scholarly journals Distributed System Behavior Modeling with Ontologies, Rules, and Message Passing Mechanisms

2015 ◽  
Vol 44 ◽  
pp. 373-382 ◽  
Author(s):  
Mark Austin ◽  
Parastoo Delgoshaei ◽  
Alan Nguyen
Keyword(s):  
Distributed System ◽  
Message Passing ◽  
Behavior Modeling ◽  
System Behavior

scholarly journals An Executive Approach to Achieve Mutual Exclusion in Distributed Data using Topology and Association Rule.

2014 ◽  
Vol 13 (6) ◽  
pp. 4537-4542
Author(s):  
Mr. Anurag Singh ◽  
Dr. Amod Tiwari
Keyword(s):  
Distributed System ◽  
Association Rule ◽  
Message Passing ◽  
Computer Network ◽  
Mutual Exclusion ◽  
Distributed Data ◽  
Worst Case ◽  
New Approach ◽  
And Topology ◽  
Minimum Number

In this paper, a new approach is being proposed to achieve mutual exclusion in distributed system using computer network and topology of nth nodes. In this executive approach nodes communicate among themselves using message passing technique. In this executive approach, distributed system with n nodes is logically partitioned into number of sub distributed system having only m½ nodes, where m is obtained by adding a minimum number in n to make it next perfect square number only if n is not a perfect square. Proposed algorithm is a Token based approach and achieves token optimally in 2 messages only for the best case and in worst case a node achieves token in n messages only.

scholarly journals CONSISTENCY OF DISTRIBUTED SYSTEM WITH ACTIVE INITIATOR PROCESS WITHOUT USELESS CHECKPOINTS

2014 ◽  
pp. 92-99
Author(s):  
N. P. Gopalan ◽  
K. Nagarajan
Keyword(s):  
Fault Tolerance ◽  
Distributed System ◽  
Message Passing ◽  
Domino Effect ◽  
Exchange Of Information ◽  
Global Consistency ◽  
Software Fault Tolerance ◽  
Software Fault ◽  
The One ◽  
Active Initiator

Checkpointing mechanism is the one of the best attractive approach for providing software fault tolerance in distributed message passing systems. This paper aims to implement a distributed checkpointing technique, which eliminates the drawbacks of the centralized approach like “domino effect”, “useless checkpoint” (checkpoints that do not contribute to global consistency), and “hidden and zigzag” dependencies. The proposed checkpointing protocol has a checkpoint initiator, but, coordination among the local checkpoints is done in a distributed fashion. This guaranty that no message would be lost in case of failure occurs, has been maintained in this work by exchange of information among the processes. However, there is no central checkpoint initiator, but each of the processes takes turn to act as an initiator. Processes take local checkpoints only after being notified by the initiator. The processes synchronize their activities of the current checkpointing interval before finally committing their checkpoints. Thus, the checkpointing pattern described in this paper takes only those checkpoints that will contribute to the consistent global snapshot thereby eliminating the number of useless checkpoints.

scholarly journals A LTS Approach to Control in Event-B

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Han Peng ◽  
Chenglie Du ◽  
Lei Rao ◽  
Fu Chen
Keyword(s):  
Flow Model ◽  
State Machine ◽  
Transition System ◽  
Control Flow ◽  
Behavior Modeling ◽  
System Model ◽  
Behavior Model ◽  
System Behavior ◽  
Labeled Transition System ◽  
Event Trace

In Event-B, people need to use control variables to constrain the order of events, which is a time-consuming and error-prone process. This paper presents a method of combining labeled transition system and iUML-B to complete the behavior modeling of system, which is more convenient and practical for engineers who are accustomed to using the automaton to build a system behavior model. First, we use labeled transition system to establish the behavior model of the system. Then we simulate and verify the event traces of the labeled transition system behavior model. Finally, we convert labeled transition system model into iUML-B state machine and use it to generate the corresponding control flow model. We use Abrial’s bounded retransmission protocol to demonstrate the practicality of our approach. The simulation results show that the system behavior model generated by the iUML-B state machine has the same event trace as the corresponding labeled transition system model.

Geometric Message-Filtering Protocols for Distributed Multiagent Environments

2004 ◽  
Vol 13 (3) ◽  
pp. 279-295 ◽  
Author(s):  
Alexander Goldin ◽  
Craig Gotsman
Keyword(s):  
Virtual Environments ◽  
Distributed System ◽  
Message Passing ◽  
The Other ◽  
Small Subset ◽  
Main Challenge ◽  
The Status ◽  
Multi Agent ◽  
First Time ◽  
2D Space

Message filtering is important for distributed multiagent systems, where a large number of dynamic agents participate in the system activity, but a typical agent is interested in only a very small dynamic subset of the other agents. The agent must be constantly informed on the status of this subset, and this is achieved by message passing between relevant agents. Message filtering is required to reduce the communications load on the system, which could be prohibitive if each agent must communicate with all others in order to obtain the information it needs. This paper deals with the case of a multiagent virtual environment, where each agent has a location in 2D space, and is interested in a small subset of the other agents, either those within a fixed range—as treated by previous authors, or the k other agents nearest to it—treated here for the first time. Furthermore, we treat the case of a fully distributed system, where no central server(s) are available to coordinate between the agents. The main challenge is then to design protocols that perform significant message filtering, yet enable each agent to maintain a consistent image of the other agents it is interested in. These protocols are useful in multi-agent games, simulations, and other virtual environments in which the geometric relationships between agents are important. They could also be useful for mobile-commerce and cellphone-based gaming applications.

System Behavior Modeling As a Basis for Advanced Failure Modes and Effects Analysis

1996 ◽  
Author(s):  
Charles F. Eubanks ◽  
Steven Kmenta ◽  
Kosuke Ishii
Keyword(s):  
Conceptual Design ◽  
Failure Modes ◽  
Behavior Modeling ◽  
Behavior Model ◽  
System Behavior ◽  
Early Stages ◽  
Device Operation

Abstract This paper presents a method for developing a device behavior model to enhance reliability at the early stages of conceptual design. The model facilitates a semi-automated advanced failure modes and effects analysis (FMEA). The model performs analyses and simulations of device behavior, reasons about conditions that depart from desired behaviors, and analyzes the results of those departures. The proposed method rigorously specifies pre- and post-conditions, yet is flexible in the syntax of device operation. The paper shows how the method can capture failures normally missed by existing FMEA methods. An automatic ice maker serves as an example application.

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