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  1. 1
    Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks

    Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks by Motwakel, Abdelwahed, Hassan Abdalla Hashim, Aisha, Alamro, Hayam, Alqahtani, Hamed, Alotaibi, Faiz Abdullah, Sayed, Ahmed

    Published 2023
    “…Therefore, this paper develops a Chaotic Mapping Lion Optimization Algorithm-based Node Localization Approach (CMLOA-NLA) for WSNs. …”
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  2. 2
    Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior

    Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior by Abidin H.Z., Din N.M., Radzi N.A.M.

    Published 2023
    “…The main objectives considered in this paper are to achieve maximum coverage and minimum energy consumption with guaranteed connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm implemented in two different single objective approaches with an Integer Linear Programming based algorithm and another biological inspired algorithm. …”
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  3. 3
    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network

    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…This paper emphasizes employing a ranging technique called Received Signal Strength Indicator (shortly RSSI) to calculate the length of distances among all the nodes of WSNs. Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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  4. 4
    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. …”
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  5. 5
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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  6. 6
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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  7. 7
    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network by Puteri Azwa, Ahmad

    Published 2014
    “…The performance of Extended Virtual Force-Based Algorithm (EVFA) and Cuckoo Search (CS) algorithm are evaluated and EVFA shows the improvement of coverage area and exhibits a guaranteed connectivity compared to CS algorithm. …”
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  8. 8
    A noble approach of ACO algorithm for WSN

    A noble approach of ACO algorithm for WSN by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2018
    “…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.…”
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    Proceeding Paper
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  9. 9
    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
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  10. 10
    Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

    Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm by Zainol Abidin H., Din N.M., Yassin I.M., Omar H.A., Radzi N.A.M., Sadon S.K.

    Published 2023
    “…A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. …”
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  11. 11
    WSN sensor node placement approach based on multi-objective optimization

    WSN sensor node placement approach based on multi-objective optimization by Abidin H.Z., Din N.M., Radzi N.A.M.

    Published 2023
    Conference Paper
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  12. 12
    Accurate range free localization in multi-hop wireless sensor networks

    Accurate range free localization in multi-hop wireless sensor networks by Abdulwahhab, Abdullah Raed

    Published 2019
    “…The performance is evaluated in terms of RMSE in terms of three algorithms WLS, CRLR, and GMSDP based on using the Monte Carlo simulation with account the number of anchors that varying from anchor=4 to anchor =20. …”
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  13. 13
    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach

    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach by Kong, Zan Wai

    Published 2022
    “…One of the contributions of this work is the formalization of the fitness function for genetic algorithm. A series of simulations were designed and carried out to benchmark our framework against existing solutions with different evaluation criteria based on the consideration factors. …”
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  14. 14
    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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  15. 15
    EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network

    EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network by Nurlan, Zhanserik, Zhukabayeva, Tamara, Othman, Mohamed

    Published 2021
    “…EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. …”
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  16. 16
    A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks

    A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks by Q. Qadori, Huthiafa, Ahmad Zulkarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…Mobile agent (MA), a part of the mobile computing paradigm, was recently proposed for data gathering in Wireless Sensor Networks (WSNs). The MA-based approach employs two algorithms: Single-agent Itinerary Planning (SIP) and Multi-mobile agent Itinerary Planning (MIP) for energy-efficient data gathering. …”
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  17. 17
    A novel bio-inspired routing algorithm based on ACO for WSNs

    A novel bio-inspired routing algorithm based on ACO for WSNs by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2019
    “…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. …”
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  18. 18
    Mobile data gathering algorithms for wireless sensor networks

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…These mobile elements will go to each transmission range of each respective sensor to upload its data. In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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  19. 19
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). DSSA is a schedule based protocol and the objective of the algorithm is to assign the time slots to the nodes and avoid collision. …”
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  20. 20
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). DSSA is a schedule based protocol and the objective of the algorithm is to assign the time slots to the nodes and avoid collision. …”
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