Security enhanced optimal trajectoryselection for mobile sink using reinforcement learning

2021 ◽  
pp. 1-13
Author(s):  
Usama Abdur Rahman ◽  
C. Jayakumar
Keyword(s):  
Reinforcement Learning ◽  
Energy Efficient ◽  
Cluster Head ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Dual Function ◽  
Visual Sensor ◽  
Mobile Sinks ◽  
Route Design

Wireless visual sensor networks (WVSNs) have emerged as a strategic inter disciplinary category of WSN with its visual sensor based intelligence that has garnered considerable attention. The growing demand for energy efficient and maximized life time networks in highly critical applications like surveillance, military and medicine has opened up more prospects as well as challenges in the deployment of WVSNs. Multi-hop communication in WVSN results in overloading of intermediate sensor nodes due to its dual function in the network which results in hotspot effect. This can be mitigated with the help of mobile sinks and rendezvous points based route design. But mobile sinks has to visit every cluster head to gather data which results in longer traversal path and higher latency and power consumption related issues if not addressed properly will impact the performance of the network. Our objective is to analyze and determine the optimal trajectory for mobile sink node traversal with the help of a high quality transmission architecture integrated with reinforcement learning and isolation forest based anomaly detection to propose an energy efficient meta-heuristic approach to enhance the performance of network by reducing the latency and securing the network against possible attacks.

The Research of Data Gathering Protocol for Mobile Sensor Networks

2011 ◽  
Vol 216 ◽  
pp. 621-624
Author(s):  
Xin Lian Zhou ◽  
Jian Bo Xu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Mobile Sink ◽  
Mobile Node ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Node Mobility ◽  
Sink Node ◽  
Mobile Sensor ◽  
The Impact

This paper first proposed an energy-efficient distributed clustering technology for mobile sensor nodes and sink node mobility, select the higher residual energy and the nearest node from fixed nodes as cluster heads responsible for collecting sensed data, and all the fixed nodes form routing backbone to forward data, both can save energy and avoid cluster head away. Then, proposed a cross-layer scheduling mechanism to avoid the impact of mobile node and meet expectations cluster coverage. With energy-efficient clustering technology, efficient network topology control technology and mobile sink node, the data collection algorithm MSDBG, not only has considered mobility of nodes and energy saving, but also has achieved prolonging network lifetime.

scholarly journals Energy Efficient Inter And Intra Cluster Movement of Mobile Sink In Wireless Sensor Network

2019 ◽  
Vol 8 (6) ◽  
pp. 2682-2688
Keyword(s):  
Energy Efficient ◽  
Smart Grids ◽  
Network Performance ◽  
Smart Cities ◽  
Sewage Treatment ◽  
Cluster Head ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Sewage Treatment Plants ◽  
Stability Period

WSN has brought revolution in monitoring or examining the particular area of the network. It has acquired many sectors like agricultural sectors, smart cities (Smart grids, Sewage treatment plants) and automation industries etc. the most prominent concern of battery of the sensor nodes are reported to deal with the energy efficient solution but still there is a lot of scope in enhancing the network performance of the WSN. The sink mobility in a controlled scenario with optimized Cluster head selection after every round using PSO has improved the network performance. The proposed scheme beats the ICM in terms of stability period, lifetime and half node dead. Stability Period, Half Node Dead and Network lifetime has increased by 19.8%, 42.1% and 37% respectively. Standard average coverage time decreases with increase in network area size.

scholarly journals Routing Algorithm using Fuzzy Logic Based Clustering with Mobile Sink for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 4000-4005
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree

Minimization of the energy consumption in Wireless Sensor Network (WSN) is one of the most important area which has been explored by researchers through different methods. The use of non-stationary mobile sink has undoubtedly decreased the energy consumption within the sensor nodes and hence the life time of the system. Applying the Fuzzy Logic could effectively optimize the selection of Cluster Head. In this paper, Fuzzy Logic has been implemented for Cluster Head selection along with a mobile sink. The energy remaining in the sensor node, distance between the sink and the node, and the node degree are considered as the fuzzy inference variables. The life time of the node has been compared with the LEACH and Fuzzy logic based Clustering Combined with Mobile Sink (FCCMS) with mobile sink.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

2020 ◽  
Vol 17 (12) ◽  
pp. 5447-5456
Author(s):  
R. M. Alamelu ◽  
K. Prabu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Link Quality ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Energy Efficient Clustering

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

scholarly journals Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Network

2021 ◽  
Vol 13 (1) ◽  
pp. 75-92
Author(s):  
Lakshmi M ◽  
Prashanth C R
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Mac Layer ◽  
Optimum Energy ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering ◽  
Secured Data

Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.

scholarly journals Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Baniata ◽  
Jiman Hong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Chain Length ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Smart Cities ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities. These advances are also helping to monitor smart cities and making our living environments workable. However, sensor nodes are constrained in energy supply if they have no constant power supply. Moreover, communication links can be easily failed because of unequal node energy depletion. The energy constraints and link failures affect the performance and quality of the sensor network. Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN. In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime. Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.

Energy-Efficient Routing Protocol on Mobile Sink in Wireless Sensor Network

2013 ◽  
Vol 787 ◽  
pp. 1050-1055 ◽  
Author(s):  
Zhi Gui Lin ◽  
Hui Qi Zhang ◽  
Xu Yang Wang ◽  
Fang Qin Yao ◽  
Zhen Xing Chen
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Model Simulation ◽  
Cluster Head ◽  
Mobile Sink ◽  
High Energy ◽  
Residual Energy ◽  
Energy Efficient Routing ◽  
Simulation Results

To the disadvantages, such as high energy consumption and the energy consumption imbalance, we proposed an energy-efficient routing protocol on mobile sink (MSEERP) in this paper. In the MSEERP, the network is divided into several square virtual grids based on GAF, each grid is called a cluster, and the cluster head election method of GAF is improved. In addition, the MSEERP introduces a mobile sink in the network, the sink radios in limited number of hops and uses control moving strategy, namely the sink does not collect the information until it moves to a cluster with highest residual energy. We applied NS2 to evaluate its performance and analyze the simulation results by the energy model. Simulation results show that the MSEERP balances the energy consumption of the network, saves nodes energy and extends the network lifetime.

scholarly journals REGION BASED CLUSTERING FOR DATA COLLECTION IN WSN

2017 ◽  
Vol 16 (5) ◽  
pp. 6913-6919
Author(s):  
Ramandeep Kaur ◽  
Dinesh Kumar
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Smart Cities ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Clustering Methods ◽  
Mobile Nodes ◽  
Improved Performance

The lower cost and easier installation of the WSNs than the wired counterpart pushes industry and academia to pay more attention to this promising technology. Large scale networks of small energy-constrained sensor nodes require techniques and protocols which are scalable, robust, and energy-efficient. The most efficient approach provided by clustering the nodes is hierarchy. The one node will send the data to another node and the another node will send to its neightbouring node. In smart cities, wireless sensor networks (WSNs) act as a type of core infrastructure that collects data from the city to implement smart services. Our thesis work included the region based clustering, cluster head selection and energy efficient communication using static base station and movable mobile nodes. Since it was earlier proposed that clustering improves the network lifetime. We modified the region based clustering by dividing the network area into n regions with cluster head chosen for each region and proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. We have used the mobile nodes for each section with controlled trajectory path as a reference to compare the performance of each of the clustering methods.

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