MPSICA: An intelligent routing recovery scheme for heterogeneous wireless sensor networks

Ding, Yongsheng; Hu, Yifan; Lü, Cheng

doi:10.1016/j.ins.2015.03.001

Cited by 18 publications

(9 citation statements)

References 32 publications

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“…The energy‐related issues in WSNs have prompted the designing of numerous latest routing strategies, especially clustering techniques or routing strategies for enhancing network lifetime. For the research community, retaining the energy of routing protocols for longer duration is still an open challenge in WSNs 25–37 . The basic thought of clustering in WSNs is to divide the network into a small group of sensor nodes, in which one CH is included; others are the member nodes.…”

Section: Related Workmentioning

confidence: 99%

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Anand

Pandey

2020

Int J Communication

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SummaryWireless sensor networks (WSNs) not only have become an essential technology in the current scenario but also has been established as a core technology for many applications, like the Internet of Things (IoT). The drawback of limited energy resources in WSN creates the challenge of designing an energy‐efficient network topology and routing path. As these devices are generally not attended for any maintenance, such as battery replacement or charging, these resources need to be intelligently used. The paper represents a methodology for enhancing the lifetime of a network by using a genetic algorithm‐based clusteringand particle swarm optimization‐based routing in WSN. The best cluster head (CH) that collects the data from the remaining nodes is selected using a genetic algorithm, which considers distance and energy parameters. Further, the particle swarm optimization algorithm depends on optimal routing paths that are chosen for all relay nodes to send data to the Base Station (BS). The proposed procedure shows that the relay node supports and facilitates communication among the sink and CH, which enhances energy efficiency. Finally, the quality of service (QoS) of the WSNs is improved, due to which the system would survive longer. The results of simulated experiments show that the proposed approach significantly increases the lifetime of WSN and that energy consumption is reduced when compared with the existing protocols.

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Section: Related Workmentioning

confidence: 99%

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Anand

Pandey

2020

Int J Communication

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“…This work mainly concentrates in developing two algorithms for low memory components. In contrast, the authors of [18] have proposed a multi particle swarm immune cooperative algorithm for reliable routing in WSNs with more number http://journals.uob.edu.bh of resource rich nodes. Protocols to be followed in case of node failure have been proposed as a failure resilient routing approach in [19].…”

Section: Related Studymentioning

confidence: 99%

Fault Tolerant Sensor Node Placement for IoT based Large Scale Automated Greenhouse System

Al¹

2019

IJCDS

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Greenhouse method of agriculture overcomes various issues of traditional agriculture and provides good crop yield in farming. When the maintenance of greenhouse plants is automated, it helps the farmers in monitoring the soil, water and lighting required for higher crop yield, with low cost and saving man power and time. Internet of Things (IoT) makes the different components involved in this monitoring process to talk to each other, and coordinate and disseminate the observed data to reach the sink node and direct instructions to the actuator components to perform appropriate actions. The lifetime of the network is directly proportional to the energy of the nodes in the automated system. So as to improve the network lifetime, location of sensors and the distance between the relay nodes should be taken into consideration. This paper demonstrates the work of an automated greenhouse system based on IoT for sensing soil moisture, light, temperature and humidity. For improving the lifetime of this system, especially when the system is deployed in a large scale greenhouse, the complexity involved are discussed and the solution based on node placement is provided to efficiently improve the network lifetime. We provide solution for fault tolerant node placement using Menger's Theorem. Simulation of the proposed model has been carried out and the results suggest the better model of sensor node placement in a green house system. The simulation results prove that the model we proposed provides reliable transmission and better throughput compared to the existing approach.

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“…Location of the IoT nodes are fixed in the network and distance between nth normal node to the mth cluster head is represented by and provides the distance between cluster head and sink node . [17] is refered. In IoT network each nodes deployed will have transreciever, amplifiers for communication between them and the energy drained out by these compunents will be accounted.…”

Section: Related Workmentioning

confidence: 99%

Mobility Aware Weighted Clustering Algorithm for Maximizing IOT Network Lifetime by Harnessing Routing Energy

N N,

Kumar,

2019

IJEAT

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The Internet of Things (IoT) is considered as evolved form of Internet in the present scenario. Due to the prediction that large amount of data could be generated by billions of devices connecting to the Internet, requires data to be routed and processed rapidly by harnessing IoT devices energy. Energy constraint IoT devices consume more energy due to mobility of nodes and results in minimizing network lifetime. Motivated by this challenge, mobility aware weighted clustering algorithm (MAWCA) for maximizing IoT network lifetime by harnessing routing energy is proposed to find the optimal cluster head (CH) for mobile nodes in the IoT network. MAWCA considers degree difference of the node, sum of differences between neighbors, cumulative time, nodes mobility and delay in choosing a CH as weighting factor during CH election process. Simulation results shows that the proposed MAWCA outperforms in respect to network energy, delivery ratio, alive nodes count, packet loss ratio and network lifetime in par with similar existing algorithm. The uniqueness of the paper lies in selecting potential cluster head to maximize IoT network lifetime.

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MPSICA: An intelligent routing recovery scheme for heterogeneous wireless sensor networks

Cited by 18 publications

References 32 publications

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Fault Tolerant Sensor Node Placement for IoT based Large Scale Automated Greenhouse System

Mobility Aware Weighted Clustering Algorithm for Maximizing IOT Network Lifetime by Harnessing Routing Energy

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