5G Services
Arvind Narayanan, Eman Ramadan, Jacob Quant, Peiqi Ji, Feng Qian, Zhi-Li Zhang
ACM SIGCOMM 2020, Virtual Event, USA, August, 2020. SIGCOMM, August 2020 poster Website Mozilla Hubs

[2] A First Measurement Study of Commercial mmWave 5G Performance on Smartphones
Arvind Narayanan, Eman Ramadan, Jason Carpenter, Qingxu Liu, Yu Liu, Feng Qian, and Zhi-Li Zhang
In The Web Conference, 2020. WWW, April 2020 Abstract

We conduct to our knowledge a first measurement study of commercial 5G performance on smartphones by closely examining 5G networks of three carriers (two mmWave carriers, one mid-band carrier) in three U.S. cities. We conduct extensive field tests on 5G performance in diverse urban environments. We systematically analyze the handoff mechanisms in 5G and their impact on network performance. We explore the feasibility of using location and possibly other environmental information to predict the network performance. We also study the app performance (web browsing and HTTP download) over 5G. Our study consumes more than 15 TB of cellular data. Conducted when 5G just made its debut, it provides a “baseline” for studying how 5G performance evolves, and identifies key research directions on improving 5G users’ experience in a cross-layer manner. We have released the data collected from our study (referred to as 5Gophers) at https://fivegophers.umn.edu/www20.

BibTeX

@inproceedings{10.1145/3366423.3380169, author = {Narayanan, Arvind and Ramadan, Eman and Carpenter, Jason and Liu, Qingxu and Liu, Yu and Qian, Feng and Zhang, Zhi-Li}, title = {A First Look at Commercial 5G Performance on Smartphones}, year = {2020}, isbn = {9781450370233}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3366423.3380169}, doi = {10.1145/3366423.3380169}, booktitle = {Proceedings of The Web Conference 2020}, pages = {894–905}, numpages = {12}, keywords = {Cellular Network Measurement., Cellular Performance, 5G, Millimeter Wave, 5Gophers}, location = {Taipei, Taiwan}, series = {WWW '20} }

Website Slides

[3] Performance Estimation and Evaluation Framework for Caching Policies in Hierarchical Caches
Eman Ramadan, Pariya Babaie, Zhi-Li Zhang
In Computer Communications, Volume 144. Computer Communications, 2019 Abstract

The emergence of information-centric network (ICN) architectures has attracted a flurry of renewed research interest in caching policies and their performance analysis. One important feature ICNs offer that is distinct from classical computer caches is a distributed network of caches, namely, a cache network which poses additional challenges both in terms of practical cache management issues and performance analysis. Much attention of the research community has focused on performance analysis of cache networks under various caching policies. However, the issue of how to evaluate and compare caching policies for cache networks has not been adequately addressed. In this paper, we propose a novel and general framework for evaluating caching policies in a hierarchical network of caches. We introduce the notion of a hit probability/rate matrix, and employ a generalized notion of majorization as the basic tool for evaluating caching policies for various performance metrics. We discuss how the framework can be applied to existing caching policies, and conduct an extensive simulation-based evaluation to demonstrate the utility and accuracy of our framework.

BibTeX

@article{RAMADAN201944, title = "Performance Estimation and Evaluation Framework for Caching Policies in Hierarchical Caches", journal = "Computer Communications", volume = "144", pages = "44 - 56", year = "2019", issn = "0140-3664", doi = "https://doi.org/10.1016/j.comcom.2019.05.006", url = "http://www.sciencedirect.com/science/article/pii/S0140366419303524", author = "Eman Ramadan and Pariya Babaie and Zhi-Li Zhang", keywords = "BIG cache, Content caching, Hierarchical caching, Performance estimation, Performance evaluation, Cache management, Content delivery networks, Information-centric networks", abstract = "The emergence of information-centric network (ICN) architectures has attracted a flurry of renewed research interest in caching policies and their performance analysis. One important feature ICNs offer that is distinct from classical computer caches is a distributed network of caches, namely, a cache network which poses additional challenges both in terms of practical cache management issues and performance analysis. Much attention of the research community has focused on performance analysis of cache networks under various caching policies. However, the issue of how to evaluate and compare caching policies for cache networks has not been adequately addressed. In this paper, we propose a novel and general framework for evaluating caching policies in a hierarchical network of caches. We introduce the notion of a hit probability/rate matrix, and employ a generalized notion of majorization as the basic tool for evaluating caching policies for various performance metrics. We discuss how the framework can be applied to existing caching policies, and conduct an extensive simulation-based evaluation to demonstrate the utility and accuracy of our framework." }


[4] Making Content Caching Policies ’Smart’ Using the DEEPCACHE Framework
Arvind Narayanan, Saurabh Verma, Eman Ramadan, Pariya Babaie, Zhi-Li Zhang
In ACM SIGCOMM Computer Communication Review. SIGCOMM CCR 2019 Abstract

In this paper, we present Deepcache a novel Framework for content caching, which can significantly boost cache performance. Our Framework is based on powerful deep recurrent neural network models. It comprises of two main components: i) Object Characteristics Predictor, which builds upon deep LSTM Encoder-Decoder model to predict the future characteristics of an object (such as object popularity) - to the best of our knowledge, we are the first to propose LSTM Encoder-Decoder model for content caching; ii) a caching policy component, which accounts for predicted information of objects to make smart caching decisions. In our thorough experiments, we show that applying Deepcache Framework to existing cache policies, such as LRU and k-LRU, significantly boosts the number of cache hits.

BibTeX

@article{Narayanan:2019:MCC:3310165.3310174, author = {Narayanan, Arvind and Verma, Saurabh and Ramadan, Eman and Babaie, Pariya and Zhang, Zhi-Li}, title = {Making Content Caching Policies 'Smart' Using the Deepcache Framework}, journal = {SIGCOMM Comput. Commun. Rev.}, issue_date = {October 2018}, volume = {48}, number = {5}, month = jan, year = {2019}, issn = {0146-4833}, pages = {64--69}, numpages = {6}, url = {http://doi.acm.org/10.1145/3310165.3310174}, doi = {10.1145/3310165.3310174}, acmid = {3310174}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {DeepCache, cache hit, caching, deep learning, fake requests, lstm, machine learning, popularity prediction, prefetching, proactive caching, seq2seq, smart caching policies, video object caches}, }


[5] Cache Network Management Using BIG Cache Abstraction
Pariya Babaie, Eman Ramadan, Zhi-Li Zhang
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications INFOCOM 2019 Abstract

In this paper, we develop an optimization decomposition framework for cache management under “BIG” cache abstraction which fully utilizes the cache resources in a cache network. We assign a utility function to each content, and formulate a joint optimization problem to maximize the overall utility of a cache network. We show that this global network utility maximization problem can be decomposed into two sub-problems, the cache allotment problem and object placement problem, which can be solved separately and iteratively. This decoupling enables us to separately optimize the performance objectives from the perspectives of content providers, cache network operators, and users. We provide exact solution to the object placement problem with Poisson and Pareto request interarrival distributions. We also devise a primal-dual algorithm for online content management. We conduct extensive numerical analysis and simulations to evaluate the performance of our optimization decomposition framework, and study the impact of various key factors such as hazard rate functions of the request interarrival distributions and object popularities. We show that our optimization decomposition framework outperform existing heuristic methods.

BibTeX

@INPROCEEDINGS{8737407, author={P. {Babaie} and E. {Ramadan} and Z. {Zhang}}, booktitle={IEEE INFOCOM 2019 - IEEE Conference on Computer Communications}, title={Cache Network Management Using BIG Cache Abstraction}, year={2019}, volume={}, number={}, pages={226-234}, keywords={cache storage;content management;optimisation;resource allocation;statistical distributions;cache network management;big cache abstraction;optimization decomposition framework;cache management;cache resources;utility function;joint optimization problem;global network utility maximization problem;cache allotment problem;object placement problem;performance objectives;cache network operators;online content management;Pareto request interarrival distribution;Poisson distribution;primal-dual algorithm;Servers;Optimization;Hazards;Content management;Bandwidth;Resource management;Content distribution networks}, doi={10.1109/INFOCOM.2019.8737407}, ISSN={}, month={April},}

Slides

[6] DeepCache: A Deep Learning Based Framework For Content Caching
Arvind Narayanan, Saurabh Verma, Eman Ramadan, Pariya Babaie, Zhi-Li Zhang
In Workshop on Network Meets AI & ML, SIGCOMM WKSHPS. NetAI 2018 Abstract

In this paper, we present DEEPCACHE a novel Framework for content caching, which can significantly boost cache performance. Our Framework is based on powerful deep recurrent neural network models. It comprises of two main components: i) Object Characteristics Predictor, which builds upon deep LSTM Encoder-Decoder model to predict the future characteristics of an object (such as object popularity) -- to the best of our knowledge, we are the first to propose LSTM Encoder-Decoder model for content caching; ii) a caching policy component, which accounts for predicted information of objects to make smart caching decisions. In our thorough experiments, we show that applying DEEPCACHE Framework to existing cache policies, such as LRU and k-LRU, significantly boosts the number of cache hits.

BibTeX

@inproceedings{Narayanan:2018:DDL:3229543.3229555, author = {Narayanan, Arvind and Verma, Saurabh and Ramadan, Eman and Babaie, Pariya and Zhang, Zhi-Li}, title = {DeepCache: A Deep Learning Based Framework For Content Caching}, booktitle = {Proceedings of the 2018 Workshop on Network Meets AI \& ML}, series = {NetAI'18}, year = {2018}, isbn = {978-1-4503-5911-5}, location = {Budapest, Hungary}, pages = {48--53}, numpages = {6}, url = {http://doi.acm.org/10.1145/3229543.3229555}, doi = {10.1145/3229543.3229555}, acmid = {3229555}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {DeepCache, cache hit, caching, deep learning, fake requests, lstm, machine learning, popularity prediction, prefetching, proactive caching, seq2seq, smart caching policies, video object caches}, }

Slides Code Best Paper Award

[7] A Framework for Evaluating Caching Policies in a Hierarchical Network of Caches
Eman Ramadan, Pariya Babaie, Zhi-Li Zhang
In IFIP Networking Conference and Workshops. IFIP Networking 2018 Abstract

Much attention of the research community has focused on performance analysis of cache networks under various caching policies. However, the issue of how to evaluate and compare caching policies for cache networks has not been adequately addressed. In this paper, we propose a novel and general framework for evaluating caching policies in a hierarchical network of caches. We introduce the notion of a hit probability/rate matrix, and employ a generalized notion of majorization as the basic tool for evaluating caching policies for various performance metrics. We discuss how the framework can be applied to existing caching policies, and conduct extensive simulation-based evaluation to demonstrate the utility and accuracy of our framework.

BibTeX

@INPROCEEDINGS{8697030, author={E. {Ramadan} and P. {Babaie} and Z. {Zhang}}, booktitle={2018 IFIP Networking Conference (IFIP Networking) and Workshops}, title={A Framework for Evaluating Caching Policies in A Hierarchical Network of Caches}, year={2018}, volume={}, number={}, pages={1-9}, keywords={cache storage;performance evaluation;cache networks;caching policies;Servers;Performance analysis;Tools;Measurement;Network topology;Topology}, doi={10.23919/IFIPNetworking.2018.8697030}, ISSN={}, month={May},}

Slides

[8] OpenCDN: An ICN-based Open Content Distribution System Using Distributed Actor Model
Arvind Narayanan, Eman Ramadan, Zhi-Li Zhang
In IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IECCO 2018 Abstract

Building upon the results of recent works on understanding large-scale content distribution systems, we revisit CONIA, a Content-provider Oriented Namespace Independent Architecture for content delivery. The key idea of CONIA is to let any willing ISP or third party to participate as a content distribution network (CDN). In this paper, we propose a first step in the direction of an information-centric network-based open content distribution system (OpenCDN), that allows for better scalability, flexibility, and performance. In particular, we concentrate on the functions of the content store and routing elements (CSRs) that form the network substrate. We propose an actor-model driven programming model and a runtime system, which together we refer to as the OpenCDN platform. Using OpenCDN, content providers will have full control over building and managing the basic building blocks for the functionality of CSRs, and the flexibility on which content to cache, when to cache, and how to satisfy user requests.

BibTeX

@INPROCEEDINGS{8406937, author={A. {Narayanan} and E. {Ramadan} and Z. {Zhang}}, booktitle={IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, title={OpenCDN: An ICN-based open content distribution system using distributed actor model}, year={2018}, volume={}, number={}, pages={268-273}, keywords={content management;Internet;telecommunication network routing;content providers;ICN-based open content distribution system;large-scale content distribution systems;CONIA;Content-provider Oriented Namespace Independent Architecture;content delivery;content distribution network;information-centric network-based open content distribution system;network substrate;actor-model driven programming model;runtime system;OpenCDN platform;distributed actor model;content store and routing elements;Computer architecture;Servers;Load modeling;Conferences;Computational modeling;Substrates;Programming}, doi={10.1109/INFCOMW.2018.8406937}, ISSN={}, month={April},}

Slides

[9] When Raft Meets SDN: How to Elect a Leader and Reach Consensus in an Unruly Network
Yang Zhang, Eman Ramadan, Hesham Mekky, Zhi-Li Zhang
In Asia-Pacific Workshop on Networking. APNet 2017 Abstract

In SDN, the logically centralized control plane ("network OS") is often realized via multiple SDN controllers for scalability and reliability. ONOS is such an example, where it employs Raft -- a new consensus protocol developed recently -- for state replication and consistency among the distributed SDN controllers. The reliance of network OS on consensus protocols to maintain consistent network state introduces an intricate inter-dependency between the network OS and the network under its control, thereby creating new kinds of fault scenarios or instabilities. In this paper, we use Raft to illustrate the problems that this inter-dependency may introduce in the design of distributed SDN controllers and discuss possible solutions to circumvent these issues.

BibTeX

@inproceedings{Zhang:2017:RMS:3106989.3106999, author = {Zhang, Yang and Ramadan, Eman and Mekky, Hesham and Zhang, Zhi-Li}, title = {When Raft Meets SDN: How to Elect a Leader and Reach Consensus in an Unruly Network}, booktitle = {Proceedings of the First Asia-Pacific Workshop on Networking}, series = {APNet'17}, year = {2017}, isbn = {978-1-4503-5244-4}, location = {Hong Kong, China}, pages = {1--7}, numpages = {7}, url = {http://doi.acm.org/10.1145/3106989.3106999}, doi = {10.1145/3106989.3106999}, acmid = {3106999}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {Consensus, Raft Algorithm, Resilient Routing, SDN}, }

Slides Best Paper Award

[10] BIG Cache Abstraction for Cache Networks
Eman Ramadan, Arvind Narayanan, Zhi-Li Zhang, Runhui Li, Gong Zhang
In The 37th IEEE International Conference on Distributed Computing Systems. ICDCS 2017 Abstract

In this paper, we advocate the notion of "BIG" cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The "BIG" cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of "BIG" cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of "BIG" cache abstraction.

BibTeX

@INPROCEEDINGS{7980017, author={E. {Ramadan} and A. {Narayanan} and Z. {Zhang} and R. {Li} and G. {Zhang}}, booktitle={2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)}, title={BIG Cache Abstraction for Cache Networks}, year={2017}, volume={}, number={}, pages={742-752}, keywords={cache storage;network servers;big cache abstraction;cache networks;distributed storage;hierarchical network;cache servers;cache resources;intermediate servers;classical cache replacement policy;LRU;dCLIMB cache algorithm;moving object overheads;distributed cache boundaries;cache allotment problem;Servers;Cache storage;Bandwidth;Algorithm design and analysis;Streaming media;Resource management;Standards;Caching;Hierarchical Caching;Content Network Distribution;Cache Replacement Policies;BIG Cache;dCLIMB}, doi={10.1109/ICDCS.2017.306}, ISSN={}, month={June},}

Slides

[11] Adaptive Resilient Routing via Preorders in SDN
Eman Ramadan, Hesham Mekky, Braulio Dumba, Zhi-Li Zhang
In Workshop on Distributed Cloud Computing. DCC 2016 Abstract

In this paper, we propose and advocate a new routing paradigm -- dubbed routing via preorders -- which circumvents the limitations of conventional path-based routing schemes to effectively take advantage of topological diversity inherent in a network with rich topology for adaptive resilient routing, while at the same time meeting the quality-of-service requirements (e.g., latency) of applications or flows. We show how routing via preorders can be realized in SDN networks using the "match-action" data plane abstraction, with a preliminary implementation and evaluation of it in Mininet.

BibTeX

@inproceedings{Ramadan:2016:ARR:2955193.2955204, author = {Ramadan, Eman and Mekky, Hesham and Dumba, Braulio and Zhang, Zhi-Li}, title = {Adaptive Resilient Routing via Preorders in SDN}, booktitle = {Proceedings of the 4th Workshop on Distributed Cloud Computing}, series = {DCC '16}, year = {2016}, isbn = {978-1-4503-4220-9}, location = {Chicago, Illinois}, pages = {5:1--5:6}, articleno = {5}, numpages = {6}, url = {http://doi.acm.org/10.1145/2955193.2955204}, doi = {10.1145/2955193.2955204}, acmid = {2955204}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {OpenFlow, adaptive resilient routing, network failures, routing via preorders, software-defined networking}, }

Slides

[12] Adaptive Resilient Routing via Preorders in SDN
Eman Ramadan, Hesham Mekky, Braulio Dumba, Zhi-Li Zhang
AT&T Labs SDN Summit. 2016 poster

[13] CONIA: Content (provider)-Oriented, Namespace-Independent Architecture for Multimedia Information Delivery
Eman Ramadan, Arvind Narayanan, Zhi-Li Zhang
In Workshop on Multimedia & Expo. ICMEW 2015 Abstract

We propose and present CONIA, a novel content (provider)-oriented, namespace-independent architecture for multimedia information delivery. CONIA is designed specifically to account for the diversity and complexity of multimedia content, and to recognize the prominent roles of content providers (CPs) in the network economics of content delivery. In this paper, we provide an overview of the content delivery architecture of CONIA and outline the basic functions of its key components. Using several use cases, we illustrate the flexibility of CONIA in allowing for CPs to employ various control policies to dynamically handle user demands and meet users' quality-of-experience expectations.

BibTeX

@INPROCEEDINGS{7169811, author={E. {Ramadan} and A. {Narayanan} and Z. {Zhang}}, booktitle={2015 IEEE International Conference on Multimedia Expo Workshops (ICMEW)}, title={CONIA: Content (provider)-oriented, namespace-independent architecture for multimedia information delivery}, year={2015}, volume={}, number={}, pages={1-6}, keywords={content management;Internet;multimedia computing;object-oriented methods;quality of experience;CONIA;content oriented namespace-independent architecture;multimedia information delivery;multimedia content complexity;content provider network economics;content delivery architecture;quality-of-experience expectation;Context;Multimedia communication;Substrates;Streaming media;Bandwidth;Internet;Routing}, doi={10.1109/ICMEW.2015.7169811}, ISSN={}, month={June},}

Slides

[14] OpenCDN: Towards Software Defined Content Distribution Networks
Eman Ramadan, Arvind Narayanan, Zhi-Li Zhang
The Third GENI Research and Educational Experiment Summer Camp. GREE-SC 2014
The Fourth Networking Networking Women Workshop - N2Women: Broadening Participation. N2Women 2014 poster


Education

Ph.D. Computer Science Present
University of Minnesota Minneapolis, MN, USA
M.Sc. Computer Engineering 2012
Alexandria University Alexandria, Egypt
B.Sc. Computer Engineering 2008
Alexandria University Alexandria, Egypt

Research

University of Minnesota Minneapolis, MN, USA
Research Assistant Present
Futurewei Technologies, Inc. Santa Clara, CA
Research Intern Fall 2016
Huawei Technologies, Inc. Hong Kong
Research Intern Summer 2016
Bell-Labs/Alcatel-Lucent Stuttgart, Germany
Research Intern Summer 2013
Alexandria University Alexandria, Egypt
Graduate Research Assistant Fall 2009 - Fall 2010

Work

Google Inc. Zurich, Switzerland
Software Engineering Intern Summer 2011
Ejada Systems Alexandria, Egypt
Software Engineer Fall 2008 - Summer 2009

Teaching

Co-Instructor at the University of Minnesota Minneapolis, MN, USA
Csci 4211: Introduction to Computer Networks Fall 2017
Research Assistant at the University of Minnesota Minneapolis, MN, USA
Csci 1902: Structure of Computer Programming II Fall 2012 - Spring 2013
Alexandria University Alexandria, Egypt
Microprocessor Systems, Introduction to Programming
Structural Programming using C and Introduction to C++,
Digital Fundamentals, and Software Engineering.
Fall 2008 - Spring 2012

Awards

Awarded ACM’s Student Research Competition (SRC) travel grant to attend Grace Hopper Celebration 2018.
Best paper award for our paper "DeepCache" SIGCOMM NetAIM workshop 2018.
Best paper award for our paper "When Raft Meets SDN" APNet workshop 2017.
Awarded the travel grant to attend GENI NICE (co-located with CoNEXT) 2016.
Awarded the N2Women travel grant to attend SIGCOMM 2014 and N2Women Workshop.
Awarded the travel grant to attend GENI Summer Camp 2014.
Awarded the CRA-W grant to attend the Graduate Cohort Workshop 2014.
Awarded the Arab Women in Computing (AWIC) grant to attend the Grace Hopper Conference 2013.
Google Anita Borg EMEA Scholarship Finalist in 2010.
Received faculty award for Graduation Project in 2008.
Dean's List of Distinguished Students in undergraduate study.

Activities

Computer Science and Engineering CS&E Grad Coordinator for Inclusiveness, Diversity, Equity, and Advocacy since Fall 2020.
A member of the Computer Science and Engineering Committee CS-IDEA for Inclusiveness, Diversity, Equity, and Advocacy since Fall 2019.
Volunteer at Feed My Starving Children charity organization since 2019.
The social coordinator for the Computer Science Graduate Student Association CSGSA Fall 2018 - Summer 2020.
Volunteered as a panelist for the CS UMN department's Visit Day event for prospective graduate students in 2019.
Volunteered at the CS UMN department's Visit Day event for prospective graduate students in 2018.
A graduate mentor volunteer for UMN CSE WISE Undergrad-Grad Mentor program Fall 2017 - Spring 2019.
Volunteered at Summer Tech Camp for primary school kids in 2014.


Office:

Walter Library
117 Pleasant St SE, Suite 488
Minneapolis, MN 55455

Email:
eman AT cs DOT umn DOT edu

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