A Systematic Approach to Safe Coordination of Dynamic Participants in Real-Time Distributed Systems

Advances in Intelligent Systems and Computing - Complex Systems Design & Management Asia ◽

10.1007/978-3-319-29643-2_9 ◽

2016 ◽

pp. 121-134

Author(s):

Mong Leng Sin

Keyword(s):

Distributed Systems ◽

Real Time ◽

Systematic Approach

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A Systematic Approach on Modeling Refinement and Regression Testing of Real-Time Distributed Systems

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2019.11.341 ◽

2019 ◽

Vol 52 (13) ◽

pp. 1091-1096

Author(s):

Deepak Pal ◽

Jüri Vain

Keyword(s):

Distributed Systems ◽

Real Time ◽

Systematic Approach ◽

Regression Testing

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Performability of integrated software-hardware components of real-time parallel and distributed systems

IEEE Transactions on Reliability ◽

10.1109/24.159799 ◽

1992 ◽

Vol 41 (3) ◽

pp. 352-362 ◽

Cited By ~ 8

Author(s):

S.M.R. Islam ◽

N.H. Ammar

Keyword(s):

Distributed Systems ◽

Real Time ◽

Integrated Software

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XERIS/APEX

ACM SIGAda Ada Letters ◽

10.1145/3463478.3463484 ◽

2021 ◽

Vol 40 (2) ◽

pp. 65-69

Author(s):

Richard Wai

Keyword(s):

Distributed Systems ◽

Real Time ◽

Distributed System ◽

Dynamic Scaling ◽

Distributed Application ◽

Heavy Weight ◽

System Models ◽

In The Wild ◽

On Line ◽

Language Technologies

Modern day cloud native applications have become broadly representative of distributed systems in the wild. However, unlike traditional distributed system models with conceptually static designs, cloud-native systems emphasize dynamic scaling and on-line iteration (CI/CD). Cloud-native systems tend to be architected around a networked collection of distinct programs ("microservices") that can be added, removed, and updated in real-time. Typically, distinct containerized programs constitute individual microservices that then communicate among the larger distributed application through heavy-weight protocols. Common communication stacks exchange JSON or XML objects over HTTP, via TCP/TLS, and incur significant overhead, particularly when using small size message sizes. Additionally, interpreted/JIT/VM-based languages such as Javascript (NodeJS/Deno), Java, and Python are dominant in modern microservice programs. These language technologies, along with the high-overhead messaging, can impose superlinear cost increases (hardware demands) on scale-out, particularly towards hyperscale and/or with latency-sensitive workloads.

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