Manimozhi Muthukumarasamy

Bio: Manimozhi Muthukumarasamy is an academic researcher from VIT University. The author has contributed to research in topics: Wireless sensor network & Scalability. The author has an hindex of 3, co-authored 4 publications receiving 24 citations.

Energy-efficient clustering algorithm for structured wireless sensor networks

Abstract: Wireless communication is preferred in numerous sensing applications due to its convenience, cost-effectiveness, and flexibility. Modern sensors are versatile to sense the environmental factors and send them wirelessly. The information collection centres prefer to collect confined clustered information from a group of sensors rather than collecting them from individual sensors. Good connectivity, speedy communication, and effective data gathering can be ensured in the network when a good clustering algorithm is utilized. In this paper, a simple and effective clustering algorithm called energy efficient structured clustering algorithm (EESCA) is proposed for the environmental monitoring fields. Cluster heads (CHs) are elected based on average communication distance and lingering energy. Further, a new parameter called cluster head to normal ratio (CTNR) is introduced to rotate the cluster head role among the nodes. The performance evaluation is carried out in terms of first node die (FND), simulation time, scalability, load balancing, and a new parameter called complete useful data percentage (CUDP). Simulations are conducted for three different network scenarios. Results are compared with the renowned existing algorithms low energy adaptive clustering hierarchy (LEACH) and scalable energy efficient clustering hierarchy (SEECH) and it is proved that the proposed technique is beneficial for WSNs.

Scalable Grid-Based Data Gathering Algorithm for Environmental Monitoring Wireless Sensor Networks

Abstract: Proper utilization of the available low-power is essential to extend the lifetime of the battery-operated wireless sensor networks (WSNs) for environmental monitoring applications. It is mandatory because the batteries cannot be replaced or recharged after deployment due to impracticality. To utilize the power properly, an appropriate cluster-based data gathering algorithm is needed which reduces the overall power consumption of the network significantly. So, in this paper, a grid-based data gathering algorithm called energy-efficient structured clustering algorithm with relay (EESCA-WR) is proposed. In this algorithm, the grids have a single grid leader (GL) and multiple grid relays (GRs). The count of GRs in a grid is variable based on the geographic location of the grid with respect to the destination sink (DS). By doing this, we ensure that the reduction in power consumption is achieved because of the multi-hop short-distance data communications. Also, the GLs are rotated in the right intervals in hybrid modes to minimize the usage of control messages considerably. A hybrid GL selection policy, a threshold-based GL rotation policy, and the policy of allotting dedicated relay-clusters in every grid make the proposed algorithm unique and better for homogeneous and heterogeneous wireless sensor networks. Performance evaluation of the proposed algorithm is carried out by varying the length of the field, the node-density, the grid-count, and the initial energy. Experimental results show that EESCA-WR is extremely scalable, energy-efficient with a minimum number of control messages, and can be used for large scale WSNs.

A Novel PID Controller with Second Order Lead/Lag Filter for Stable and Unstable First Order Process with Time Delay

Abstract: Abstract A novel Proportional-Integral-Derivative (PID) controller is proposed for stable and unstable first order processes with time delay. The controller is cascaded in series with a second order filter. Polynomial approach is employed to derive the controller and filter parameters. Simple tuning rules are derived by analysing the maximum sensitivity of the control loop. Formulae are provided for initial guess of tuning parameter. The range of tuning parameter around the initial guess and the corresponding range of maximum sensitivity is specified based on time delay to time constant ratio. Promising results are obtained with the proposed method is compared against recently proposed methods in the literature. The comparison is made in terms of various performance indices for servo and regulatory responses separately. The proposed method is implemented for an isothermal chemical reactor at an unstable equilibrium point.

Scalable Grid-Based Data Gathering Algorithm for Environmental Monitoring Wireless Sensor Networks

Abstract: Proper utilization of the available low-power is essential to extend the lifetime of the battery-operated wireless sensor networks (WSNs) for environmental monitoring applications. It is mandatory because the batteries cannot be replaced or recharged after deployment due to impracticality. To utilize the power properly, an appropriate cluster-based data gathering algorithm is needed which reduces the overall power consumption of the network significantly. So, in this paper, a grid-based data gathering algorithm called energy-efficient structured clustering algorithm with relay (EESCA-WR) is proposed. In this algorithm, the grids have a single grid leader (GL) and multiple grid relays (GRs). The count of GRs in a grid is variable based on the geographic location of the grid with respect to the destination sink (DS). By doing this, we ensure that the reduction in power consumption is achieved because of the multi-hop short-distance data communications. Also, the GLs are rotated in the right intervals in hybrid modes to minimize the usage of control messages considerably. A hybrid GL selection policy, a threshold-based GL rotation policy, and the policy of allotting dedicated relay-clusters in every grid make the proposed algorithm unique and better for homogeneous and heterogeneous wireless sensor networks. Performance evaluation of the proposed algorithm is carried out by varying the length of the field, the node-density, the grid-count, and the initial energy. Experimental results show that EESCA-WR is extremely scalable, energy-efficient with a minimum number of control messages, and can be used for large scale WSNs.

Energy-Saving Optimization and Matlab Simulation of Wireless Networks Based on Clustered Multi-hop Routing Algorithm

Abstract: Reducing the energy consumption of the wireless sensor network is an effective way to extend the lifetime of the wireless sensor network. This paper proposes a real-time routing protocol RRPBLC that combines location information and clustering technology. By dividing the monitoring area into cells, each cell is composed of a cluster, and the method of mixing cluster head elections and dynamically adjusting the forwarding transmission rate is adopted. The simulation results show that the clustering algorithm and cluster head election algorithm designed in this paper have good performance in balancing node load, which not only avoids the problem of “hot zone”, but also makes the node energy consumption uniform. At the same time, the performance of the algorithm in response to network performance degradation caused by node failure is also outstanding, even if 50% of nodes fail. The algorithm can still guarantee reliable monitoring data from the network, so it can greatly extend the network life cycle. The protocol not only can achieve energy balance of the network, extend the life cycle of the network, and has better real-time performance.

An Algorithmic Approach for Core Election in Mobile Ad-hoc Network

Abstract: Multicasting has an important contribution in a wireless sensor network. Through multicasting, multiple copies of data at the same time in a single transmission can be transmitted to a group of interested users. This reduces the multiple unicasting and hence increases efficiency in term of overhead and reliability in term of delay in the presence of dynamic topology. In this paper, an efficient core is elected within the receiver group on some predefined parameters. Likewise, to increase the reliability in term of delay, a mirror core is introduced. In case of the failure of primary core, the mirror core takes the responsibility as a primary core and communication of the group is continued without any delay. To achieve the above goals, an algorithm is proposed for core-based protocol and mathematical model is used to analyze the overhead performance. Finally, the performance of efficiency and reliability is measured in Network Simulator 2 (NS-2).

Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs

Abstract: In this paper, we propose and discuss two types of algorithms to improve energy efficiency in Wireless Sensor Networks. An efficient approach for extending the life of a network is known as “sensor clustering” in wireless sensor networks. In proposed algorithms, the study area where sensor nodes are randomly distributed is divided into clusters. In each cluster, the sensor that is the closest to the cluster center and has the highest residual energy is chosen as the cluster head. To make this choice, a greedy approach and artificial neural network methods are applied. In addition, to reduce the energy consumption of cluster heads, a mobile sink is used. The list of routes to be used by the mobile sink is calculated with the genetic algorithm. According to the route information, the mobile sink moves to the clusters and initiates the data collection process for each cluster. We compared our models according to the round value at which all sensor nodes run out of energy and the energy consumption by the network per round. Simulation results show that the proposed models increase the energy efficiency and extend the network lifespan.