Open Network Emulator: A Parallel Direct Code Execution Network Simulator

2012 ◽  
Author(s):  
Vedavyas Duggirala ◽  
Srinidhi Varadarajan
Keyword(s):  
Network Simulator ◽  
Open Network ◽  
Network Emulator

Optimizing Time-multiplexing Raster Cellular Neural Network simulator using genetic algorithms with RK8(6)

2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Cellular Neural Network ◽  
Network Simulator

Link-Level Simulator for Wireless local Area Network

2018 ◽  
Vol 6 (7) ◽  
pp. 314
Author(s):  
Chaithra. H. U ◽  
Vani H.R
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area Networks ◽  
Local Area ◽  
Long Term Evolution ◽  
Wireless Local Area Networks ◽  
Area Network ◽  
Network Simulator ◽  
Term Evolution

Now a days in Wireless Local Area Networks (WLANs) used in different fields because its well-suited simulator and higher flexibility. The concept of WLAN  with  advanced 5th Generation technologies, related to a Internet-of-Thing (IOT). In this project, representing the Network Simulator (NS-2) used linked-level simulators for Wireless Local Area Networks and still utilized IEEE 802.11g/n/ac with advanced IEEE 802.11ah/af technology. Realization of the whole Wireless Local Area Networking linked-level simulators inspired by the recognized Vienna Long Term Evolution- simulators. As a outcome, this is achieved to link together that simulator to detailed performances of Wireless Local Area Networking with Long Term Evolution, operated in the similar RF bands. From the advanced 5th Generation support cellular networking, such explore is main because different coexistences scenario can arise linking wireless communicating system to the ISM and UHF bands.

Virtualized Fog Network with Load Balancing for IoT based Fog-to-Cloud

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary
Keyword(s):  
Load Balancing ◽  
Packet Loss ◽  
Fog Computing ◽  
Transport Protocol ◽  
Network Simulator ◽  
Huge Number ◽  
Message Queue ◽  
Limited Bandwidth ◽  
Cloud Architecture ◽  
Fog Network

Fog Computing is a new concept made by Cisco to provide same functionalities of Cloud Computing but near to Things to enhance performance such as reduce delay and response time. Packet loss may occur on single Fog server over a huge number of messages from Things because of several factors like limited bandwidth and capacity of queues in server. In this paper, Internet of Things based Fog-to-Cloud architecture is proposed to solve the problem of packet loss on Fog server using Load Balancing and virtualization. The architecture consists of 5 layers, namely: Things, gateway, Fog, Cloud, and application. Fog layer is virtualized to specified number of Fog servers using Graphical Network Simulator-3 and VirtualBox on local physical server. Server Load Balancing router is configured to distribute the huge traffic in Weighted Round Robin technique using Message Queue Telemetry Transport protocol. Then, maximum message from Fog layer are selected and sent to Cloud layer and the rest of messages are deleted within 1 hour using our proposed Data-in-Motion technique for storage, processing, and monitoring of messages. Thus, improving the performance of the Fog layer for storage and processing of messages, as well as reducing the packet loss to half and increasing throughput to 4 times than using single Fog server.

A Low-Cost, IP-Based Mobile Network Emulator (MNE)

2003 ◽  
Author(s):  
Joseph P. Macker ◽  
William Chao ◽  
Jeffrey W. Weston
Keyword(s):  
Low Cost ◽  
Mobile Network ◽  
Network Emulator

Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation

2014 ◽  
Author(s):  
Curtis Tade ◽  
Venkat Dasari ◽  
Vinod K. Mishra
Keyword(s):  
Network Environment ◽  
Open Network

SPREAD - A Routing Protocol to Meet End-to-end Adjusted Deadline in Real Time Wireless Sensor Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 63-78
Author(s):  
Neetika Jain ◽  
Sangeeta Mittal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Routing Protocol ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Packet Delivery ◽  
High Data ◽  
Hard Real Time

Background: Real Time Wireless Sensor Networks (RT-WSN) have hard real time packet delivery requirements. Due to resource constraints of sensors, these networks need to trade-off energy and latency. Objective: In this paper, a routing protocol for RT-WSN named “SPREAD” has been proposed. The underlying idea is to reserve laxity by assuming tighter packet deadline than actual. This reserved laxity is used when no deadline-meeting next hop is available. Objective: As a result, if due to repeated transmissions, energy of nodes on shortest path is drained out, then time is still left to route the packet dynamically through other path without missing the deadline. Results: Congestion scenarios have been addressed by dynamically assessing 1-hop delays and avoiding traffic on congested paths. Conclusion: Through extensive simulations in Network Simulator NS2, it has been observed that SPREAD algorithm not only significantly reduces miss ratio as compared to other similar protocols but also keeps energy consumption under control. It also shows more resilience towards high data rate and tight deadlines than existing popular protocols.

Model of Trust Monitoring and Updating Based on Dynamic Weighted Allocation

2019 ◽  
Vol 12 (1) ◽  
pp. 79-85
Author(s):  
Bin Hu ◽  
Yuemin Wu ◽  
Min Sun ◽  
Zheng Bang Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Information Entropy ◽  
Network Environment ◽  
Mathematical Methods ◽  
Efficient Operation ◽  
Open Network ◽  
Dynamic Trust ◽  
Effective Synthesis ◽  
Effectiveness And Efficiency ◽  
And Performance

Backgrounds: In order to guarantee safe and efficient operation interaction in open network environment, a new dynamic trust monitoring and updating model based on behavior context is proposed in this paper. Methods: Setting four behavior attributes such as security, availability, reliability and performance. Then utilizing the fuzzy clustering and information entropy mathematical methods to carry out the effective synthesis on such attributes. Conclusion: The effectiveness and efficiency of the schema are verified by simulation.

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