Protruder optimization-based routing protocol for energy efficient routing in Wireless Sensor Networks

2021 ◽  
Vol 17 (2) ◽  
pp. 0-0
Keyword(s):  
Data Aggregation ◽  
Routing Algorithm ◽  
Optimal Path ◽  
Cluster Head ◽  
Optimal Routing ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Window Approach

The energy efficiency problem is addressed using the Cluster Head (CH) formation, data aggregation, and routing techniques. Therefore,an energy-aware routing algorithm named as protruder optimization algorithm is proposed, which boosts the network lifetime through finding the optimal routing path. The proposed protruder optimization is developed with the hybridization of the wave propagator characteristics and weed characteristics in such a way that the global optimal convergence is boosted while selecting the optimal routing path. Moreover, the communication in the network through the optimal path is progressed through the optimal CHs selection based on fractional artificial bee colony optimization (FABC) and in turn, the energy minimization problem is aided with data aggregation process using sliding window approach that avoids retransmission of the data. The results of the proposed method are compared with the existing methods on the basis of its performance measures such as energy, alive nodes and throughput.

scholarly journals EARPC – Energy Aware Routing Protocol for Cooperative MIMO Scheme in WSNs

2020 ◽  
Vol 3 ◽  
pp. 22-27
Author(s):  
Kummathi Chenna Reddy ◽  
Geetha D. Devanagavi ◽  
Thippeswamy M. N.
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Levels ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Energy Aware Routing

Wireless sensor networks are typically operated on batteries. Therefore, in order to prolong network lifetime, an energy efficient routing algorithm is required. In this paper, an energy-aware routing protocol for the co-operative MIMO scheme in WSNs (EARPC) is presented. It is based on an improved cluster head selection method that considers the remaining energy level of a node and recent energy consumption of all nodes. This means that sensor nodes with lower energy levels are less likely to be chosen as cluster heads. Next, based on the cooperative node selection in each cluster, a virtual MIMO array is created, reducing uneven distribution of clusters. Simulation results show that the proposed routing protocol may reduce energy consumption and improve network lifetime compared with the LEACH protocol

Meta-Heuristic MOALO Algorithm for Energy-Aware Clustering in the Internet of Things

2021 ◽  
Vol 12 (2) ◽  
pp. 74-93
Author(s):  
Ravi Kumar Poluru ◽  
R. Lokeshkumar
Keyword(s):  
Energy Consumption ◽  
Data Transmission ◽  
Transmission Rate ◽  
Fitness Function ◽  
Shortest Paths ◽  
Cluster Head ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Multi Objective ◽  
Data Transmission Rate

Boosting data transmission rate in IoT with minimized energy is the research issue under consideration in recent days. The main motive of this paper is to transmit the data in the shortest paths to decrease energy consumption and increase throughput in the IoT network. Thus, in this paper, the authors consider delay, traffic rate, and density in designing a multi-objective energy-efficient routing protocol to reduce energy consumption via the shortest paths. First, the authors propose a cluster head picking approach that elects optimal CH. It increases the effective usage of nodes energy and eventually results in prolonged network lifetime with enhanced throughput. The data transmission rate is posed as a fitness function in the multi-objective ant lion optimizer algorithm (MOALOA). The performance of the proposed algorithm is investigated using MATLAB and achieved high convergence, extended lifetime, as well as throughput when compared to representative approaches like E-LEACH, mACO, MFO-ALO, and ALOC.

An Optimal Routing Algorithm for Internet of Things Enabling Technologies

2017 ◽  
Vol 4 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Amol V. Dhumane ◽  
Rajesh S. Prasad ◽  
Jayashree R. Prasad
Keyword(s):  
Genetic Algorithm ◽  
Internet Of Things ◽  
Energy Cost ◽  
High Reliability ◽  
Routing Algorithm ◽  
Optimal Path ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Trust Level ◽  
Enabling Technologies

In Internet of things and its relevant technologies the routing of data plays one of the major roles. In this paper, a routing algorithm is presented for the networks consisting of smart objects, so that the Internet of Things and its enabling technologies can provide high reliability while the transmitting the data. The proposed technique executes in two stages. In first stage, the sensor nodes are clustered and an optimal cluster head is selected by using k-means clustering algorithm. The clustering is performed based on energy of sensor nodes. Then the energy cost of the cluster head and the trust level of the sensor nodes are determined. At second stage, an optimal path will be selected by using the Genetic Algorithm (GA). The genetic algorithm is based on the energy cost at cluster head, trust level at sensor nodes and path length. The resultant optimal path provides high reliability, better speed and more lifetimes.

An Energy Aware Routing Algorithm for WSNs Based on Semi-Static Clustering

2015 ◽  
Vol 752-753 ◽  
pp. 1413-1418
Author(s):  
Tao Du ◽  
Qing Bei Guo ◽  
Kun Zhang ◽  
Kai Wang
Keyword(s):  
Energy Efficiency ◽  
Large Scale ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Routing Algorithms ◽  
Sensor Nodes ◽  
Energy Aware ◽  
Hierarchical Routing ◽  
Static Clustering

Energy efficiency is a key factor to improve WSNs’ performance, and hierarchical routing algorithms are fitter in large scale networks and have more reliability, so they are mostly used to improve the nodes’ energy efficiency now. In this paper, mainly existing hierarchical routing algorithms are introduced, and based on these researches, a new energy efficient hierarchical routing algorithm designed based on energy aware semi-static clustering method is proposed. In this algorithm named EASCA, the nodes’ residual energy and cost of communication would both be considered when clustering. And a special packet head is defined to update nodes’ energy information when transmitting message; to rotate cluster head automatically, a member management scheme is designed to complete this function; and a re-cluster mechanism is used to dynamic adjust the clusters to make sensor nodes organization more reasonable. At last, EASCA is compared with other typical hierarchical routing algorithms in a series of experiments, and the experiments’ result proves that EASCA has obviously improved WSNs’ energy efficiency.

scholarly journals Artificial Bee Colony Optimization Algorithm for Enhancing Routing in Wireless Networks

2021 ◽  
Vol 3 (1) ◽  
pp. 62-71
Author(s):  
Jeena Jacob I. ◽  
Ebby Darney P.
Keyword(s):  
Wireless Networks ◽  
Optimization Algorithm ◽  
Performance Optimization ◽  
Artificial Bee Colony ◽  
Routing Algorithm ◽  
Model Performance ◽  
Specific Model ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Bee Colony Optimization

The throughput of wireless multi-channel networks are enhanced using artificial intelligence algorithm. The performance of the network may be improved while reducing the interference. This technique involves three steps namely creation of wireless environment specific model, performance optimization using the right tools and improvement of routing by selecting the performance indicators cautiously. Artificial bee colony optimization algorithm and its evaluative features positively affects communication in wireless networks. The simple behavior of bee agents in this algorithm assist in making synchronous and decentralized routing decisions. The advantages of this algorithm is evident from the MATLAB simulations. The nature inspired routing algorithm offers improved performance when compared to the existing state-of-the-art models. The simple agent model can improve the performance values of the network. The breadth first search variant is utilized for discovery and deterministic evaluation of multiple-paths in the network increasing the overall routing protocol output.

scholarly journals Energy Efficient Routing Algorithm with Mobile Sink Support for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1494 ◽  
Author(s):  
Jin Wang ◽  
Yu Gao ◽  
Wei Liu ◽  
Arun Kumar Sangaiah ◽  
Hye-Jin Kim
Keyword(s):  
Energy Efficient ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Similar Work ◽  
Sensor Field ◽  
A Chain ◽  
The Greedy Algorithm

Recently, wireless sensor network (WSN) has drawn wide attention. It can be viewed as a network with lots of sensors that are autonomously organized and cooperate with each other to collect, process, and transmit data around targets to some remote administrative center. As such, sensors may be deployed in harsh environments where it is impossible for battery replacement. Therefore, energy efficient routing is crucial for applications that introduce WSNs. In this paper, we present an energy efficient routing schema combined with clustering and sink mobility technology. We first divide the whole sensor field into sectors and each sector elects a Cluster Head (CH) by calculating its members’ weight. Member nodes calculate energy consumption of different routing paths to choose the optimal scenario. Then CHs are connected into a chain using the greedy algorithm for intercluster communication. Simulation results prove the presented schema outperforms some similar work such as Cluster-Chain Mobile Agent Routing (CCMAR) and Energy-efficient Cluster-based Dynamic Routing Algorithm (ECDRA). Additionally, we explore the influence of different network parameters on the performance of the network and further enhance its performance.

scholarly journals Clustered chain founded on ant colony optimization energy efficient routing scheme for under-water wireless sensor networks

2021 ◽  
Vol 11 (6) ◽  
pp. 5197
Author(s):  
Djilali Moussaoui ◽  
Mourad Hadjila ◽  
Sidi Mohammed Hadj Irid ◽  
Sihem Souiki
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Head Rotation ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Energy Efficient Routing

One challenge in under-water wireless sensor networks (UWSN) is to find ways to improve the life duration of networks, since it is difficult to replace or recharge batteries in sensors by the solar energy. Thus, designing an energy-efficient protocol remains as a critical task. Many cluster-based routing protocols have been suggested with the goal of reducing overall energy consumption through data aggregation and balancing energy through cluster-head rotation. However, the majority of current protocols are concerned with load balancing within each cluster. In this paper we propose a clustered chain-based energy efficient routing algorithm called CCRA that can combine fuzzy c-means (FCM) and ant colony optimization (ACO) create and manage the data transmission in the network. Our analysis and results of simulations show a better energy management in the network.

scholarly journals Energy Aware Hierarchal Data Aggregation and Trust Based Data Integrity Verification for WSN

2021 ◽  
Vol 58 (1) ◽  
pp. 5637-5643
Author(s):  
Masthan Ali A.H, Ali Ahammed G.F, Reshman Banu
Keyword(s):  
Data Aggregation ◽  
Cluster Formation ◽  
Cluster Head ◽  
Data Integrity ◽  
Residual Energy ◽  
Optimal Number ◽  
Energy Aware ◽  
Trust Mechanism ◽  
Normal Node ◽  
Wide Range

Currently the demand of wireless sensor networks has gained huge attraction due to its wide range of applications. Generally, these nodes are equipped with limited power resource and deployed in harsh environment where replacing these resources is a tedious task. Due to these issues, minimizing the energy consumption is a prime task to prolong the network lifetime. To overcome the challenging issue of data aggregation we introduced a novel combined mechanism which performs clustering and trust computing process to improve the data aggregation. According to this scheme, we arrange the nodes as normal node, advanced node and super nodes based on their residual energy parameters. The proposed model uses hierarchal scheme where we present a new mechanism for optimal number of cluster formation and cluster head selection. After selecting the cluster head, we apply trust computation scheme which provides sensing trust, link trust and node trust. The node trust is computed as direct and indirect trust. This trust mechanism is used as hop-by-hop manner to maintain he data integrity. The experimental study shows that proposed approach achieves better performance and maintains the security aspects of WSN.  

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