scholarly journals A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4873
Author(s):  
Biao Xu ◽  
Minyan Lu ◽  
Hong Zhang ◽  
Cong Pan
Keyword(s):  
Wireless Sensor ◽  
Component Reliability ◽  
Agent Based ◽  
Agent Model ◽  
Cross Domain ◽  
Malware Propagation ◽  
Network Topologies ◽  
Multi Agent ◽  
Agent Characteristics ◽  
Information Domain

A wireless sensor network (WSN) is a group of sensors connected with a wireless communications infrastructure designed to monitor and send collected data to the primary server. The WSN is the cornerstone of the Internet of Things (IoT) and Industry 4.0. Robustness is an essential characteristic of WSN that enables reliable functionalities to end customers. However, existing approaches primarily focus on component reliability and malware propagation, while the robustness and security of cascading failures between the physical domain and the information domain are usually ignored. This paper proposes a cross-domain agent-based model to analyze the connectivity robustness of a system in the malware propagation process. The agent characteristics and transition rules are also described in detail. To verify the practicality of the model, three scenarios based on different network topologies are proposed. Finally, the robustness of the scenarios and the topologies are discussed.

A Study on the Agent-Based Vehicles Dispatching Optimization at Container Terminals

2012 ◽  
Vol 241-244 ◽  
pp. 1745-1750
Author(s):  
Nan Nan Yan ◽  
Di Zheng
Keyword(s):  
Decision Support ◽  
Analytic Hierarchy Process ◽  
Container Terminal ◽  
Container Terminals ◽  
Analytic Hierarchy ◽  
Agent Based ◽  
Agent Model ◽  
Contract Net ◽  
Multi Agent ◽  
Hierarchy Process

This paper mainly concentrated on the method of improving the dispatching trucks working at a container terminal and built the multi-agent model for the dispatching job. The contract net protocol was taken as the communication ones among agents, and the analytic hierarchy process was also applied for the decision support for container trucks dispatching.

Multi-Agent Based Simulation Model for Rail Transit Evacuation Process

2014 ◽  
Vol 1030-1032 ◽  
pp. 2044-2049
Author(s):  
Can Can Zhao ◽  
Xiao Hong Guo ◽  
Juxihong Julaiti ◽  
Jie Wang
Keyword(s):  
Simulation Model ◽  
Rail Transit ◽  
Evacuation Simulation ◽  
Transit System ◽  
Agent Based ◽  
Agent Model ◽  
Agent Simulation ◽  
Multi Agent ◽  
The Military ◽  
Specific Definition

In order to analyze the evacuation behaviors and optimize evacuation strategies for rail transit system, an evacuation agent centered simulation model was proposed. Firstly, by considering the attributes, status and decision-making behaviors of evacuation personnel, the evacuation agent model was established, and the running principle as well as construction process of multi-agent simulation model was discussed. Then, the specific definition and design for the agent attributes and evacuation behavior protocol were provided. Finally, based on the simulation model proposed, an evacuation simulation platform for the military museum station of Beijing subway line 9 was established by using REPAST and JAVA, several evacuation strategies were tested and optimized.

Multi-Agent-Based Acoustic Sensor Node Deployment in Underwater Acoustic Wireless Sensor Networks

2020 ◽  
Vol 13 (4) ◽  
pp. 136-155
Author(s):  
Basaprabhu S. Halakarnimath ◽  
Ashok V. Sutagundar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Propagation Loss ◽  
Wireless Sensor ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Agent Based ◽  
Node Deployment ◽  
Multi Agent

The deployment of acoustic sensor nodes in 3-D underwater acoustic wireless sensor networks (UAWSN) is a difficult task due to various aquatic conditions and physical obstacles. This work proposes multi-agent-based acoustic sensor node deployment (MASD) to deploy the acoustic nodes at ideal positions to enhance coverage and seamless connectivity. The proposed scheme works is threefold: 1) AUV initiates random walk in the network to gather the information and prospective common reference points; 2) the base station gets this information through surface buoys and computes the routing path, feasible locations for deploying new nodes; and 3) AUV collects this information and follows the path to deploy nodes with the help of agents. The multi-agent-enabled deployment framework (MADF) is proposed to support the deployment process at each level of the proposed MASD scheme. The performance of propagation loss, coverage, and overhead tradeoffs are analyzed to validate the proposed scheme. Mobility issues can be further re-investigated in shallow water as a future direction to the MASD scheme.

AGENT BASED DATA STORAGE AND DISTRIBUTION IN DATA WAREHOUSES

2008 ◽  
Vol 18 (05) ◽  
pp. 597-617 ◽  
Author(s):  
NADER KOLSI ◽  
ABDELAZIZ ABDELLATIF ◽  
KHALED GHEDIRA
Keyword(s):  
Data Warehouse ◽  
Data Storage ◽  
Data Distribution ◽  
Distributed Data ◽  
Agent Based ◽  
Agent Model ◽  
Capacity Limit ◽  
Processing Resources ◽  
Multi Agent ◽  
Distributed Data Warehouse

The data warehouse (DWH) is usually presented as a centralized database. In this paper, we propose a new approach to manage data storage and distribution in a data warehouse environment. This approach deals with the dynamic data distribution of the DWH on a set of servers. The data distribution that we consider is different from the "classical" one which depends on the data use. The distribution in our approach consists in distributing data when the server reaches its storage capacity limit. This distribution assures the scalability and exploits the storage and processing resources available in the organization using the data warehouse. It is worth noting that our approach is based on a multi-agent model mixed with the scalability distribution proposed by the Scalable Distributed Data Structures. The proposed multi-agent model is composed of stationary agent classes: Client, Dispatcher, Domain and Server, and a mobile agent class called Messenger. These agents collaborate and interact to achieve automatically the storage, the splitting (distribution), the redirection and the access operations on the distributed data warehouse. In this paper, we demonstrate the improvements obtained when we have used the multi-agent system and the Messenger agents in the data storage operation.

A survey on agent learning architecture that adopts internet of things and wireless sensor networks

2020 ◽  
pp. 2030002
Author(s):  
T. Joshva Devadas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Swot Analysis ◽  
Wireless Sensor ◽  
Agent Architectures ◽  
Agent Based ◽  
Intelligent Software ◽  
Agent Learning ◽  
Multi Agent

Trustworthy and reliable applications built using intelligent software agents aim to provide improved performance using its characteristics. Agents introduced in various architectures represent its functionality as functional elements of the architecture and shows the interaction between other components present in the architecture. The Internet of things (IoT) reveals as a frequent technology that allows accessing the physical objects present in the world. IoT systems utilize wireless sensor network to transmit and receive data by establishing communication. Wireless Sensor Networks transmits digital signals to the cyber-world for analyzing and processing the information into useful data by either formulating or communicating with the intelligent and innovative system. While talking about IoT and WSN, agents introduced in such environments assist in making decisions quickly by perceiving the input from the environment. The number of agents needed for an application depends upon the complexity of the problem. Multi-Agent architectures discussed in the article describe their association, roles, functionality and interaction. This paper gives a detailed survey of various agent/multi-agent learning architectures introduced over IoT and WSN. Moreover, this survey with the performance and the SWOT analysis on the Agent-based learning architecture helps the reader and paves a way to pursue research on Agent-based architectural deployment over IoT and WSN paradigms.

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