sosp2011 socc2011 plos2011 Report
23rd ACM Symposium on Operating Systems Principles (SOSP)October 23-26, 2011, Cascais, Portugal
http://sosp2011.gsd.inesc-id.pt/
2nd ACM Symposium on Cloud Computing October 26-28, 2011, Cascais, Portugal
http://socc2011.gsd.inesc-id.pt/
6th Workshop on Programming Languages and Operating Systems, October 23, 2011, Cascais, Portugal
http://plosworkshop.org/2011/
Titie: Rethink Package Components on De-Duplication: From Logical Sharing to Physical Sharing
URL: http://events.linuxfoundation.org/2010/linuxcon-japan/suzaki
Abstract: inux distributions include many logical sharing techniques (shared library, symbolic link, etc) on memory and storage. Unfortunately they cause security and management problems, such as GOT (Global Offset Table) overwrite attack, TOCTTOU (Time Of Check To Time Of Use) attack, Dependency hell, etc. In order to mitigate the problems, we propose the replacement of logical sharing by physical sharing (memory and disk deduplication; e.g., KSM: Kernel Samepage Merging, Content Addressable Storage, etc). Original ELF binaries are transformed as self-contained binaries which include dynamic linked shared libraries as “pseudo-static”. The binaries become fat but physical resource usage is mitigated by deduplication. We have investigated the effect on Debian and Ubuntu and confirmed that the physical impact is low. Data centers of Cloud Computing utilize the deduplication techniques. Users and administrators should consider Linux images in terms of security and maintenance, and the usage of deduplicated fat binaries.
Titie: Rethink Package Components on De-Duplication: From Logical Sharing to Physical Sharing
URL: http://events.linuxfoundation.org/2010/linuxcon-japan/suzaki
Abstract: inux distributions include many logical sharing techniques (shared library, symbolic link, etc) on memory and storage. Unfortunately they cause security and management problems, such as GOT (Global Offset Table) overwrite attack, TOCTTOU (Time Of Check To Time Of Use) attack, Dependency hell, etc. In order to mitigate the problems, we propose the replacement of logical sharing by physical sharing (memory and disk deduplication; e.g., KSM: Kernel Samepage Merging, Content Addressable Storage, etc). Original ELF binaries are transformed as self-contained binaries which include dynamic linked shared libraries as “pseudo-static”. The binaries become fat but physical resource usage is mitigated by deduplication. We have investigated the effect on Debian and Ubuntu and confirmed that the physical impact is low. Data centers of Cloud Computing utilize the deduplication techniques. Users and administrators should consider Linux images in terms of security and maintenance, and the usage of deduplicated fat binaries.
Why Neurons have thousands of synapses? A model of sequence memory in the brainNumenta
Presentation given by Yuwei Cui, Numenta Research Engineer at Beijing Normal University. December 2015.
Collaborators: Jeff Hawkins, Subutai Ahmad, Chetan Surpur
Keynote presentation at GlobusWorld 2021. Highlights product updates and roadmap, as well as user success stories in research data management. Presented by Ian Foster, Rachana Ananthakrishnan, Kyle Chard and Vas Vasiliadis.
A description of software as infrastructure at NSF, and how Apache projects may be similar. What lessons can be shared from one organization to the other? How does science software compare with more general software?
Thoughts on Knowledge Graphs & Deeper ProvenancePaul Groth
Thinking about the need for deeper provenance for knowledge graphs but also using knowledge graphs to enrich provenance. Presented at https://seminariomirianandres.unirioja.es/sw19/
This talk describes our experiences from hosting scientific research application in the Microsoft Cloud. Covers an overview of Microsoft Azure capabilities, examples of big data analysis for science, data collections, science gateways and science virtual machine libraries.
Classification of Big Data Use Cases by different FacetsGeoffrey Fox
Ogres classify Big Data applications by multiple facets – each with several exemplars and features. This gives a
guide to breadth and depth of Big Data and allows one to examine which ogres a particular architecture/software support.
The Discovery Cloud: Accelerating Science via Outsourcing and AutomationIan Foster
Director's Colloquium at Los Alamos National Laboratory, September 18, 2014.
We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to leverage the “cloud” (whether private or public) to achieve economies of scale and reduce cognitive load. In this talk, I explore the past, current, and potential future of large-scale outsourcing and automation for science.
The Entity Registry System @ Verisign Labs, 2013eXascale Infolab
Talk on the Entity Registry System (ERS)
Verisign Headquarters, Distinguished Speakers Series
https://www.verisigninc.com/en_US/why-verisign/innovation-initiatives/labs/news/distinguished-speaker-series/advancing-technologies/index.xhtml
http://iswc2013.semanticweb.org/sites/default/files/iswc_demo_4.pdf
https://github.com/ers-devs
Accelerating Discovery via Science ServicesIan Foster
[A talk presented at Oak Ridge National Laboratory on October 15, 2015]
We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In big-science projects in high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to develop suites of science services to which researchers can dispatch mundane but time-consuming tasks, and thus to achieve economies of scale and reduce cognitive load. I explore the past, current, and potential future of large-scale outsourcing and automation for science, and suggest opportunities and challenges for today’s researchers. I use examples from Globus and other projects to demonstrate what can be achieved.
JD McCreary Presentation to Williams Foundation, March 22, 2018ICSA, LLC
JD McCreary, Chief, Disruptive Technology Programs, Georgia Tech Research Institute, focused on the centrality of effective decision making in high intensity conflict and on leveraging technologies like artificial intelligence to do so much more effectively.
NumPyCNNAndroid: A Library for Straightforward Implementation of Convolutiona...Ahmed Gad
The presentation of my paper titled "#NumPyCNNAndroid: A Library for Straightforward Implementation of #ConvolutionalNeuralNetworks for #Android Devices" at the second International Conference of Innovative Trends in #ComputerEngineering (ITCE 2019).
The paper proposes a library for implementing convolutional neural networks (CNNs) in order to run on Android devices. The process of running the CNN on the mobile devices is straightforward and does not require an in-between step for model conversion as it uses #Kivy cross-platform library.
The CNN layers are implemented in #NumPy. You can find their implementation in my #GitHub project at this link: https://github.com/ahmedfgad/NumPyCNN
The library is also open source available here: https://github.com/ahmedfgad/NumPyCNNAndroid
There are 2 modes of operation for this work. The first one is training the CNN on the mobile device but it is very time-consuming at least in the current version. The second and preferred way is to train the CNN in a desktop computer and then use it on the mobile device.
Why Neurons have thousands of synapses? A model of sequence memory in the brainNumenta
Presentation given by Yuwei Cui, Numenta Research Engineer at Beijing Normal University. December 2015.
Collaborators: Jeff Hawkins, Subutai Ahmad, Chetan Surpur
Keynote presentation at GlobusWorld 2021. Highlights product updates and roadmap, as well as user success stories in research data management. Presented by Ian Foster, Rachana Ananthakrishnan, Kyle Chard and Vas Vasiliadis.
A description of software as infrastructure at NSF, and how Apache projects may be similar. What lessons can be shared from one organization to the other? How does science software compare with more general software?
Thoughts on Knowledge Graphs & Deeper ProvenancePaul Groth
Thinking about the need for deeper provenance for knowledge graphs but also using knowledge graphs to enrich provenance. Presented at https://seminariomirianandres.unirioja.es/sw19/
This talk describes our experiences from hosting scientific research application in the Microsoft Cloud. Covers an overview of Microsoft Azure capabilities, examples of big data analysis for science, data collections, science gateways and science virtual machine libraries.
Classification of Big Data Use Cases by different FacetsGeoffrey Fox
Ogres classify Big Data applications by multiple facets – each with several exemplars and features. This gives a
guide to breadth and depth of Big Data and allows one to examine which ogres a particular architecture/software support.
The Discovery Cloud: Accelerating Science via Outsourcing and AutomationIan Foster
Director's Colloquium at Los Alamos National Laboratory, September 18, 2014.
We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to leverage the “cloud” (whether private or public) to achieve economies of scale and reduce cognitive load. In this talk, I explore the past, current, and potential future of large-scale outsourcing and automation for science.
The Entity Registry System @ Verisign Labs, 2013eXascale Infolab
Talk on the Entity Registry System (ERS)
Verisign Headquarters, Distinguished Speakers Series
https://www.verisigninc.com/en_US/why-verisign/innovation-initiatives/labs/news/distinguished-speaker-series/advancing-technologies/index.xhtml
http://iswc2013.semanticweb.org/sites/default/files/iswc_demo_4.pdf
https://github.com/ers-devs
Accelerating Discovery via Science ServicesIan Foster
[A talk presented at Oak Ridge National Laboratory on October 15, 2015]
We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In big-science projects in high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to develop suites of science services to which researchers can dispatch mundane but time-consuming tasks, and thus to achieve economies of scale and reduce cognitive load. I explore the past, current, and potential future of large-scale outsourcing and automation for science, and suggest opportunities and challenges for today’s researchers. I use examples from Globus and other projects to demonstrate what can be achieved.
JD McCreary Presentation to Williams Foundation, March 22, 2018ICSA, LLC
JD McCreary, Chief, Disruptive Technology Programs, Georgia Tech Research Institute, focused on the centrality of effective decision making in high intensity conflict and on leveraging technologies like artificial intelligence to do so much more effectively.
NumPyCNNAndroid: A Library for Straightforward Implementation of Convolutiona...Ahmed Gad
The presentation of my paper titled "#NumPyCNNAndroid: A Library for Straightforward Implementation of #ConvolutionalNeuralNetworks for #Android Devices" at the second International Conference of Innovative Trends in #ComputerEngineering (ITCE 2019).
The paper proposes a library for implementing convolutional neural networks (CNNs) in order to run on Android devices. The process of running the CNN on the mobile devices is straightforward and does not require an in-between step for model conversion as it uses #Kivy cross-platform library.
The CNN layers are implemented in #NumPy. You can find their implementation in my #GitHub project at this link: https://github.com/ahmedfgad/NumPyCNN
The library is also open source available here: https://github.com/ahmedfgad/NumPyCNNAndroid
There are 2 modes of operation for this work. The first one is training the CNN on the mobile device but it is very time-consuming at least in the current version. The second and preferred way is to train the CNN in a desktop computer and then use it on the mobile device.
ACSAC2020 "Return-Oriented IoT" by Kuniyasu SuzakiKuniyasu Suzaki
Side of "Reboot-Oriented IoT: Life Cycle Management in Trusted Execution Environment for Disposable IoT devices" ACSAC (Annual Computer Security Applications Conference) 2020
Kernel Memory Protection by an Insertable Hypervisor which has VM Introspec...Kuniyasu Suzaki
IWSEC2014(The 9th International Workshop on Security 弘前) で"Kernel Memory Protection by an Insertable Hypervisor which has VM Introspection and Stealth Breakpoints"
USENIX OSDI 2012 Poster "Nested Virtual Machines and Proxies for Easily Implementable Rollback of Secure Communication" by Kuniyasu Suzaki, Kengo Iijima, Akira Tanaka, and Yutaka Oiwa, AIST: National Institute of Advanced Industrial Science and Technology; Etsuya Shibayama, The University of Tokyo
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
2. SOSP2011概要
• 23rd ACM Symposium on Operating Systems Principles (SOSP)
October 23-26, 2011, Cascais, Portugal
– http://sosp2011.gsd.inesc-id.pt/
– 論文&スライド&ビデオ http://sigops.org/sosp/sosp11/current/index.html
– 1colum(screen)と2colums(print)の論文があり。便利だが、screen版が作りが甘い
– 170投稿、26採択。
– 参加者540(今まで最高。そのうちStudentsが220)
– Best Paper 2本
• ColumbiaのCells: A Virtual Mobile Smartphone Architecture
• Wisconsin, MadisonのA File is Not a File: Understanding the I/O Behavior
of Apple Desktop Applications
– ポスター30(投稿50) 。日本から1件(産総研) (最終版投稿にshepherdが付く)
– WIP 17(投稿48)
– 次回は中国?
• ワークショップ
– SLAML - Managing Large-Scale Systems via the Analysis of System Logs and
the Application of Machine Learning Techniques
– PLOS - 6th Workshop on Programming Languages and Operating Systems
– MobiHeld - 3rd ACM SOSP Workshop on Networking, Systems, and
Applications on Mobile Handhelds
– HotPower - 4th Workshop on Power-Aware Computing and Systems
3. プログラム1日目 午前 1/2
• Key-Value Chair: Marvin Theimer
– SILT: A Memory-Efficient, High-Performance
Key-Value Store
• Hyeontaek Lim, Bin Fan, David G. Andersen (CMU), Michael Kaminsky (Intel Labs)
• 小メモリを特徴とするKVS。 ソースコード https://github.com/silt/silt/
• Memory Efficiency (FAWN[OSDI09], FlashStore[VLDB10], BUfferHash[NDSI10],
HashCache[NSDI09]) VS High performance (SkimpyStash[SIGMOD11])
– Scalable Consistency in Scatter
• Lisa Glendenning, Ivan Beschastnikh, Arvind Krishnamurthy, Thomas Anderson (University of Washington)
• CcalabilityとConsistencyを両立するScatterの提案。Consistencyの使い方を突っ込まれていた。
– Fast Crash Recovery in RAMCloud
• Diego Ongaro, Stephen M. Rumble, Ryan Stutsman, John Ousterhout, Mendel Rosenblum (Stanford)
• RAMの問題はPower Failure。ディスクからの高速リカバリが課題。3つのディスクコピーをScatter log
Data(各8MB) として保存。これからPartitioned Recovery する。
4. プログラム1日目 午前 2/2
• Storage Chair: Eddie Kohler
– Design Implications for Enterprise Storage Systems via Multi-Dimensional
Trace Analysis
• Yanpei Chen (UC Berkeley), Kiran Srinivasan, Garth Goodson (NetApp), Randy Katz (UC
Berkeley)
• 16種類のdimension (Total IO size , Read/Write, request, average time between IO, read/write
sequence, etc)で解析。
• 70%以上がシーケンシャルread/wireアクセス。 I/Oのタイプで.xls, .ppt, .doc, .dpfなどのファイルが推定
できる。
• NTTでもiSCSI経由で振る舞い解析からファイルタイプを推定する特許があるらしい。
– Differentiated Storage Services
g
• Michael Mesnier, Jason B. Akers, Feng Chen (Intel), Tian Luo (Ohio State)
• ディスクはSSDにキャッシュされるようになったが、大きなシーケンシャルファイルアクセスはキャッシュを
バイパスさせる。ファイルシステムにこの機能を持たせる。
– (Best Paper)A File is Not a File: Understanding the I/O Behavior of Apple
Desktop Applications (詳細後述)
• Tyler Harter, Chris Dragga, Michael Vaughn, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau (University of
Wisconsin, Madison)
5. プログラム1日目 午後
• Security Chair: Adrian Perrig
– CryptDB: Protecting Confidentiality with Encrypted Query Processing
• Raluca Ada Popa, Catherine M. S. Redfield, Nickolai Zeldovich, Hari Balakrishnan (MIT)
– Intrusion Recovery for Database-backed Web Applications
• Ramesh Chandra, Taesoo Kim, Meelap Shah, Neha Narula, Nickolai Zeldovich (MIT)
– Software fault isolation with API integrity and multi-principal modules
• Yandong Mao, Haogang Chen (MIT), Dong Zhou (Tsinghua), Xi Wang, Nickolai Zeldovich, M. Frans Kaashoek (MIT)
• カーネルモジュールを守るLXFIの提案。XFI[OSDI06]、BGI[SOSP09]からinspire。 APIは悪用される可
能性がある。Annotation langで記述 LXFIがコンパイル時にrun time コードを埋め込む。
• Reality Chair: George Candea
y g
– Thialfi: A Client Notification Service for Internet-Scale Applications
• Atul Adya, Gregory Cooper, Daniel Myers, Michael Piatek (Google)
– Windows Azure Storage: A Highly Available Cloud Storage Service with
Strong Consistency
• Brad Calder, Ju Wang, Aaron Ogus, Niranjan Nilakantan, Arild Skjolsvold, Sam McKelvie, Yikang Xu, Shashwat Srivastav, Jiesheng
Wu, Huseyin Simitci, Jaidev Haridas, Chakravarthy Uddaraju, Hemal Khatri, Andrew Edwards, Vaman Bedekar, Shane Mainali,
Rafay Abbasi, Arpit Agarwal, Mian Fahim ul Haq, Muhammad Ikram ul Haq, Deepali Bhardwaj, Sowmya Dayanand, Anitha
Adusumilli, Marvin McNett, Sriram Sankaran, Kavitha Manivannan, Leonidas Rigas (Microsoft)
– An Empirical Study on Configuration Errors in Commercial and Open
Source Systems
• Zuoning Yin, Xiao Ma (UIUC), Jing Zheng, Yuanyuan Zhou (UCSD), Lakshmi N. Bairavasundaram, Shankar
Pasupathy (NetApp)
• Posters (発表詳細後述)
6. プログラム2日目 午前 1/2
• Virtualization Chair: Gernot Heiser
– (Best Paper) Cells: A Virtual Mobile Smartphone Architecture
• Jeremy Andrus, Christoffer Dall, Alex Van’t Hof, Oren Laadan, Jason Nieh (Columbia)
• Smart Phoneの仮想化。オーバーヘッド2%。ベンチャー創業 http://www.cellrox.com/
– Breaking Up is Hard to Do: Security and Functionality in a Commodity
Hypervisor (詳細後述)
• Patrick Colp, Mihir Nanavati (UBC), Jun Zhu (Citrix), William Aiello (UBC), George Coker (NSA), Tim Deegan
(Citrix), Peter Loscocco (NSA), Andrew Warfield (UBC)
– CloudVisor: Retrofitting Protection of Virtual Machines in Multi-tenant
Cloud with Nested Virtualization (詳細後述)
• Fengzhe Zhang, Jin Chen, Haibo Chen, Binyu Zang (Fudan University)
– (Audience Choice) Atlantis: Robust, Extensible Execution Environments for
Web Applications
• James Mickens (MSR), Mohan Dhawan (Rutgers)
• 関連研究。 Illinois Browser Operating System (IBOS) [OSDI10], OP[SS&`P08]
7. プログラム2日目 午前 2/2
• OS Architecture Chair: Nickolai Zeldovich
– PTask: Operating System Abstractions To Manage GPUs as Compute
Devices
• Christopher J. Rossbach, Jon Currey (MSR), Mark Silberstein (Technion), Baishakhi Ray, Emmett Witchel (UT
Austin)
• CPUのロードの割合がGPUの性能に影響する。逆も同様。
• GPUスケジューリングを抽象化するPtask (Parallel Task)。 data flowを抽象化。Fairnessのために
priorityあり。通常のフィルタとインターフェースとできる。
• 例:#> capture(process) | xform(ptask) | filer (ptask)
– Logical Attestation: An Authorization Architecture for Trustworthy
Computing
C ti
• Emin Gün Sirer (Cornell), Willem de Bruijn (Google), Patrick Reynolds (BlueStripe Software), Alan Shieh, Kevin
Walsh, Dan Williams, Fred B. Schneider (Cornell)
• Trusted Computingの話。
• Cornellで作っているlogical attestationに対応するOSはNexusと言う。 NexusのMicro kernel 自体に
Introspection の機能がある。 NexusにはFauxbook と言うprivacy-preserving social networkが入って
いる。
8. プログラム2日目 午後
• Detection and Tracing Chair: Rebecca Isaacs
– Practical Software Model Checking via Dynamic Interface Reduction
• Huayang Guo (MSR and Tsinghua), Ming Wu, Lidong Zhou (MSR), Gang Hu (MSR and Tsinghua), Junfeng Yang
(Columbia), Lintao Zhang (MSR)
– Detecting failures in distributed systems with the FALCON spy network
• Joshua B. Leners, Hao Wu, Wei-Lun Hung (UT Austin), Marcos K. Aguilera (MSR), Michael Walfish (UT Austin)
– Secure Network Provenance
• Wenchao Zhou, Qiong Fei, Arjun Narayan, Andreas Haeberlen, Boon Thau Loo (University of Pennsylvania), Micah
Sherr (Georgetown University)
– Fay: Extensible Distributed Tracing from Kernels to Clusters
• Úlfar Erlingsson (G
Úlf E li (Google), M
l ) Marcus P i d (MSR) Si
Peinado (MSR), Simon P
Peter (ETH Zürich), Mih i B di (MSR)
Zü i h) Mihai Budiu
• Work in Progress
– 48 submissions, 17 accepted. 一人4分。
– ASPLOS11 で発表されたDoublePlayの拡張
– Paxosに対抗するIsis^2 http://www.cs.cornell.edu/ken/
– PROobE (Parallel Reconfigurable Observational Environment) http://newmexicoconsortium.org/probe
9. プログラム3日目 午前
• Threads and Races Chair: Bryan Ford
– Dthreads: Efficient Deterministic Multithreading
• Tongping Liu, Charlie Curtsinger, Emery D. Berger (UMass Amherst)
– Efficient Deterministic Multithreading through Schedule Relaxation
• Heming Cui, Jingyue Wu, John Gallagher, Huayang Guo, Junfeng Yang (Columbia)
– Pervasive Detection of Process Races in Deployed Systems
• Oren Laadan, Nicolas Viennot, Chia-che Tsai, Chris Blinn, Junfeng Yang, Jason Nieh (Columbia)
– Detecting and Surviving Data Races using Complementary Schedules
• Kaushik Veeraraghavan, Peter M. Chen, Jason Flinn, Satish Narayanasamy (University of Michigan)
• ASPLOS11でDoublePlay を発表した人
で y
• Geo-Replication Chair: Ant Rowstron
– Transactional storage for geo-replicated systems
• Yair Sovran, Russell Power (NYU), Marcos K. Aguilera (MSR), Jinyang Li (NYU)
– Don’t Settle for Eventual: Scalable Causal Consistency for Wide-Area
Storage with COPS
• Wyatt Lloyd, Michael J. Freedman (Princeton), Michael Kaminsky (Intel Labs), David G. Andersen (CMU)
10. A File is Not a File: Understanding the I/O Behavior of Apple
Desktop Applications (Best Paper)
Tyler Harter, Chris Dragga, Michael Vaughn, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-
Dusseau (University of Wisconsin, Madison)
• ホームユーザアプリケーション(MaxOS X対象)は、UNIX流の
単純なアプリケーションとは異なり、大規模で複雑。解析するた
めにiBenchを提案。
– http://research.cs.wisc.edu/adsl/Traces/ibench/
• Case Study
– Pages 4.0.3(Apple s iWork suite)によるDOCフォーマット文書ファイル
4 0 3(Apple’s
作成。Insert 15 JPEG images (each ~2.5MB)
• 1docファイルの為に385 files
– 218 KV store files + 2 SQLite files: Personalized behavior (recently used lists, settings, etc)
– 118 multimedia files: Rich graphical experience
– 25 Strings files: Language localization
– 17 Other files: Auto-save file and others
• docファイル中にはディレクトリをもつ。(Document, Data, Table, Ministream)。
• 11 threads で実行
• fsync とrenameを多用した更新
– シーケンシャルアクセスしたつもりでもシーケンシャルになっていない
• FATではヘッダを更新した後に、各データストリームがフラグメント化されて保存
11. Th
hreads
Files
s
fsyncと
rename
の多用 small I/O
次スライド big I/O
で拡大
fsync
rename
13. A File is Not a File: Understanding the I/O Behavior of Apple
Desktop Applications (Best Paper)
Tyler Harter, Chris Dragga, Michael Vaughn, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-
Dusseau (University of Wisconsin, Madison)
• 何故アプリケーションが大きくなるのか。
– 現在は開発環境による開発が主流
– Cocoa を使うと 689 のファイルから112,047行が取り込まれる
– 多言語対応も自動的に行われるが、多くのファイルが自動的に含まれる
• ホームユーザアプリケーションを解析するためにiBenchを提案
– iPhoto, iTunes, iMovie,Pages, Numbers, and Keynoteを組み合わせ
たBenchmark Suite
– AppleScriptによるUIのプログラミング
– Dtraceにsystem callの収集
• iTunesはptraceを使ってしまっているので、gdbを使って回避。
– ファイルサイズごとに解析
• very small (< 4KB), small (< 64KB), medium (< 1MB), large (< 10MB), very large
(≥ 10MB).
14. CloudVisor: Retrofitting Protection of Virtual Machines in
Multi-tenant Cloud with Nested Virtualization
Fengzhe Zhang, Jin Chen, Haibo Chen, Binyu Zang (Fudan University)
• 現在のVMMは大規模でTCB(Trusted Computing
Base)と呼ぶには大きすぎる。
• VMMの脆弱性も多い
VMMの脆弱性も多い。
– 32 CVE on Xen, 35 CVE on VMware
• Cloud Operatorによる情報漏えいもある。
• Nested VirtualizationによりVMM(Xen)の下位に置き、
VMメモリイメージ、I/Oを暗号化し、VM間や管理OSな
どからの不正アクセスを禁止するCloudVisorの提案。
15. CloudVisor: Retrofitting Protection of Virtual Machines in
Multi-tenant Cloud with Nested Virtualization
Fengzhe Zhang, Jin Chen, Haibo Chen, Binyu Zang (Fudan University)
• CloudVisor 5.5K LOC。Intel CPUの機能をフルに使う
• VMM起動後に挿入
– Intel TXTを使ったlate launch。Xenの起動後に挿入できる。
• IOMMUを使ってDMA Attackを防ぐ
• EPT-v ReadOnlyによるVMMメモリの仮想化とメモリ保護
• VMexit の回数が増える
– VM read と VM writeをVMCSへのメモリアクセスとするパッチ
で回避
18. Breaking Up is Hard to Do: Security and Functionality in a
Commodity Hypervisor
Patrick Colp, Mihir Nanavati (UBC), Jun Zhu (Citrix), William Aiello (UBC), George Coker (NSA), Tim
Deegan (Citrix), Peter Loscocco (NSA), Andrew Warfield (UBC)
• 現在のVMM(Xen)は
– Monolithic Control VM を含めてTCB(Trusted Computing Base)が大きい
– Control VM はVMに対して多くのインターフェース
• 空間的、時間的にmodularity とisolationを高めたXoarの提案
Xoarの構成
既存のXen
21. Poster
• 30(投稿50本) 最終版投稿にshepherdが付く
• Title: Software Side Channel Attack on Memory Deduplication
– 3 Referees: Weak Accept, Accept, Reject
– EuroSec2011で発表できなかったメモリ重複除外へのサイドチャネル攻撃
Normal Attacked
VM1(victim) VM2(attacker) VM1(victim) VM2(attacker) Write Access
Guest
Pseudo
Memory
Attacker knows the
Real page contents exist
Physical on victim VM.
Memory
Same-content pages
S t t When
Wh a write access is issued to the d d li
i i i d h deduplicated
d
on VMs are merged on pages, the access time is delayed, because the
real physical memory page are re-created by Copy-On-Write .
attacker’s program memory on attacker’s VM
matching
Un-control by
target file
… attacker’s program Page
Cache
open();
Contents stored
•Challenge for the attacker …
posix_memalign();
on page cache
read(); Heap
•Alignment of matching data … Contents stored on
heap memory
Same contents
are deduplicated
gettimeofday(); on self memory
•Self-reflection (explained to the right) // wrie data to heap
gettimeofday();
access time is delayed with self
memory deduplication
•Runtime modification
(swap-out, ASLR, anonymous page, matching target
file with gziped
attacker’s program memory on attacker’s VM
Un-control by
… attacker’s program
preloading, self-modifying code) gzopen();
Contents stored
Page
Cache
… on page cache different
posix_memalign(); contents
gzread();
Contents stored Heap
…
on heap memory
gettimeofday();
// write data to heap Deduplicated with
memory on other VM
gettimeofday();
23. SOCC2011概要
• 2nd ACM Symposium on Cloud Computing October 26-28, 2011, Cascais,
Portugal
– http://socc2011.gsd.inesc-id.pt/
– 採択論文 Long 24/136 (17%) short 6/42 (14%)
– 参加者194(昨年 208)
– 初日にTutorial 2本
• Amazon Web Services
• The Windows Azure Cloud Platform
– Keynote Speaker by Christopher Olston, Bionica Human Computing
y p y p p g
• Programming and Debugging Large-Scale Data Processing Workflows
– Hadoop MapReduce 用データフロー言語Pig、ワークフローマネージャNOVA、およ
びプログラミング環境の解説
• 異なる会議だがほぼ同じスライドを使っている。
• http://www.sfbayacm.org/wp/wp-content/uploads/2011/03/olston-slides.pdf
24. プログラム1日目 午前
• Virtual Infrastructure Chair: Amr El Abbadi
– Paper of Distinction! Pesto: Online Storage Performance
Management in Virtualized Datacenters [full paper]
• Ajay Gulati, Ganesha Shanmuganathan, and Irfan Ahmad (VMware, Inc.), Carl A.
Waldspurger (unaffiliated), and Mustafa Uysal (VMware, Inc.)
• データセンターのストレージパフォーマンスすシステム。
• PestoはCongestion management はPARDA[FAST09]ベース。I/O load
balancingによりデータの移動。Datastoreのremove/addあり。
– Improving Per-Node Efficiency in the Datacenter with New OS Abstractions [short
paper]
• Barret Rhoden, Kevin Klues, David Zhu, and Eric Brewer (UC Berkeley)
– Paper of Distinction! Opportunistic Flooding to Improve TCP Transmit
Performance in Virtualized Clouds [full paper]
• Sahan Gamage, Ardalan Kangarlou, Ramana Rao Kompella, and Dongyan Xu (Purdue University)
VMのコンテキストスイッチでRTTが悪くなる。ドライ
バドメインでOffload congestion controlするvFlood
を提案。類似研究 vSnoop [SC10]
packet lossがあった時はcongestion controlをVM
側に移す。
vFloodはXenのドライバドメインで実現。1500LOC。
Xen3.3 Linux.2.6.18 for driver domain
– Cuanta: Quantifying Effects of Shared On-chip Resource Interference for
Consolidated Virtual Machines [full paper]
• Sriram Govindan (The Pennsylvania State University), Jie Liu and Aman Kansal (Microsoft Research, Redmond), and
Anand Sivasubramaniam (The Pennsylvania State University)
25. プログラム1日目 午後 1/2
• Computation Chair: John Wilkes
– Orleans: Cloud Computing for Everyone [full paper]
• Sergey Bykov, Alan Geller, Gabriel Kliot, James R. Larus, Ravi Pandya, and Jorgen Thelin (Microsoft Research)
– Paper of Distinction! PrIter: A Distributed Framework for Prioritized Iterative
Computations [full paper]
• Yanfeng Zhang and Qixin Gao (Northeastern University, 中国), Lixin Gao (University of Massachusetts Amherst), and
Cuirong Wang (Northeastern University)
• MacPreduceの高速化。基本はIterative Computationのプライオリティを付けて、キューに
入れる。スレッシュホールドより大きいものから分散処理。Hadoopより50倍のスピードアップ。
• ソースコード http://code.google.com/p/priter/
– Making Time-stepped Applications Tick in the Cloud [full paper, regular
presentation]
• Tao Zou, Guozhang Wang, Marcos Vaz Salles, David Bindel, Alan Demers, Johannes Gehrke, and Walker White (Cornell
University)
– Scaling the Mobile Millennium System in the Cloud [short paper]
• Timothy Hunter, Teodor Moldovan, Matei Zaharia, and Justin Ma (UC Berkeley), Samy Merzgui (EPFL), and Justin Ma,
Michael Franklin, Pieter Abbeel, and Alexandre Bayen (UC Berkeley)
26. プログラム1日目 午後 2/2
• Data Centers etc Chair: Jeff Chase
– ALIAS: Scalable, Decentralized Label Assignment for Data Centers [full paper]
• Meg Walraed-Sullivan, Radhika Niranjan Mysore, and Malveeka Tewari (UCSD), Ying Zhang (Ericsson), and Keith Marzullo
and Amin Vahdat (UCSD)
– Small-World Datacenters [full paper]
• Ji-Yong Shin, Bernard Wong, and Emin Gun Sirer (Cornell University)
– Switching the Optical Divide: Fundamental Challenges for Hybrid Electrical/Optical
Datacenter Networks [short paper]
• Hamid Hajabdolali Bazzaz and Malveeka Tewari (University of California, San Diego), Guohui Wang (Rice University),
George Porter (University of California, San Diego), T. S. Eugene Ng (Rice University), David G. Andersen (Carnegie Mellon
University), Michael Kaminsky and Michael A. Kozuch (Intel Labs), and Amin Vahdat (University of California, San Diego)
• データセンターで1Bpsのケーブルで100m, 10 Gpbs のケーブルで12m しか延ばせない。これを埋める
p , p
Optical networkの活用。類似の研究としてSIGCOM10のHelio/C-Throughがある。
– CloudNaaS: A Cloud Networking Platform for Enterprise Applications [full paper]
• Theophilus Benson and Aditya Akella (University of Wisconsin, Madison) and Anees Shaikh and Sambit Sahu (IBM
Research, TJ Watson)
– To Cloud Or Not To Cloud? Musings On Costs and Viability [short paper, short
presentation]
• Yao Chen and Radu Sion (Stony Brook University)
– ActiveSLA: A Profit-Oriented Admission Control Framework for Database-as-a-
Service Providers [full paper]
• Pengcheng Xiong (Georgia Institute of Technology), Yun Chi, Shenghuo Zhu, and Junichi Tatemura (NEC Laboratories
America), Calton Pu (Georgia Institute of Technology), and Hakan Hacigumus (NEC Laboratories America)
• POSTER SESSION
28. プログラム2日目 午後
• Managing Resources (Part I) Chair: Dongyan Xu
– Modeling and Synthesizing Task Placement Constraints in Google Compute Clusters [full paper]
• Bikash Sharma (Pennsylvania State University), Victor Chudnovsky, Joseph L. Hellerstein, and Rasekh Rifaat (Google Inc.), and
Chita R. Das (Pennsylvania State University)
– CloudScale: Elastic Resource Scaling for Multi-Tenant Cloud Systems [full paper]
• Zhiming Shen, Sethuraman Subbiah, and Xiaohui Gu (North Carolina State University) and John Wilkes (Google)
– Automatic Management of Partitioned, Replicated Search Services [short paper]
• Florian Leibert, Jake Mannix, Jimmy Lin, and Babak Hamadani (Twitter)
– DOT: A Matrix Model for Analyzing, Optimizing and Deploying Software for Big Data Analytics in
Distributed Systems [full paper]
• Yin Huai and Rubao Lee (Department of Computer Science and Engineering, The Ohio State University), Simon Zhang
(Department of Computer Science, Cornell University), and Cathy H. Xia and Xiaodong Zhang (Department of Computer Science
and Engineering, The Ohio State University)
g g, y)
• Managing Resources (Part II) Chair: Shivnath Babu
– No One (Cluster) Size Fits All: Automatic Cluster Sizing for Data-intensive Analytics [full paper]
• Herodotos Herodotou, Fei Dong, and Shivnath Babu (Duke University)
– Declarative Automated Cloud Resource Orchestration [short paper]
• Changbin Liu and Boon Thau Loo (University of Pennsylvania) and Yun Mao (AT&T Labs Research)
– CoScan: Cooperative Scan Sharing in the Cloud [full paper]
• Xiaodan Wang (Johns Hopkins University), Anish Das Sarma and Christopher Olston (Yahoo! Research), and Randal Burns
(Johns Hopkins University)
– Incoop: MapReduce for Incremental Computations [full paper]
• Pramod Bhatotia, Alexander Wieder, Rodrigo Rodrigues, Umut A. Acar, and Rafael Pasquini (MPI-SWS)
30. PLOS2011概要
• 6th Workshop on Programming Languages and Operating Systems,
October 23, 2011, Cascais, Portugal
– http://plosworkshop.org/2011/
– SOSP2011のワークショップの一つ
– 参加者 40人ぐらい
– Keynote
• The Role of Language Technology in Trustworthy Operating Systems
– Gernot Heiser, University of New South Wales and NICTA
– スライドを公開している
http://ertos.nicta.com.au/publications/papers/Heiser_11:plos.slides.pdf
– MMU-enforced protection (SeL4) v.s. Type safety (Singularity)
のコスト比較(InterDomain Comm, CrossDomain Comm,サイク
ル毎の実行コード、コード量)は面白い
31. • Static Analyses
PLOS 午前
– Finding Resource-Release Omission Faults in Linux
• Suman Saha (LIP6-Regal), Julia Lawall (DIKU, University of Copenhagen), and Gilles Muller (INRIA/LIP6-Regal)
• リソースの解放ミスはエラー処理時に起こりやすい。エラーハンドリングの終了時にリソースリリースを開
放を確認する。はLinux 2.6.34のドライバディレクトリで100個のfaultを発見。
– Configuration Coverage in the Analysis of Large-Scale System Software
• Reinhard Tartler, Daniel Lohmann, Christian Dietrich, Christoph Egger, and Julio Sincero (Friedrich-Alexander University)
• Linux 3.0 では883のKonfig fileがある。All offのKonfigでは最小カーネルにならない。
• Security
• Rounding Pointers — Type Safe Capabilities with C++ Meta Programming
• Alexander Warg and Adam Lackorzynski (Technische Universität Dresden)
• Capability = C++のsmart pointer?
– Preliminary Design of the SAFE Platform
• André DeHon, Ben Karel (University of Pennsylvania), Thomas F. Knight, Jr. (BAE Systems), Gregory Malecha (Harvard
University), Benoît Montagu (University of Pennsylvania), Robin Morisset (École Normale Supérieure Paris), Greg Morrisett
(Harvard University), Benjamin C. Pierce (University of Pennsylvania), Randy Pollack (Harvard University), Sumit Ray (BAE
Systems), Olin Shivers (Northeastern University), Jonathan M. Smith (University of Pennsylvania), and Gregory Sullivan (BAE
Systems)
32. •
PLOS 午後
Dynamic Safety and Performance
– Dynamic Deadlock Avoidance in Systems Code Using Statically Inferred Effects
• Prodromos Gerakios, Nikolaos Papaspyrou (National Technical University of Athens), Konstantinos Sagonas (National Technical
University of Athens and Uppsala University), and Panagiotis Vekris (National Technical University of Athens)
• トランザクション毎ファイルシステムの一貫性を取るRecon
データ解析言語Datalog(prolog subset)
との統合
– Using Declarative Invariants for Protecting File-System Integrity
• Jack Sun, Daniel Fryer, Ashvin Goel, and Angela Demke Brown (University of Toronto)
– Assessing the Scalability of Garbage Collectors on Many Cores
• Lokesh Gidra, Gaël Thomas, Julien Sopena, and Marc Shapiro (Regal-LIP6/INRIA)
• メニーコア上でのガベコレ評価。OpenJDKで使われているparallel copying、concurrent
Mark Sweepなどのガベコレを48コア上で評価。
• Reversible Debugging
– URDB: A Universal Reversible Debugger Based on Decomposing Debugging Histories
• Ana-Maria Visan, Kapil Arya, Gene Cooperman, and Tyler Denniston (Northeastern University)