A novel bio-inspired routing algorithm based on ACO for WSNs

The methods to achieve efficient routing in energy constrained wireless sensor networks (WSNs) is a fundamental issue in networking research. A novel approach of ant colony optimization (ACO) algorithm for discovering the optimum route for information transmission in the WSNs is proposed here for optimization and enhancement. The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. Utilizing the novel technique and considering both the node mobility and the existing energy of the nodes, an optimal route and best cost from the originating node to the target node can be detected. The proposed algorithm has been simulated and verified using MATLAB and the simulation results demonstrate that new ACO based algorithm achieved improved performance, about 30% improvement compared with the traditional ACO algorithm, and faster convergence to determine the best cost route, and recorded an improvement in the energy consumption of the nodes per transmission

A noble approach of ACO algorithm for WSN

In energy compelled wireless sensor networks (WSNs), the means by which to perform effectual routing is among the main focuses. A noble approach of ant colony optimization (ACO) algorithm for discovering the optimum route in the WSNs for data transmission is proposed here for enhancement and optimization considering the issue of path selection to reach the nodes. Using the proposed ACO algorithm and considering both the node mobility and the existing energy of the nodes, an optimum route and best cost from the originating node to the target node can be detected. The proposed algorithm has been simulated and verified utilizing MATLAB and the simulation results demonstrate that new ant colony optimization based algorithm can achieve better performance and faster convergence to determine the best cost route

Energy-efficient scalable routing protocol based on ACO for WSNS

Efficient routing is an essential requirement for the design of wireless sensor network (WSN) protocols to overcome inherent challenges and to meet hardware and resource constraints. An energy-efficient scalable routing algorithm based on ant colony optimization (ACO) for WSNs is presented here to find the optimal path of data transmission while consuming less energy leading to increase of network’s lifetime. Most of the existing ACO based routing algorithms are designed on the assumption that the sensor nodes and the sinks are stationary and do not consider the overhead of mobility and the current node energy is not considered, which will prompt sudden passing of certain nodes. To overcome the existing problem of accommodating node mobility, reducing initialization time for ant based routing algorithm and to maintain scalability in WSN for time critical applications, an ACO based WSN routing algorithm has been proposed and analyzed in this paper. The proposed algorithm has been simulated and verified utilizing MATLAB. The evaluation results demonstrate that it has reduced energy consumption, almost 50% less consumed energy even with the increasing number of nodes, compared with the traditional ACO and an existing ant-based routing algorithm. Moreover, it increases the nodes’ lifetime and lifetime of the network

Efficient and scalable ant colony optimization based WSN routing protocol for IoT

IoT integrates and connects intelligent devices or objects with varied architectures and resources. The number of IoT devices is growing exponentially. Due to the massive wave of IoT objects, their diversity and heterogeneity among their architectures, the existing communication protocols for wireless networks become ineffective in the context of IoT. Wireless Sensor Network (WSN) has the potential to be integrated to the internet of things (IoT). The issues of the routing of WSNs impose nearly similar prerequisites for IoT routing technique. Most of the traditional routing protocols are not appropriate for WSNs and IoT because of resource constraints, computational overhead and environmental interference and do not take into account the different factors affecting energy parameter and do not accommodate node mobility. Routing algorithms must ensure the data transmission in an efficient way, having proper knowledge of the IoT system. For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. The proposed routing algorithm is simulated using MATLAB for performance evaluations. The evaluation results have recorded an improvement in conservation of energy, of almost 50% less consumed energy even with an increase in the number of nodes, by comparing with an existing routing technique based on ant system, a current routing protocol for IoT and the conventional ACO algorithm. © 2020 ASTES Publishers. All rights reserved

Design of a Wireless Data Transmission Protocol for Underwater Acoustic Networks

In the present world underwater acoustic sensor network (UWSN) is a new research area and currently quite challenging in terms of limited bandwidth, low data rates and multipath propagation & high equipment costs. Most of the research works are stalled by some fundamental factors. For example, high cost of underwater networking experiments as well as lack of portable devices to conduct experiments. In this paper, a new underwater data transmission protocol is proposed to promote experimental research works and to form an underwater acoustic sensor network in which data is transmitted by DTMF tones. The total system consists of a portable transmitter and a receiver. On the transmission module user input will be encoded into DTMF tones, and these tones are generated automatically using a microcontroller. The tone signal is modulated and then transmitted via an acoustic transmitter in form of acoustic waves. On the receiver module these acoustic waves are received via low cost hydrophones which have the ability to capture sound signal in underwater condition. The received signal is decoded into digital binary digits using a DTMF decoder. The decoded digits are combined and the corresponding ASCII character is shown. This portable device can be operated using battery as low power is required to transmit data. The system requires very low power and hence ensures longer battery life

Development of approximate prediction model for 3-DOF helicopter and benchmarking with existing controllers

Recent trend of living is getting modernized rapidly by the involvement of automatic systems. Within the aviation industry, automatic systems had become heavily reliable by the end of the nineteen centuries. The systems usually require controllable devices with desired control algorithm known as controller. Controllers can be replaced with, almost every mechanical automation aspect where, safety is a serious issue. But it is not easy to adapt a controller with a specific model at the beginning. It is important to predict the model before a controller works on the model and the controller parameters need to be adapted to get maximum efficiency. A 3-DOF (Three Degrees of Freedom) airframe model is an advanced benchmark model of real 3-DOF helicopter. It has the same uncommon model dynamics with nonlinearities, strong duel motor cross coupling system, uncertain characteristics, disturbances dependent, unmodeled dynamics and many more. The 3-DOF airframe model is a well-known platform for controller performance benchmarking. This research paper shows the development of an approximate prediction model of a Three Degrees of Freedom helicopter model and uses the proposed approximate model to observe the performance of an existent hybrid controller. The hybrid controller is the combination of two different controllers named Quantitative Feedback Theory (QFT) controller and Adaptive controller.To achieve the research objective, the proposed mathematical model of this airframe was used to develop transfer function and simulate with the hybrid controller in MATLAB. The performance of the controller based on the proposed heliframe model of 3-DOF helicopter have also been reported added within this paper

A trust aware secure ant colony optimization based routing algorithm for Internet of Things

With the rapid spread of Internet of Things (IoT) systems enhancing the development of IoT applications, the issue of designing a secure routing algorithm for IoT, including reasonable trust management, has attracted more and more research attention. The unique characteristics of IoT networks make them vulnerable to attacks due to the resource constrained nature of IoT and the complex distribution of the network. Moreover, the sensors deployed in these kinds of networks are also energy-constrained. It is a challenging task to implement security in IoT networks when the design consideration comprises light weighted security mechanisms and routing protocols due to the insight that security is pricy regarding memory, computational power, and CPU cycles. The adoption of bio-inspired approaches contributes to discovering the optimal path for IoT routing by modeling the cognitive behavior of insect colonies to attain security cost-effectively. For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. Implemented in MATLAB, the assessment results of the proposed routing algorithm are benchmarked to demonstrate that it has minimized the average energy consumption by nearly 50% even as the number of nodes has increased compared to the existing standard and secure routing protocols

A secure trust aware ACO-Based WSN routing protocol for IoT

The Internet of Things (IoT) is the evolving paradigm of interconnectedness of objects with varied architectures and resources to provide ubiquitous and desired services. The popularization of IoT-connected devices facilitating evolution of IoT applications does come with security challenges. The IoT with the integration of wireless sensor networks possess a number of unique characteristics, so the implementation of security in such a restrictive environment is a challenging task. Due to the perception that security is expensive in terms of computation, power and user-interface components, and as sensor nodes or low-power IoT objects have limited resources, it is desired to design security mechanisms especially routing protocols that are light weighted. Bio-inspired mechanisms are shown to be adaptive to environmental variations, robust and scalable, and require less computational and energy resources for designing secure routing algorithms for distributed optimization. In IoT network, the malicious intruders can exploit the routing system of the standardized routing protocol, e.g., RPL (The Routing Protocol for Low-Power and Lossy Networks), that does not observe the node’s routing behavior prior to data forwarding, and can launch various forms of routing attacks. To secure IoT networks from routing attacks, a secure trust aware ACO-based WSN routing protocol for IoT is proposed here that establishes secure routing with trustworthy nodes. The trust evaluation system, is enhanced to evaluate the node trust value, identify sensor node misbehavior, and maximize energy conservation. The performance of the proposed routing algorithm is demonstrated through MATLAB. Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT

Secure ACO-Based Wireless Sensor Network Routing Algorithm for IoT

The problem of developing effective and secure routing protocols has drawn more interest in network research with the popularization of IoT-connected devices. The perception of ensuring security is expensive in terms of computation, power and user-interface components because of low-power IoT objects or sensor nodes. Secret keys distribution schemes are computationally expensive and require more resources. Rather, bio-inspired mechanisms are considered more robust as they offer optimal and inexpensive solutions for designing secure routing algorithms for their inherent adaptable and scalable features. Moreover, trusted neighbor discovery is a crucial task. That is why a complementary security measure, trust evaluation system, is adopted here. In this paper, a secure bio-inspired WSN (Wireless Sensor Network) routing protocol based on ant colony optimization (ACO) algorithm for IoT has been proposed and analyzed to find secure and optimal path that is energy-efficient as well as aiming at providing trust in IoT environment. The performance of the proposed routing algorithm is evaluated utilizing MATLAB. The assessment results indicate that it can find the forwarding path with comparatively low cost in the premise of ensuring security and has minimized the average energy consumption by nearly 50% even as the number of nodes has increased, when compared with the traditional ACO algorithm, an existing ant colony based routing algorithm and a current routing protocol for IoT