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Cluster-Based Routing Protocol for WSN Using Fusion of Swarm Intelligence and Neural Network
Published in Santosh Kumar Das, Massimiliano Giacalone, Fuzzy Optimization Techniques in the Areas of Science and Management, 2023
Jeevan Kumar, Rajesh Kumar Tiwari, Tapan Kumar Dey, Amit Kumar Singh
The suggested scheme's performance in various simulated scenarios is depicted in this section. For the simulation, the OMNET++ tool was utilized, which supports routing protocols for wireless sensor networks. OMNET++ is a discrete, event-driven network simulator that is object-oriented. Because of its simplicity and adaptability, the OMNET++ network simulator has garnered tremendous appeal among members of the research community. The network simulation allows simulation scripts, also known as simulation scenarios, to be easily created in a language, while still relying on more complex capabilities via C++ code. Several metrics are used to evaluate performance, as shown in Figures 5.5 to 8. All nodes broadcast a message to each other and retain surrounding node information, as shown in Figure 5.5. This data is saved in a routing table. When transferring data packets, this method assists in determining which node is closest to the target node. First, define the source and destination nodes; next, from the routing table and determine the surrounding node information. Compare all nodes with their relevant parameters to determine which is closest to the destination. The data packet is transmitted to the appropriate node that is closest to the destination node. Repeat this process until all data packets have arrived at their destination.
Design Issues, Models, and Simulation Platforms
Published in Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare, Energy Optimization Protocol Design for Sensor Networks in IoT Domains, 2023
Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare
OMNeT++ is a comprehensible, modular C++ simulation and modular discrete network simulation platform for object-oriented purposes primarily to construct network simulators. It has a generic architecture so that it can be used for several domains:Wired network modeling and wireless network modelingprotocol modelingQueueing Network modelingMulti-processor modeling and other distribution hardware structuresHardware architecture validationevaluate complicated software device performance aspectsGenerally, any device that fits the distinct event method can be modeled and simulated conveniently into entities that communicate via message exchange.
Internet of Things for Structural Health Monitoring
Published in Jayantha Ananda Epaarachchi, Gayan Chanaka Kahandawa, Structural Health Monitoring Technologies and Next-Generation Smart Composite Structures, 2016
Aravinda S. Rao, Jayavardhana Gubbi, Tuan Ngo, Priyan Mendis, Marimuthu Palaniswami
Our results were verified using Castalia-3.2 simulator. OMNeT++ is a discrete event simulation environment. It is an extensible, modular, component-based C++ simulation library and framework essentially build simulators [53]. At the core of the OMNeT++, it provides option for component architecture model that can be programmed using C++. At higher level, these components can be linked together (using .NED) [53]. Castalia is a discrete event simulator that runs on OMNeT++ simulation framework. It can be used to simulate WSNs, body area networks and also low-power embedded devices. It is a not specific to any sensor and provides a range of realistic node behaviors. It provides flexibility in its modularity, reliability, and celerity of execution that are partly attributed to OMNeT++ support [37].
Search for parking: A dynamic parking and route guidance system for efficient parking and traffic management
Published in Journal of Intelligent Transportation Systems, 2019
Huajun Chai, Rui Ma, H. Michael Zhang
Simulations are carried out using SUMO and OmNet++. SUMO is a microscopic traffic simulator, which can simulate the network and vehicle movements in the network using various car-following models. OmNet++ is a simulation framework used to simulate computer networks and network protocols. We use it to simulate the online information release mechanism in our framework. See Amoozadeh, Deng, Chuah, Zhang, and Ghosal (2015) and Chai et al. (2017) for more details on the simulation tools. The synthetic network used for the simulation is shown in Figure 2.
Deploying IPv4-only Connectivity across Local IPv6-only Access Networks
Published in IETE Technical Review, 2019
This section investigates some of the important networking performance metrics and compares the performance of the proposed protocol with Address-Plus-Port (A+P), DS-Lite and 4rd protocols. These metrics are Round Trip Delay Time (RTD) and Throughput [33,34]. OMNET++ and INET framework [35] were used as a simulation environment. OMNET++ is a discrete event-driven simulator. INET framework is a package for OMNET++ used to simulate communication networks. It has many models for network-based protocols such as UDP, TCP, IPv4, IPv6, etc. The simulation was intended to prove the validity and study the performance of the D4across6 protocol. The performance of D4across6 was evaluated and compared with the performance of other related protocols in large-scale settings. In order to study the influence of these protocols on the native communication environments (IPv4 network initiates communications with IPv4 peers and IPv6 network initiate communications with IPv6 peers), the performance of all protocols (proposed and existing protocols) was compared with both native IPv4 and IPv6-based networks. The simulation environment handles the network scenario when a dual-stack host is connected to an IPv6-only network, and that host is trying to initiate communications with IPv4-only peers. A synthetic traffic was generated for all experiments using the ReaSE [36] tool. The ReaSE traffic generator tool was used to generate TCP traffic between D46Hs and IPv4-only servers. This tool is used to set up the simulator parameters in all the conducted experiments. For example, it configures traffic parameters for a traffic flow such as packet size, destination IPv4 address, and traffic generation (ON/OFF) in seconds. In all experiments, the simulator was run for 600 seconds. The following subsections analyse the performance of D4across6 using different network performance metrics when varying number of nodes and different packet sizes are used.