@proceedings{Georgiou2025,

title = {Dynamic Distributed Shared Memory: When&How? },

author = {Chryssis Georgiou and Nicolas Nicolaou and Andria Trigeorgi

},

url = {https://dl.acm.org/doi/10.1145/3721473.3722140},

year  = {2025},

date = {2025-05-31},

urldate = {2025-05-31},

howpublished = {Proceedings of the 12th Workshop on Principles and Practice of Consistency for Distributed Data (PaPoC'25), co-located with EuroSy'25, Rotterdam, Netherlands},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{SRDS2024,

title = {Ares II: Tracing the Flaws of a (Storage) God},

author = {Chryssis Georgiou and Nicolas Nicolaou and Andria Trigeorgi},

url = {https://github.com/atrigeorgi/Tracing-ARES-Bottlenecks/blob/main/Tracing___Optimizations_Design___arxiv.pdf},

doi = {10.1109/SRDS64841.2024.00027},

year  = {2024},

date = {2024-11-01},

urldate = {2024-11-01},

booktitle = {Proceedings of the 43rd International Symposium on Reliable Distributed Systems (SRDS'24)},

abstract = {Ares is a modular framework, designed to implement dynamic, reconfigurable, fault-tolerant, read/write and strongly consistent distributed shared memory objects. Recent enhancements of the framework have realized the efficient implementation of large objects, by introducing versioning and data striping techniques. In this work, we identify performance bottlenecks of the Ares's variants by utilizing distributed tracing, a popular technique for monitoring and profiling distributed systems. We then propose optimizations across all versions of Ares, aiming in overcoming the identified flaws, while preserving correctness. We refer to the optimized version of Ares as Ares II, which now features a piggyback mechanism, a garbage collection mechanism, and a batching reconfiguration technique for improving the performance and storage efficiency of the original Ares. We rigorously prove the correctness of Ares II, and we demonstrate the performance improvements by an experimental comparison (via distributed tracing) of the Ares II variants with their original counterparts.},

howpublished = {Proceeding of the 43rd International Symposium on Reliable Distributed Systems (SRDS'24)},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{APPLIED24,

title = {Tracing the Latencies of Ares: A DSM Case Study},

author = {Chryssis Georgiou and Nicolas Nicolaou and Andria Trigeorgi},

doi = {10.1145/3663338.3665826},

isbn = {9798400706707},

year  = {2024},

date = {2024-06-20},

urldate = {2024-06-20},

booktitle = {The Applied Workshop: Advanced tools, programming languages, and Platforms for Implementing and Evaluating algorithms for Distributed systems (ApPLIED24)},

abstract = {Distributed tracing is a method used to monitor applications by 

tracking and visualizing requests as they move across various com- 

ponents and services in a distributed system. Despite being widely 

adopted in major cloud-computing applications, to the best of our 

knowledge, distributed tracing has not been employed in Distributed 

Shared Memory (DSM) emulations. In such emulations, typically, a 

set of networked nodes (servers) maintain copies of the memory 

data, and a set of clients (readers/writers) access the data by sending 

messages to the servers. The main challenge in this environment 

is to maintain the consistency of the data despite asynchrony and 

failures. Traditionally, the latency of operations in DSM implemen- 

tations has been evaluated through simple log-based strategies 

providing a high-level performance analysis. 

This paper introduces distributed tracing to DSM, in an attempt 

to provide a fine-grain performance analysis, helping to identify 

performance bottlenecks. To this respect, we use Ares as a case 

study. Ares is a crash-tolerant DSM algorithm, providing atomic 

consistency and supporting dynamic participation of networked 

nodes. Our approach employs a set of tracing tools: Opentelemetry 

for code instrumentation, Jaeger for telemetry data collection, and 

Grafana for visualization.},

howpublished = {Proceedings of the 2024 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED'24)},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}

@proceedings{GEC2024,

title = {Robust and Consistent Distributed Storage as a Service.},

author = {Andria Trigeorgi},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {proceedings of the 6th Summit on Gender Equality in Computing (GEC 2024)},

journal = {the 6th Summit on Gender Equality in Computing (GEC 2024 Conference)},

howpublished = {Proceedings of the Conference on Gender Equality in Computing (GEC'24)},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}