scholarly journals Modelling Distributed Systems in Distributed Autonomous and Asynchronous Automata (DA3)

2019 ◽  
Author(s):  
Wiktor Daszczuk
Keyword(s):  
Distributed Systems ◽  
Structural Analysis ◽  
Distributed System ◽  
System Configuration ◽  
Graphical Modeling ◽  
Global System ◽  
Equivalent Models ◽  
Distributed Components ◽  
System Components ◽  
Asynchronous Automata

Integrated Model of Distributed Systems is used for modeling and verification. In formalism, the distributed system is modeled as a collection of server states and agent messages. The evolution of the system takes the form of actions that transform the global system configuration (states and messages) into a new configuration. Formalism is used in the Dedan verification environment for finding different kinds of deadlocks: communication deadlocks in the server view and resource deadlocks in the agent view. For other purposes, a conversion has been developed to equivalent models: to Petri nets for structural analysis and do Distributed Autonomous and Asynchronous Automata (DA3) for easy graphical modeling in terms of system components. In addition, it is possible to simulate a verified system on distributed components in DA3. The automata have two forms: Server-DA3 (S-DA3) for the server view and Agent-DA3 (A-DA3) for the agent view. DA3 formalism is compared to other concepts of distributed automata known from the literature.

D-Cloud

2012 ◽  
pp. 340-355 ◽  
Author(s):  
Toshihiro Hanawa ◽  
Mitsuhisa Sato
Keyword(s):  
Distributed Systems ◽  
Software Testing ◽  
Distributed System ◽  
Test Procedure ◽  
System Configuration ◽  
Test Scenario ◽  
Management Software ◽  
Testing Environment ◽  
Cloud Management ◽  
Hardware Faults

Various information systems are widely used in the information society era, and the demand for highly dependable system is increasing year after year. However, software testing for such a system becomes more difficult due to the enlargement and the complexity of the system. In particular, it is often difficult to test parallel and distributed systems in the real world after deployment, although reliable systems, such as high-availability servers, are parallel and distributed systems. To solve these problems, the authors propose a software testing environment for dependable parallel and distributed system using the cloud computing technology, named D-Cloud. D-Cloud consists of the cloud management software as the role of the resource management, and a lot of virtual machine monitors with fault injection facility in order to simulate hardware faults. In addition, D-Cloud introduces the scenario manager, and it makes a number of different tests perform automatically. Currently, D-Cloud is realized by the use of Eucalyptus as the cloud management software. Furthermore, the authors introduce FaultVM based on QEMU as the virtualization software, and D-Cloud frontend that interprets test scenario, constructs test environment, and dispatches commands. D-Cloud enables automating the system configuration and the test procedure as well as performing a number of test cases simultaneously and emulating hardware faults flexibly. This chapter presents the concept and design of D-Cloud, and describes how to specify the system configuration and the test scenario. Furthermore, the preliminary test example as the software testing using D-Cloud is presented. As the result, the authors show that D-Cloud allows easy setup of the environment, and to test the software testing for the distributed system.

scholarly journals Graphic modeling in Distributed Autonomous and Asynchronous Automata (DA3)

2021 ◽  
Author(s):  
Wiktor B. Daszczuk
Keyword(s):  
Distributed Systems ◽  
Formal Verification ◽  
Graphical Simulation ◽  
Distributed Components ◽  
Distributed Computations ◽  
Asynchronous Automata ◽  
Graphic Modeling ◽  
Late Stages ◽  
Natural Characteristics ◽  
Insight Into

AbstractAutomated verification of distributed systems becomes very important in distributed computing. The graphical insight into the system in the early and late stages of the project is essential. In the design phase, the visual input helps to articulate the collaborative distributed components clearly. The formal verification gives evidence of correctness or malfunction, but in the latter case, graphical simulation of counterexample helps for better understanding design errors. For these purposes, we invented Distributed Autonomous and Asynchronous Automata (DA3), which have the same semantics as the formal verification base—Integrated Model of Distributed Systems (IMDS). The IMDS model reflects the natural characteristics of distributed systems: unicasting, locality, autonomy, and asynchrony. Distributed automata have all of these features because they share the same semantics as IMDS. In formalism, the unified system definition has two views: the server view of the cooperating distributed nodes and the agent view of the migrating agents performing distributed computations. The automata have two formally equivalent forms that reflect two views: Server DA3 for observing servers exchanging messages, and Agent DA3 for tracking agents, which visit individual servers in their progress of distributed calculations. We present the DA3 formulation based on the IMDS formalism and their application to design and verify distributed systems in the Dedan environment. DA3 formalism is compared with other concepts of distributed automata known from the literature.

D-Cloud

2015 ◽  
pp. 2307-2322
Author(s):  
Toshihiro Hanawa ◽  
Mitsuhisa Sato
Keyword(s):  
Distributed Systems ◽  
Software Testing ◽  
Distributed System ◽  
Test Procedure ◽  
System Configuration ◽  
Test Scenario ◽  
Management Software ◽  
Testing Environment ◽  
Cloud Management ◽  
Hardware Faults

Various information systems are widely used in the information society era, and the demand for highly dependable system is increasing year after year. However, software testing for such a system becomes more difficult due to the enlargement and the complexity of the system. In particular, it is often difficult to test parallel and distributed systems in the real world after deployment, although reliable systems, such as high-availability servers, are parallel and distributed systems. To solve these problems, the authors propose a software testing environment for dependable parallel and distributed system using the cloud computing technology, named D-Cloud. D-Cloud consists of the cloud management software as the role of the resource management, and a lot of virtual machine monitors with fault injection facility in order to simulate hardware faults. In addition, D-Cloud introduces the scenario manager, and it makes a number of different tests perform automatically. Currently, D-Cloud is realized by the use of Eucalyptus as the cloud management software. Furthermore, the authors introduce FaultVM based on QEMU as the virtualization software, and D-Cloud frontend that interprets test scenario, constructs test environment, and dispatches commands. D-Cloud enables automating the system configuration and the test procedure as well as performing a number of test cases simultaneously and emulating hardware faults flexibly. This chapter presents the concept and design of D-Cloud, and describes how to specify the system configuration and the test scenario. Furthermore, the preliminary test example as the software testing using D-Cloud is presented. As the result, the authors show that D-Cloud allows easy setup of the environment, and to test the software testing for the distributed system.

XERIS/APEX

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.

Performability Modeling of Distributed Systems and Its Formal Methods Representation

2020 ◽  
pp. 203-233
Author(s):  
Razib Hayat Khan
Keyword(s):  
Complex System ◽  
Quantitative Analysis ◽  
Functional Properties ◽  
Distributed System ◽  
System Performance ◽  
Early Stage ◽  
Behavioral Changes ◽  
Design Development ◽  
Modeling Framework ◽  
System Components

A distributed system is a complex system. Developing complex systems is a demanding task when attempting to achieve functional and non-functional properties such as synchronization, communication, fault tolerance. These properties impose immense complexities on the design, development, and implementation of the system that incur massive effort and cost. Therefore, it is vital to ensure that the system must satisfy the functional and non-functional properties. Once a distributed system is developed, it is very difficult and demanding to conduct any modification in its architecture. As a result, the quantitative analysis of a complex distributed system at the early stage of the development process is always an essential and intricate endeavor. To meet the above challenge, this chapter introduces an extensive framework for performability evaluation of a distributed system. The goal of the performability modeling framework is to consider the behavioral change of the system components due to failures. This reveals how such behavioral changes affect the system performance.

Distributed system simulation using infinite product expansions

SIMULATION ◽  
1970 ◽  
Vol 15 (6) ◽  
pp. 255-263 ◽  
Author(s):  
R.E. Goodson
Keyword(s):  
Distributed Systems ◽  
Distributed System ◽  
Transfer Functions ◽  
System Simulation ◽  
Infinite Product ◽  
Characteristic Roots

Infinite product expansions for the transcendental terms in the transfer functions for linear distributed systems are developed. Simulation of the dynamic re sponse of such systems is indicated, using the product expansion. Comparisons are made between the classi cal eigenvalue and product expansion approximations. It is concluded that the product expansion is an ex tremum transient-amplitude-preserving approximation based on the correct characteristic roots.

A THREE-ROUND ADAPTIVE DIAGNOSTIC ALGORITHM IN A DISTRIBUTED SYSTEM MODELED BY DUAL-CUBES

2014 ◽  
Vol 25 (02) ◽  
pp. 125-139 ◽  
Author(s):  
JHENG-CHENG CHEN ◽  
CHIA-JUI LAI ◽  
CHANG-HSIUNG TSAI
Keyword(s):  
Distributed Systems ◽  
Distributed System ◽  
Diagnostic Algorithm ◽  
Building Blocks ◽  
Diagnostic Approach ◽  
Diagnostic Model ◽  
Test Results ◽  
Spanning Subgraph ◽  
Test Result ◽  
Distributed Computer Systems

Problem diagnosis in large distributed computer systems and networks is a challenging task that requires fast and accurate inferences from huge volumes of data. In this paper, the PMC diagnostic model is considered, based on the diagnostic approach of end-to-end probing technology. A probe is a test transaction whose outcome depends on some of the system's components; diagnosis is performed by selecting appropriate probes and analyzing the results. In the PMC model, every computer can execute a probe to test a dedicated system's components. Furthermore, any test result reported by a faulty probe station is unreliable and the test result reported by fault-free probe station is always correct. The aim of the diagnosis is to locate all faulty components in the system based on collection of the test results. A dual-cube DC(n) is an (n + 1)-regular spanning subgraph of a (2n + 1)-dimensional hypercube. It uses n-dimensional hypercubes as building blocks and returns the main desirable properties of the hypercube so that it is suitable as a topology for distributed systems. In this paper, we first show that the diagnosability of DC(n) is n + 1 and then show that adaptive diagnosis is possible using at most 22n+1 + n tests for a 22n+1-node distributed system modeled by dual-cubes DC(n) in which at most n + 1 processes are faulty. Furthermore, we propose an adaptive diagnostic algorithm for the DC(n) and show that it diagnoses the DC(n) in three testing rounds and at most 22n+1 + O(n3) tests, where each node is scheduled for at most one test in each round.

Port-Based Modeling of Distributed-Lumped Parameter Systems

2010 ◽  
Vol 164 ◽  
pp. 183-188
Author(s):  
Cezary Orlikowski ◽  
Rafał Hein
Keyword(s):  
Distributed Systems ◽  
Transfer Function ◽  
Distributed System ◽  
Function Method ◽  
Input Data ◽  
Distributed Parameter ◽  
Transfer Function Method ◽  
Lumped Parameter ◽  
Concise Representation ◽  
Distributed Transfer Function

This paper presents a uniform, port-based approach for modeling of both lumped and distributed parameter systems. Port-based model of the distributed system has been defined by application of bond graph methodology and distributed transfer function method (DTFM). The proposed approach combines versatility of port-based modeling and accuracy of distributed transfer function method. A concise representation of lumped-distributed systems has been obtained. The proposed method of modeling enables to formulate input data for computer analysis by application of DTFM.

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