A novel multi-objective optimization strategy for enhancing quality of service in IoT-enabled WSN applications

Prasanth, A.; Jayachitra, S.

doi:10.1007/s12083-020-00945-y

Cited by 83 publications

(36 citation statements)

References 34 publications

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“…The enhancement level of given scheme is 17% more than the related schemes. Prasanth and Jayachitra [32] proposed a scheme to achieve effective IWSN (IoT based wireless sensor network) model. The purpose of the related scheme is to improve more than one objectives including connectivity, energy usage and coverage under WSN.…”

Section: Literature Reviewmentioning

confidence: 99%

Effective modelling of sinkhole detection algorithm for edge‐based Internet of Things (IoT) sensing devices

2022

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The sinkhole attacks for Internet of Things (IoT) situations can overcome the network and interrupt communication. Sinkhole attacker nodes can advertise the best possible shortest path towards the destination, and once the normal node starts transferring the packets by the given path, the attacker node starts troublemaking the flow of the network. In this environment, the destination is unable to receive proper information or may not receive complete information. Sinkhole attacked network keeps the problems like the enhanced end-to-end delay, less throughput, and reduced packet delivery. Furthermore, it can affect other network constraints. So, it has become important to design an effective model to prevent the IoT environment from sinkhole attacks. In this article, an intrusion detection model is proposed to protect the IoT environment from sinkhole attacks. A model proposed by using rich resourced edge nodes to detect various kinds of sinkhole attacker nodes by exchanging messages. A well-known NS2 simulator is used for the practical implementation of the model. The proposed model attains more than 95% detection rate with a near about 1.4% false-positive rate, which seems better than previously given schemes. Finally, the proposed scheme is the appropriate match for a sensitive platform like a monitoring and security system.

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Section: Literature Reviewmentioning

confidence: 99%

Effective modelling of sinkhole detection algorithm for edge‐based Internet of Things (IoT) sensing devices

2022

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“…Figure 2 demonstrates an example of the clustering-based WSN. Various studies based on hierarchical structure have been proposed in the literature to prolong the networks life and for efficient energy consumption (Prasanth and Pavalarajan, 2019;Prasanth and Jayachitra, 2020). This paper describes some of the well-known and recent published hierarchical methods that have energy efficiency as their main objective.…”

Section: Hierarchical-based Algorithmsmentioning

confidence: 99%

Improving the performance of hierarchical wireless sensor networks using the metaheuristic algorithms: efficient cluster head selection

Kiani

Seyyedabbasi

Nematzadeh

2021

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Purpose Efficient resource utilization in wireless sensor networks is an important issue. Clustering structure has an important effect on the efficient use of energy, which is one of the most critical resources. However, it is extremely vital to choose efficient and suitable cluster head (CH) elements in these structures to harness their benefits. Selecting appropriate CHs and finding optimal coefficients for each parameter of a relevant fitness function in CHs election is a non-deterministic polynomial-time (NP-hard) problem that requires additional processing. Therefore, the purpose of this paper is to propose efficient solutions to achieve the main goal by addressing the related issues. Design/methodology/approach This paper draws inspiration from three metaheuristic-based algorithms; gray wolf optimizer (GWO), incremental GWO and expanded GWO. These methods perform various complex processes very efficiently and much faster. They consist of cluster setup and data transmission phases. The first phase focuses on clusters formation and CHs election, and the second phase tries to find routes for data transmission. The CH selection is obtained using a new fitness function. This function focuses on four parameters, i.e. energy of each node, energy of its neighbors, number of neighbors and its distance from the base station. Findings The results obtained from the proposed methods have been compared with HEEL, EESTDC, iABC and NR-LEACH algorithms and are found to be successful using various analysis parameters. Particularly, I-HEELEx-GWO method has provided the best results. Originality/value This paper proposes three new methods to elect optimal CH that prolong the networks lifetime, save energy, improve overhead along with packet delivery ratio.

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“…Paper [22] proposes an adaptive coverage and connectivity (ACC) scheme. It uses two basic methods, the first of which can provide the best coverage for all target objects,…”

Section: Related Workmentioning

confidence: 99%

Hybrid Niche Immune Genetic Algorithm for Fault Detection Coverage in Industry Wireless Sensor Network

et al. 2021

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The industry wireless sensor network (IWSN) technology, which is used to monitor industrial equipment, has attracted more and more attention in recent years. Sensor nodes in IWSN can spontaneously complete distributed networking and carry out monitoring tasks under random deployment conditions. Therefore, a self-organized IWSN is particularly suitable for the fault detection and diagnosis of industrial equipment in complex environments. However, due to the detection, ability of a single sensor node is limited, and the monitoring distribution problem is a typical multidimensional discrete NP-hard combinatorial stochastic optimization problem, which is challenging to solve for the traditional mathematical methods. With the purpose of improving the target monitoring capability and prolonging lifetime of IWSN, a novel hybrid niche immune genetic algorithm (HNIGA) for optimizing the target coverage model of fault detection is proposed. It uses the genetic operation to evolve antibody groups and applies niche technology to maintain the diversity of antibody groups. As a result, HNIGA can effectively reduce the failure rate of detection targets. To verify the performance of HNIGA, a series of simulations under different simulation conditions are carried out. Specifically, HNIGA is compared with genetic algorithm (GA) and simulated annealing (SA). Simulation results show that HNIGA has a faster convergence speed and more robust global search capability than the other two algorithms.

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A novel multi-objective optimization strategy for enhancing quality of service in IoT-enabled WSN applications

Cited by 83 publications

References 34 publications

Effective modelling of sinkhole detection algorithm for edge‐based Internet of Things (IoT) sensing devices

Effective modelling of sinkhole detection algorithm for edge‐based Internet of Things (IoT) sensing devices

Improving the performance of hierarchical wireless sensor networks using the metaheuristic algorithms: efficient cluster head selection

Hybrid Niche Immune Genetic Algorithm for Fault Detection Coverage in Industry Wireless Sensor Network

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