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Abstract
Current Work: Analysis and Approach
GC Pauses Analysis
Conclusions and Future Work
Related Work
Performance Analysis
Evaluation and Conclusions
Measurement Results for Time-Based Fingerprinting
Conclusion and Future Work
Data Segmentation and Tagging
Work in Progress and Future Work
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2014 Doctoral Workshop on Distributed Systems

Profile image of Pierre KuonenPierre Kuonen

2014

https://doi.org/10.7892/BORIS.55030
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…

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80 pages

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1 file

Abstract

The Doctoral Workshop on Distributed Systems has been held at Kandersteg, Switzerland, from June 3-5, 2014. Ph.D. students from the Universities of Neuchâtel and Bern as well as the University of Applied Sciences of Fribourg presented their current research work and discussed recent research results. This technical report includes the extended abstracts of the talks given during the workshop.

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Qualitative Results for Distributed Systems
D. J . Inman

Approved for public release, distribution 2b DECLASSIFICATIONIDOWNGRAD ItCHAMEJ IW' unlimited 4 PERFORMING ORGANIZATION REPWUMBER(S) S. MONITORING ORGANIZATION REPORT NUMBER(S) JD AY)"RTx. 89-U426 I 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Research Foundation of the (If applicable)

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Principles of Distributed Systems
Vijay Garg

1996

PRINCIPLES OF DISTRIBUTED SYSTEMS 2.4 Ricart and Agrawala's Algorithm 2.5 Centralized Algorithm 2.6 Dijkstra's Self-stabilizing Algorithm 2.7 Exercises 2.8 Bibliographic Remarks Chapter 2 2.1 Problem with the simple centralized mutual exclusion algorithm 2.2 The Algorithm for Active Vector at process i 2.3 Proof for the induction case 2.4 Lamport's Algorithm for Mutual Exclusion 2.5 Ricart and Agrawala's Algorithm 2.6 Proof for the Ricart and Agrawala's Algorithm 2.7 Algorithm for Client Processes 2.8 Algorithm for the coordinator process 66 xi xii PRINCIPLES OF DISTRIBUTED SYSTEMS Chapter 3 3.1 Consistent and inconsistent cuts 72 3.2 Snapshot algorithm for recording local states 75 3.3 Chandy and Lamport's Snapshot Algorithm 78 3.4 Prooffor Safety 78 3.5 An Algorithm for Snapshots when channels are non-FIFO. 80 Chapter 4 4.1 Example of a Non-Linear Predicate 91 4.2 An efficient algorithm to detect a linear predicate 91 Chapter 5 List of Figures xiii 6.6 Using a queue insert graph to find the output queue 6.7 Function FindQ that finds the output queue to insert an element 6.8 Algorithm for the Adversary 6.9 Converting Deposets into Flow Graphs 163 Chapter' 7.1 Computations with the strong predicate flagl " flag2 true. 7.2 I(z) and first(z) 7.3 Illustration of the proof of strong conjunctive predicates Chapter 8 8.1 State machine implementing a + cb*c Chapter 9 9.1 A FIFO computation that is not causally ordered 9.2 A computation that is not synchronously ordered 9.3 A computation that is synchronously ordered 9.4 Algorithm for FIFO ordering 9.5 Algorithm for causal ordering 9.6 Inconsistent Memory State 201 9.7 Time Diagrams under Synchronous Message Passing 9.8 Crowns of size 2 and 3 203 9.9 commit and commit reply Messages 9.10 Algorithm to Implement Synchronous Ordering of Messages Chapter 10 10.1 A message sequence for repeated computation of a function 10.2 Overlapping trees that determine message sequences 10.3 The function nezt 10.4 Node groups and transitions 10.5 Node labels generated by next 10.6 Physical connectivity required based on two-step routing 10.7 The function snezt 10.8 Message Sequences Generated by snext 10.9 Message sequence generated by bcnext xiv PRINCIPLES OF DISTRIBUTED SYSTEMS 10.10 The function bcnezt 10.11 Distributed branch and bound 10.12 Asynchronous computation of a fixed point 239 244 PREFACE The book is designed for a graduate level course on distributed systems. Several examples and exercise problems are included in each chapter to facilitate classroom teaching. Our treatment is based on the graduate courses given at The University of Texas at Austin. Preface xvii I thank the Department of Electrical and Computer Engineering at The University of Texas at Austin where I was given the opportunity to develop and teach courses on distributed systems. I was supported in part by a grant from the National Science Foundation, a lRW faculty assistantship, an IBM grant, and a General Motors Centennial fellowship. I also thank Alex Greene at Kluwer Academic Publishers for his help. Finally, I thank my wife Meenakshi whose love, support, and understanding kept me inspired in accomplishing this goal. Vijay K. Garg • Low cost: Availability of high bandwidth network and inexpensive workstations also favors distributed computing for economic reasons.

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Report of the NSF workshop on research challenges in distributed computer systems
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2005

This report 1 summarizes recommendations from a workshop on research challenges in distributed computer systems, sponsored by the National Science Foundation. A program committee solicited input from the research community by asking researchers to submit position papers that identified grand challenges in distributed systems, invited researchers based on their submissions, and selected a few position papers for presentation at the workshop. Most of the workshop was organized around break-out sessions, in which we refined the research challenges and identified the facilities needed to carry out future research as well as what the distributed systems community can contribute to the facility. Information about the workshop, including the full program, the selected submissions, and the slides of the presentations and the break-out sessions, is available at http://www.pdos.lcs.mit.edu/˜kaashoek/nsf/.

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Balancing Complexity and Advantages in Distributed Systems: A Comprehensive Analysis
Fateme Rahimi

Distributed systems, composed of interconnected nodes working collaboratively, form the backbone of modern technology, powering applications in cloud computing, IoT, and beyond. While offering advantages like scalability, reliability, and cost-efficiency, these systems also present challenges such as design complexity, synchronization, and security risks. This paper explores the intricacies of distributed systems, detailing their advantages, challenges, and applications while highlighting advanced programming techniques and optimization strategies that drive their evolution

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Andrzej Goscinski

Lecture Notes in Computer Science, 2006

Parallel computing is strongly influenced by the challenges of distributed systems, such as a need for a Single System Image, resource sharing and allocation, failures and a need for fault tolerance, long latencies, network partition, disconnected operation, demands of users wishing to solve more computationally and communication demanding problems, and opportunities created by grids and Web services. Distributed computing is the computing mainstream now; it is based on different forms of distributed systems: clusters, grids, peer-to-peer systems, web services, service oriented architectures. This topic provides a forum for research and practice, of interest to both academia and industry, about distributed computing and distributed algorithms. Submissions were encouraged in all areas of distributed systems and algorithms relevant to parallel computing, with emphasis on design and practice of distributed algorithms, analysis of the behaviour of distributed systems and algorithms, distributed fault-tolerance, distributed operating systems and databases, scalability, concurrency and performance in distributed systems, resource sharing and load balancing in distributed systems, distributed algorithms in telecommunications, distributed mobile computing, resource and service discovery, security in distributed systems, and standards and middleware for the distribution of parallel computations. Twenty papers were submitted in this topic. The subjects were varied, but a common theme of many of them is recovery, resource allocation, mutual exclusion, garbage collection and coordination. Other themes include load balancing, scheduling and consensus algorithms. Eight papers have been accepted.

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