3 research outputs found

    An Election Energy Threshold Based Multi-Hop Routing Protocol in a Grid-Clustered Wireless Sensor Network

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    Owing to the limited energy of sensor nodes (SNs) in a wireless sensor network (WSN), it is important to reduce and balance the energy consumption of the SNs in order to extend the WSN lifetime. Clustering mechanism is a highly efficient and effective mechanism for minimizing the amount of energy that SNs consume during the transmission of data packets. In this paper, an election energy threshold based multi-hop routing protocol (mEEMRP) is presented. In order to minimize energy consumption, this routing protocol uses grid clustering, where the network field is divided into grid clusters. SNs in each grid cluster select a cluster head (CH) based on a weight factor that takes the node location, node’s residual energy (RE) as well as the node’s distance from the base station into consideration. An energy efficient multi-hop routing algorithm is adopted during the transmission of data packets from the cluster heads (CHs) to the base station (BS). This multi-hop routing algorithm uses an election energy threshold value, T­nhCH that takes into consideration the RE of CHs as well as the distance between CHs. Simulation results show a 1.77% and 10.65% improvement in terms of network lifetime for two network field scenarios over Energy Efficient Multi-hop Routing Protocol (EEMRP)

    Performance Comparison of the Ball and Beam System using Linear Quadratic Regulator Controller

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    This paper proposes the performance comparison of a linear quadratic regulator (LQR) controller for the ball and beam system (BBS). The BBS is a standard benchmark control system, which has two degree-of-freedom (2 DOF). It is an open loop and a highly nonlinear unstable system. This makes its parameter difficult to be estimated accurately, hence designing a controller for it is a challenging task. MatheThe BBS was modelled using Euler–Lagrange modeling technique, while the LQR controller was used for the stabilization of the ball on the beam. Simulation was done in MATLAB/Simulink 2022b environment, and the results simulated showed that for the two weighting matrices (Q and R), the state weighting matrix had a higher penalty on the ball displacement, ball velocity, beam angle, and beam angular velocity at lower values of Q. For the state weighting matrix had a better effect of penalty performance on the BBS with lower values. Also, as the diagonal element of the state weighting matrix Q increases from 0.1 to 20, the values of the optimal controller K increase, the reduced Ricatti matrix P increases, and the estimated eigenvalues E reduce. This implies that the ball displacement, ball velocity, beam angle, and beam angular velocity are better at lower values of Q

    An Election Energy Threshold Based Multi-Hop Routing Protocol in a Grid-Clustered Wireless Sensor Network

    Get PDF
    Owing to the limited energy of sensor nodes (SNs) in a wireless sensor network (WSN), it is important to reduce and balance the energy consumption of the SNs in order to extend the WSN lifetime. Clustering mechanism is a highly efficient and effective mechanism for minimizing the amount of energy that SNs consume during the transmission of data packets. In this paper, an election energy threshold based multi-hop routing protocol (mEEMRP) is presented. In order to minimize energy consumption, this routing protocol uses grid clustering, where the network field is divided into grid clusters. SNs in each grid cluster select a cluster head (CH) based on a weight factor that takes the node location, node’s residual energy (RE) as well as the node’s distance from the base station into consideration. An energy efficient multi-hop routing algorithm is adopted during the transmission of data packets from the cluster heads (CHs) to the base station (BS). This multi-hop routing algorithm uses an election energy threshold value, T­nhCH that takes into consideration the RE of CHs as well as the distance between CHs. Simulation results show a 1.77% and 10.65% improvement in terms of network lifetime for two network field scenarios over Energy Efficient Multi-hop Routing Protocol (EEMRP)
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