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distributed debugging for mobile networks

JOURNAL OF SYSTEMS AND SOFTWARE 2014年第1期90卷 76-90页

作者： Boix, Elisa Gonzalez Noguera, Carlos De Meuter, Wolfgang Vrije Univ Brussel B-1050 Brussels Belgium

Debuggers are an integral part, albeit often neglected, of the development of distributed applications. Ambient-oriented programming (AmOP) is a distributed paradigm for applications running on mobile ad hoc networks. In AmOP the complexity of programming in a distributed setting is married with the network fragility and open topology of mobile applications. To our knowledge, there is no debugging approach that tackles both these issues. In this paper we argue that a novel kind of distributed debugger that we term an ambient-oriented debugger, is required. We present REME-D (read as remedy), an online ambient-oriented debugger that integrates techniques from distributed debugging (event-based debugging, message breakpoints) and proposes facilities to deal with ad hoc, fragile networks - epidemic debugging, and support for frequent disconnections. (C) 2013 Elsevier Inc. All rights reserved.

关键词： distributed debugging distributed object-oriented applications Mobile networks

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debugging strongly-compartmentalized distributed systems 34

Debugging strongly-compartmentalized distributed systems

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34th IEEE International Parallel and distributed Processing Symposium (IPDPS)

作者： Zhu, Henry Sultana, Nik Loo, Boon Thau Univ Penn Comp & Informat Sci Philadelphia PA 19104 USA

ISBN: (纸本)9781728174457

Splitting software into distributed compartments is an important software security technique that limits the effect of vulnerabilities. Unfortunately the resulting systems are difficult to analyze or debug interactively when compared to the original. Not only are compartments distributed and executed in parallel, but they may also be strongly isolated by being sandboxed or run in minimal environments that lack debugging facilities. This paper is the first to study practical debugging techniques for strongly-isolated distributed compartments. We adapt ideas from other remote or distributed debugging settings to this domain, and implement and describe two radically different approaches to this problem. We evaluate these approaches both qualitatively and quantitatively, and using both toy examples and real-world open-source software. Our main finding is that out of the two approaches, using GDB remote stubs presents a good balance of performance, flexibility and usability, and we characterize this more precisely in our evaluation.

关键词： software compartments distributed debugging development tools

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Jdebug: A Fast, Non-Intrusive and Scalable Fault Locating Tool for Ten-Million-Scale Parallel Applications

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2022年第12期33卷 3491-3504页

作者： Peng, Dajia Feng, Yunlong Liu, Yong Liu, Xin Xue, Wei Chen, Dexun Song, Jiawei Chen, Zuoning Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Natl Supercomp Ctr Wuxi Wuxi Jiangsu Peoples R China Natl Res Ctr Parallel Comp Engn & Technol Beijing 100083 Peoples R China

This article presents Jdebug, a fast, non-intrusive and scalable fault locating tool for extreme-scale parallel applications. Large-scale debugging has drawn more attention with the increasing scale of supercomputers and applications. To eliminate program intrusion caused by traditional instrumentation or interception during debugging information acquisition, we introduce the out-of-band management into large-scale debugging. We propose a rapid information gathering scheme that separates user and debugging traffic to solve scalability problem and to eliminate program interference during merging data. Observations of Program Counters (PC) and performance characteristics in suspended applications find abnormalities and help locate abnormal threads caused by software errors or hardware failures effectively. Evaluation shows that Jdebug collects PCs of over 20 million cores on the new Sunway supercomputer within 1.97 seconds, and can locate the abnormal threads in 1.4 seconds with an accuracy of 92.5%. In the running test of three fundamental benchmarks (HPL, HPCG, Graph500) and seventeen real-world applications, Jdebug quickly and accurately locates abnormal threads to help find scalability errors and hardware failures including memory access failures, communication failures, and execution component failures, which validates its effectiveness.

关键词： debugging Servers Supercomputers Hardware Maintenance engineering Instruction sets Task analysis distributed debugging software engineering software software engineering testing and debugging

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Non-Intrusive distributed Tracing of Wireless IoT Devices with the FlockLab 2 Testbed

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ACM TRANSACTIONS ON INTERNET OF THINGS 2022年第1期3卷 1–31页

作者： Trub, Roman Da Forno, Reto Daschinger, Lukas Biri, Andreas Beutel, Jan Thiele, Lothar Swiss Fed Inst Technol Comp Engn & Networks Lab TIK Gloriastr 35 CH-8092 Zurich Switzerland Univ Innsbruck Dept Comp Sci Technikerstr 21a A-6020 Innsbruck Austria

Testbeds for wireless IoT devices facilitate testing and validation of distributed target nodes. A testbed usually provides methods to control, observe, and log the execution of the software. However, most of the methods used for tracing the execution require code instrumentation and change essential properties of the observed system. Methods that are non-intrusive are typically not applicable in a distributed fashion due to a lack of time synchronization or necessary hardware/software support. In this article, we present a tracing system for validating time-critical software running on multiple distributed wireless devices that does not require code instrumentation, is non-intrusive and is designed to trace the distributed state of an entire network. For this purpose, we make use of the on-chip debug and trace hardware that is part of most modern microcontrollers. We introduce a testbed architecture as well as models and methods that accurately synchronize the timestamps of observations collected by distributed observers. In a case study, we demonstrate how the tracing system can be applied to observe the distributed state of a flooding-based low-power communication protocol for wireless sensor networks. The presented non-intrusive tracing system is implemented as a service of the publicly accessible open source FlockLab 2 testbed.

关键词： distributed debugging on-chip debug and trace testbed IoT FlockLab wireless sensor network

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Retroscope: Retrospective Monitoring of distributed Systems

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2019年第11期30卷 2582-2594页

作者： Charapko, Aleksey Ailijiang, Ailidani Demirbas, Murat Kulkarni, Sandeep SUNY Buffalo Comp Sci & Engn Buffalo NY 14260 USA Michigan State Univ Dept Comp Sci & Engn E Lansing MI 48824 USA

Retroscope is a comprehensive lightweight distributed monitoring tool that enables users to query and reconstruct past consistent global states of the system. Retroscope achieves this by augmenting the system with Hybrid Logical Clocks (HLC) and by streaming HLC-stamped event logs for storage and processing;these HLC timestamps are then used for constructing global (or nonlocal) snapshots upon request. Retroscope provides a rich querying language (RQL) to facilitate searching for global predicates across past consistent states. The search is performed by advancing through global states in small incremental steps, greatly reducing the amount of computation needed to construct consistent states. The Retroscope search algorithm is embarrassingly-parallel and can employ many worker processes (each processing up to 150,000 consistent snapshots per second) to handle a single query. We evaluate Retroscope's monitoring capabilities in two case studies: Chord and Apache ZooKeeper.

关键词： distributed debugging distributed applications tracing query languages

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Using Weaker Consistency Models with Monitoring and Recovery for Improving Performance of Key-Value Stores 8

Using Weaker Consistency Models with Monitoring and Recovery...

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8th Latin-American Symposium on Dependable Computing (LADC)

作者： Duong Nguyen Charapko, Aleksey Kulkarni, Sandeep S. Demirbas, Murat Michigan State Univ E Lansing MI 48824 USA SUNY Buffalo Buffalo NY USA

ISBN: (纸本)9781538684894

Limitations of the CAP theorem imply that if availability is desired in the presence of faults - especially that create network partitions (or substantial delays), one must sacrifice sequential consistency, a consistency model that is more natural for system design. We focus on the problem of what a designer should do if he/she has an algorithm that works correctly with sequential consistency but is faced with an underlying key-value store that provides a weaker (e.g., eventual or causal) consistency. We propose a detect-rollback based approach: The designer identifies a correctness predicate, say P, and continues to run the protocol, as our system monitors P. If P is violated (because the underlying key-value store provides a weaker consistency), the system rolls back and resumes the computation at a state where P holds. We evaluate this approach with practical graph applications running on the Voldemort key-value store. Our experiments, deployed on Amazon AWS EC2 instances, show that using eventual consistency with monitoring can provide a 50-80% increase in throughput when compared with sequential consistency. We also show that the overhead of the monitoring itself is low (typically less than 4%) and the latency of detecting violations is small. In particular, more than 99.9% of violations are detected in less than 50 milliseconds in regional AWS networks, and in less than 5 seconds in global AWS networks. In turn, this makes it possible to provide efficient recovery from such faults with a minimal amount of work wasted due to rollbacks.

关键词： predicate detection distributed debugging distributed monitoring distributed snapshot distributed key-value stores

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Implementing record and refinement for debugging timing-dependent communication

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SCIENCE OF COMPUTER PROGRAMMING 2017年 134卷 4-18页

作者： Felgentreff, T. Perscheid, M. Hirschfeld, R. Univ Potsdam Software Architecture Grp Hasso Plattner Inst Prof Dr Helmert Str 2-3 Potsdam Germany

distributed applications are hard to debug because timing-dependent network communication is a source of non-deterministic behavior. Current approaches to debug non deterministic failures include post-mortem debugging as well as record and replay. However, the first impairs system performance to gather data, whereas the latter requires developers to understand the timing-dependent communication at a lower level of abstraction than they develop at. Furthermore, both approaches require intrusive core library modifications to gather data from live systems. In this paper, we present the Peek-At-Talk debugger for investigating non-deterministic failures with low overhead in a systematic, top-down method, with a particular focus on tool-building issues in the following areas: First, we show how our debugging framework Path Tools guides developers from failures to their root causes and gathers run-time data with low overhead. Second, we present Peek-At-Talk, an extension to our Path Tools framework to record non-deterministic communication and refine behavioral data that connects source code with network events. Finally, we scope changes to the core library to record network communication without impacting other network applications. (C) 2015 Elsevier B.V. All rights reserved.

关键词： distributed debugging Record and replay Dynamic analysis Record and refinement

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PerfCompass: Online Performance Anomaly Fault Localization and Inference in Infrastructure-as-a-Service Clouds

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2016年第6期27卷 1742-1755页

作者： Dean, Daniel J. Nguyen, Hiep Wang, Peipei Gu, Xiaohui Sailer, Anca Kochut, Andrzej N Carolina State Univ Dept Comp Sci Raleigh NC 27603 USA IBM Corp TJ Watson Res Ctr Yorktown Hts NY USA

Infrastructure-as-a-service clouds are becoming widely adopted. However, resource sharing and multi-tenancy have made performance anomalies a top concern for users. Timely debugging those anomalies is paramount for minimizing the performance penalty for users. Unfortunately, this debugging often takes a long time due to the inherent complexity and sharing nature of cloud infrastructures. When an application experiences a performance anomaly, it is important to distinguish between faults with a global impact and faults with a local impact as the diagnosis and recovery steps for faults with a global impact or local impact are quite different. In this paper, we present PerfCompass, an online performance anomaly fault debugging tool that can quantify whether a production-run performance anomaly has a global impact or local impact. PerfCompass can use this information to suggest the root cause as either an external fault (e.g., environment-based) or an internal fault (e.g., software bugs). Furthermore, PerfCompass can identify top affected systemcalls to provide useful diagnostic hints for detailed performance debugging. PerfCompass does not require source code or runtime application instrumentation, which makes it practical for production systems. We have tested PerfCompass by running five common open source systems (e.g., Apache, MySQL, Tomcat, Hadoop, Cassandra) inside a virtualized cloud testbed. Our experiments use a range of common infrastructure sharing issues and real software bugs. The results show that PerfCompass accurately classifies 23 out of the 24 tested cases without calibration and achieves 100 percent accuracy with calibration. PerfCompass provides useful diagnosis hints within several minutes and imposes negligible runtime overhead to the production system during normal execution time.

关键词： Reliability, availability, and serviceability debugging aids distributed debugging performance

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Diagnosis of Performance Faults in Large Scale MPI Applications via Probabilistic Progress-Dependence Inference

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2015年第5期26卷 1280-1289页

作者： Laguna, Ignacio Ahn, Dong H. de Supinski, Bronis R. Bagchi, Saurabh Gamblin, Todd Lawrence Livermore Natl Lab Livermore CA 94550 USA Purdue Univ Dept Elect & Comp Engn W Lafayette IN 47907 USA

debugging large-scale parallel applications is challenging. Most existing techniques provide little information about failure root causes. Further, most debuggers significantly slow down program execution, and run sluggishly with massively parallel applications. This paper presents a novel technique that scalably infers the tasks in a parallel program on which a failure occurred, as well as the code in which it originated. Our technique combines scalable runtime analysis with static analysis to determine the least-progressed task(s) and to identify the code lines at which the failure arose. We present a novel algorithm that infers probabilistically progress dependence among MPI tasks using a globally constructed Markov model that represents tasks' control-flow behavior. In comparison to previous work, our algorithm infers more precisely the least-progressed task. We combine this technique with static backward slicing analysis, further isolating the code responsible for the current state. A blind study demonstrates that our technique isolates the root cause of a concurrency bug in a molecular dynamics simulation, which only manifests itself at 7,996 tasks or more. We extensively evaluate fault coverage of our technique via fault injections in 10 HPC benchmarks and show that our analysis takes less than a few seconds on thousands of parallel tasks.

关键词： distributed debugging MPI progress dependence parallel applications

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Scalable Relative debugging

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2014年第3期25卷 740-749页

作者： Minh Ngoc Dinh Abramson, David Jin, Chao Monash Univ Fac Informat Technol Mulgrave Vic 3170 Australia Monash Univ Fac Informat Technol Clayton Vic 3800 Australia Univ Queensland Ctr Res Comp Brisbane Qld 4072 Australia Monash Univ Fac Informat Technol Mulgrave Vic 3170 Australia

Detecting and isolating bugs that arise only at high processor counts is a challenging task. Over a number of years, we have implemented a special debugging method, called "relative debugging," that supports debugging applications as they evolve or are ported to larger machines. It allows a user to compare the state of a suspect program against another reference version even as the number of processors is increased. The innovative idea is the comparison of runtime data to reason about the state of the suspect program. While powerful, a naive implementation of the comparison phase does not scale to large problems running on large machines. In this paper, we propose two different solutions including a hash-based scheme and a direct point-to-point scheme. We demonstrate the implementation, a case study, as well as the performance, of our techniques on 20K cores of a Cray XE6 system.

关键词： Parallellism and concurrency distributed debugging assertion checkers

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