A Hybrid Swarm Intelligence Algorithm for Clustering-Based Routing in Wireless Sensor Networks

2019 ◽  
Vol 29 (10) ◽  
pp. 2050163 ◽  
Author(s):  
Amirhossein Barzin ◽  
Ahmad Sadegheih ◽  
Hassan Khademi Zare ◽  
Mahbooeh Honarvar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Objective Function ◽  
Routing Protocol ◽  
Wireless Sensor ◽  
Average Lifetime ◽  
Hybrid Swarm ◽  
Energy Efficient Routing ◽  
Multi Objective ◽  
Nature Inspired Algorithm

Wireless sensor networks (WSNs) comprise a large number of tiny sensing nodes, which are battery-powered with limited energy. An energy-efficient routing protocol is of utmost importance to prolong the network lifetime. Clustering is the most common technique to balance energy consumption among all nodes, while minimizing traffic and overhead during the data transmission phases. In this paper, a Multi-Objective nature-inspired algorithm based on Shuffled frog-leaping algorithm and Firefly Algorithm (named MOSFA) as an adaptive application-specific clustering-based multi-hop routing protocol for WSNs is proposed. MOSFA’s multi-objective function regards different criteria (e.g., inter- and intra-cluster distances, the residual energy of nodes, distances from the sink, overlap, and load of clusters) to select appropriate cluster heads at each round. Moreover, another multi-objective function is proposed to select the forwarder nodes in the routing phase. The controllable parameters of MOSFA in both clustering and multi-hop phases can be adaptively tuned to achieve the best performance based on the network requirements according to the specific application. Simulation results demonstrate average lifetime improvements of 182%, 68%, 30%, and 28% when compared with LEACH, ERA, SIF, and FSFLA, respectively, in different network scenarios.

An Evolutionary Mobility Aware Multi-Objective Hybrid Routing Algorithm for Heterogeneous WSNs

2020 ◽  
pp. 221-237
Author(s):  
Nandkumar Prabhakar Kulkarni ◽  
Neeli Rashmi Prasad ◽  
Ramjee Prasad
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Hybrid Routing ◽  
Multi Objective ◽  
Mobile Wireless Sensor ◽  
Average Energy Consumption ◽  
Hybrid Routing Protocol

Researchers have faced numerous challenges while designing WSNs and protocols in numerous applications. Amongst all sustaining connectivity and capitalizing on the network lifetime is a serious deliberation. To tackle these two problems, the authors have considered Mobile Wireless Sensor Networks (MWSNs). In this paper, the authors put forward an Evolutionary Mobility aware multi-objective hybrid Routing Protocol for heterogeneous wireless sensor networks (EMRP). EMRP selects the optimal path from source node to sink by means of various metrics such as Average Energy consumption, Control Overhead, Reaction Time, LQI, and HOP Count. The Performance of EMRP when equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-Objective Routing Algorithm (DyMORA) using parameters such as Average Residual Energy (ARE), Delay and Normalized Routing Load. EMRP improves AES by a factor of 4.93% as related to SHRP and 5.15% as related to DyMORA. EMRP has a 6% lesser delay as compared with DyMORA.

scholarly journals A PSO-Based Uneven Dynamic Clustering Multi-Hop Routing Protocol for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1835 ◽  
Author(s):  
Ruan ◽  
Huang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Energy Efficient Routing

Since wireless sensor networks (WSNs) are powered by energy-constrained batteries, many energy-efficient routing protocols have been proposed to extend the network lifetime. However, most of the protocols do not well balance the energy consumption of the WSNs. The hotspot problem caused by unbalanced energy consumption in the WSNs reduces the network lifetime. To solve the problem, this paper proposes a PSO (Particle Swarm Optimization)-based uneven dynamic clustering multi-hop routing protocol (PUDCRP). In the PUDCRP protocol, the distribution of the clusters will change dynamically when some nodes fail. The PSO algorithm is used to determine the area where the candidate CH (cluster head) nodes are located. The adaptive clustering method based on node distribution makes the cluster distribution more reasonable, which balances the energy consumption of the network more effectively. In order to improve the energy efficiency of multi-hop transmission between the BS (Base Station) and CH nodes, we also propose a connecting line aided route construction method to determine the most appropriate next hop. Compared with UCCGRA, multi-hop EEBCDA, EEMRP, CAMP, PSO-ECHS and PSO-SD, PUDCRP prolongs the network lifetime by between 7.36% and 74.21%. The protocol significantly balances the energy consumption of the network and has better scalability for various sizes of network.

scholarly journals An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3887 ◽  
Author(s):  
Deep Kumar Bangotra ◽  
Yashwant Singh ◽  
Arvind Selwal ◽  
Nagesh Kumar ◽  
Pradeep Kumar Singh ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Algorithm ◽  
Relay Node ◽  
Healthcare Services ◽  
Opportunistic Routing ◽  
Wireless Sensor ◽  
Energy Efficient Routing

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.

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