Proceedings of the Workshop on Hot Topics in Operating Systems最新文献_第6页

Synthesizing Cluster Management Code for Distributed Systems 分布式系统的综合集群管理代码

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321444

L. Suresh, João Loff, Nina Narodytska, L. Ryzhyk, Shmuel Sagiv, B. Oki

引用次数: 3

Fast key-value stores: An idea whose time has come and gone 快速键值存储:这个想法已经过时了

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321434

A. Adya, Robert Grandl, Daniel S. Myers, Henry Qin

{"title":"Fast key-value stores: An idea whose time has come and gone","authors":"A. Adya, Robert Grandl, Daniel S. Myers, Henry Qin","doi":"10.1145/3317550.3321434","DOIUrl":"https://doi.org/10.1145/3317550.3321434","url":null,"abstract":"Remote, in-memory key-value (RINK) stores such as Memcached [6] and Redis [7] are widely used in industry and are an active area of academic research. Coupled with stateless application servers to execute business logic and a databaselike system to provide persistent storage, they form a core component of popular data center service architectures. We argue that the time of the RINK store has come and gone: their domain-independent APIs (e.g., PUT/GET) push complexity back to the application, leading to extra (un)marshalling overheads and network hops. Instead, data center services should be built using stateful application servers or custom in-memory stores with domain-specific APIs, which offer higher performance than RINKS at lower cost. Such designs have been avoided because they are challenging to implement without appropriate infrastructure support. Given recent advances in auto-sharding [8, 9], we argue it is time to revisit these decisions. In this paper, we evaluate the potential performance improvements of stateful designs, propose a new abstraction, the linked, in-memory key-value (LINK) store, to enable developers to easily implement stateful services, and discuss areas for future research.","PeriodicalId":224944,"journal":{"name":"Proceedings of the Workshop on Hot Topics in Operating Systems","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134189160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Practical Safe Linux Kernel Extensibility 实用安全的Linux内核可扩展性

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321429

Samantha Miller, Kaiyuan Zhang, Danyang Zhuo, Shibin Xu, A. Krishnamurthy, T. Anderson

引用次数: 3

Comprehensive and Efficient Runtime Checking in System Software through Watchdogs 通过看门狗全面有效地检查系统软件的运行时

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321440

Chang Lou, Peng Huang, Scott F. Smith

引用次数: 7

Designing Far Memory Data Structures: Think Outside the Box 设计远内存数据结构:跳出框框思考

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321433

M. Aguilera, K. Keeton, Stanko Novakovic, S. Singhal

引用次数: 61

Towards Multiverse Databases 迈向多元宇宙数据库

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321425

Alana Marzoev, L. Araújo, Malte Schwarzkopf, Samyukta Yagati, E. Kohler, R. Morris, M. Kaashoek, S. Madden

引用次数: 10

Machine Learning Systems are Stuck in a Rut 机器学习系统墨守成规

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321441

P. Barham, M. Isard

引用次数: 56

Towards Automatic Inference of Inductive Invariants 关于归纳不变量的自动推理

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321451

Haojun Ma, Aman Goel, Jean-Baptiste Jeannin, Manos Kapritsos, Baris Kasikci, K. Sakallah

{"title":"Towards Automatic Inference of Inductive Invariants","authors":"Haojun Ma, Aman Goel, Jean-Baptiste Jeannin, Manos Kapritsos, Baris Kasikci, K. Sakallah","doi":"10.1145/3317550.3321451","DOIUrl":"https://doi.org/10.1145/3317550.3321451","url":null,"abstract":"Distributed systems are notoriously difficult to design and implement correctly. Formal verification provides correctness proofs, and has recently been successfully applied to various distributed systems. At the heart of a typical formal verification is a computer-checked proof with an inductive invariant. Finding this inductive invariant is the hardest part of the proof: a part that is currently undertaken manually by the developer and is responsible for most of the effort associated with formal verification. In this paper, we present a new approach: Incremental Inference of Inductive Invariants (I4), to automatically generate inductive invariants for distributed protocols. We start from a simple idea: the inductive invariant of a finite instance of the protocol must be an instance of a general inductive invariant for the infinite distributed protocol. In I4, we instantiate a finite instance of the protocol, work out the finite inductive invariant of this instance, then figure out the general inductive invariant as a generalization of the finite invariant. Our experiments show that I4 can finish the general proof of correctness of several systems with minimal human effort.","PeriodicalId":224944,"journal":{"name":"Proceedings of the Workshop on Hot Topics in Operating Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131730678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

The Case for I/O-Device-as-a-Service I/ o -设备即服务案例

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321446

A. A. Sani, T. Anderson

引用次数: 6

You can't debug what you can't see: Expanding observability with the OmniTable 你不能调试你看不到的东西:用omunitable扩展可观察性

Proceedings of the Workshop on Hot Topics in Operating Systems Pub Date : 2019-05-13 DOI: 10.1145/3317550.3321428

Andrew Quinn, J. Flinn, Michael J. Cafarella

{"title":"You can't debug what you can't see: Expanding observability with the OmniTable","authors":"Andrew Quinn, J. Flinn, Michael J. Cafarella","doi":"10.1145/3317550.3321428","DOIUrl":"https://doi.org/10.1145/3317550.3321428","url":null,"abstract":"The effectiveness of a debugging tool is fundamentally limited by what program state it can observe. Yet, for performance reasons, all current debugging tools restrict the program state that can be observed in some way. For example, tools like heap analysis restrict what can be observed (i.e., only global variables) and tools like core dump analysis restrict when observations may be made (i.e., only on program termination). Other tools effectively limit the scope of observation by requiring developers to specify what and when observations will be made before execution (e.g., logging) or during an execution (e.g., gdb). We propose a new abstraction for debugging, called an OmniTable, that logically exposes unrestricted access to all program state at all points in an execution to developers. The OmniTable represents a program execution as a database-style table. Developers inspect the OmniTable using a familiar declarative query language: SQL. SQL simplifies the observation and analysis of large, complex execution state. Iterative queries are inherently consistent since they operate over the same logical table. Clearly, materializing the OmniTable for even a simple program is infeasible due to storage and processing overheads. Thus, our prototype, SteamDrill, selectively materializes only the regions of the OmniTable required to answer each query by using deterministic record and replay to reproduce the execution and dynamic instrumentation to extract needed state. By expressing debugging queries with relational logic, SteamDrill leverages proven optimizations such as query optimization and caching. In addition, decomposition into relational logic allows a query to be executed via repeated replays, each replay extracting information needed by the next, which can often be more efficient than extracting all information during a single execution.","PeriodicalId":224944,"journal":{"name":"Proceedings of the Workshop on Hot Topics in Operating Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125791775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3