scholarly journals Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Santosh Soni ◽  
Manish Shrivastava
Keyword(s):  
Reinforcement Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Research Study ◽  
Hot Spot ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Hot Spot Problem

Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data. Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes. This problem is known as hot spot problem in wireless sensor network. In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network. The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power. In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads. Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly. These algorithms did not create the extra overhead on mobile sink and save the energy as well. Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.

scholarly journals An Efficiency of Timing to Route Discovery in Mobile Sink by using WSN

2019 ◽  
Vol 8 (12) ◽  
pp. 4559-4564
Keyword(s):  
Wireless Sensor Network ◽  
Time Delay ◽  
Energy Dissipation ◽  
Sensor Network ◽  
Large Scale ◽  
Hot Spot ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delay Bound

Due to the prospective implementation in many fields, study functionality in the wireless sensor network has risen very impressively in recent years. Wireless large-scale sensor networks contain various sources and various sink numbers. This plays a significant part in application performance. To this end, we will concentrate on the primary issue of sink arrangement in this study to minimize time delay in the worst scenario as well as to increase the lifespan of the wireless sensor network. Here we suggest an interconnected anatomy frame for calculating the mobility of the junction sink, routing details. We're talking about the causes of sub problems and bringing them efficient results. Then we combine all these outcomes and suggest the real issue with the optimum polynomial-time algorithm. From this consequence, the merits of involving nodes (mobile sink) and network argument or parametric quantity impact will be displayed. (Example: various sensors, sinks and time delay bound) the lifespan of the network. As we understand, Wireless sensor network nodes are battery-dependent equipment that collects information from the surroundings and send this (information) information to the sink node for further computational processing leading to energy dissipation in batteries The batteries are non-rechargeable or in certain settings it may be hard to replace or recharge. These problems result in the design of a new algorithm for node energy efficiency In typical conditions, the sensor nodes display many to one communication with the sink, resulting in a faster energy depletion of the nodes near the sink, commonly referred to as the energy deficiency hole problem or the hot spot problem. hence in this situation, the mobility of the sink can help in balancing of energy dissipation of the sensor nodes In wireless sensor network when information data hold up by working sink it should be Bounded. Our results show that the proposed algorithm can work better than previous methods and yield results in remote locations such as in the wide region of the wireless sensor network, lake, mountains, hill stations, etc. Additional guideline antennas can boost the transfer chain, which increases to lower hops and low routing delays. Finally, numerical studies analyze the suggested work and simulations are performed to validate through MATLAB.

scholarly journals Estimation of Optimum Rendezvous Point for Mobile Sink (ORP-MS) in WSN

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1322 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav J Nigam
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
High Throughput ◽  
Mobile Sink ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Rendezvous Point ◽  
Coverage Holes

Clustering of the sensors in wireless sensor network is done to achieve energy efficiency. The nodes, which are unable to join any cluster, are referred to as isolated nodes and tend to transfer information straight to the base station. It is palpable that isolated nodes and cluster heads communicate with the base station and tend to exhaust their energy leaving behind coverage holes. In this paper, we propose the innovative clustering scheme using mobile sink approach to extend networks lifetime. The proposed (ORP-MS) algorithm is implemented in MATLAB 2017a and the results revealed that the proposed algorithm outdid the existing algorithms in terms networks lifetime and energy efficiency simultaneously achieved high throughput.  

scholarly journals A REVIEW ON A HYBRID APPROACH USING MOBILE SINK AND FUZZY LOGIC FOR REGION BASED CLUSTERING IN WSN

2017 ◽  
Vol 16 (2) ◽  
pp. 7586-7590
Author(s):  
Amneet Kaur ◽  
Harpreet Kaur
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Hybrid Approach ◽  
Mobile Sink ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wide Range ◽  
Energy Constrained

A Wireless Sensor Network or WSN is supposed to be made up of a large number of sensors and at least one base station. The sensors are autonomous small devices with several constraints like the battery power, computation capacity, communication range and memory. They also are supplied with transceivers to gather information from its environment and pass it on up to a certain base station, where the measured parameters can be stored and available for the end user. In most cases, the sensors forming these networks are deployed randomly and left unattended to and are expected to perform their mission properly and efficiently. As a result of this random deployment, the WSN has usually varying degrees of node density along its area. Sensor networks are also energy constrained since the individual sensors, which the network is formed with, are extremely energy-constrained as well. Wireless sensor networks have become increasingly popular due to their wide range of application. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. Minimizing the energy consumption of a wireless sensor network application is crucial for effective realization of the intended application in terms of cost, lifetime, and functionality. However, the minimizing task is hardly possible as no overall energy cost function is available for optimization.

scholarly journals Reinforcement Learning based Node Sleep or Wake-up Time Scheduling Algorithm for Wireless Sensor Network

2020 ◽  
Vol 5 (4) ◽  
pp. 707-731
Author(s):  
Parag Verma ◽  
Ankur Dumka ◽  
Dhawal Vyas ◽  
Anuj Bhardwaj
Keyword(s):  
Reinforcement Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Scheduling Algorithm ◽  
Data Packet ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Time Scheduling ◽  
Time Band

A wireless sensor network is a collection of small sensor nodes that have limited energy and are usually not rechargeable. Because of this, the lifetime of wireless sensor networks has always been a challenging area. One of the basic problems of the network has been the ability of the nodes to effectively schedule the sleep and wake-up time to overcome this problem. The motivation behind node sleep or wake-up time scheduling is to take care of nodes in sleep mode for as long as possible (without losing data packet transfer efficiency) and thus extend their useful life. This research going to propose scheduling of nodes sleeps and wake-up time through reinforcement learning. This research is not based on the nodes' duty cycle strategy (which creates a compromise between data packet delivery and nodes energy saving delay) like other existing researches. It is based on the research of reinforcement learning which gives independence to each node to choose its own activity from the transmission of packets, tuning or sleep node in each time band which works in a decentralized way. The simulation results show the qualified performance of the proposed algorithm under different conditions.

scholarly journals Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

2019 ◽  
Vol 8 (6) ◽  
pp. 323-327
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Optimal Solution ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Traffic Characteristics ◽  
Routing Methods

In wireless sensor network, randomly deployed nodes are formed as a clusters of varying size for each area depending upon the numbers of users. This paper deals with the cluster based joint routing with mobile sink and with static sink in cognitive based wireless sensor network. The Joint Routing (JR) is designed to overcome the problems, due to data gatherings of the sensor nodes for any application. Channel resources usually may vary among the different routing methods based on the traffic characteristics and application they require, which poses a great challenge to guarantee time delivery services. These problems poses a great challenge for cognitive radio based WSN. The resource allocation technique overcomes the problems like spatial priority, time delay, transmission delay and energy loss and here the channel resources are allocated with the help of TDMA technique. The static sink in networks consumes more energy which results the early die out of the nodes. Hence throughput of the networks declines which badly affect the network life time. To overcome these issues, static sink is replaced by mobile sink, which consumes less energy, before each transmission in a sensor networks. The networks with mobile sink provide us optimal solution and performance as well, while comparing with network with static sink. It is shown that the proposed system achieves 15% of improved throughput, 20% of less packet loss and 35% of less delay when compare with the system having centralized sink.

scholarly journals NEEF: A Novel Energy Efficient Fuzzy Logic based Clustering Protocol for Wireless Sensor Network

2020 ◽  
Vol 21 (3) ◽  
pp. 555-568
Author(s):  
Anshu Kumar Dwivedi ◽  
A. K. Sharma
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Clustering Protocol ◽  
Selection Of

The uttermost requirement of the wireless sensor network is prolonged lifetime. Unequal energy degeneration in clustered sensor nodes lead to the premature death of sensor nodes resulting in a lessened lifetime. Most of the proposed protocols primarily choose cluster head on the basis of a random number, which is somewhat discriminating as some nodes which are eligible candidates for cluster head role may be skipped because of this randomness. To rule out this issue, we propose a deterministic novel energy efficient fuzzy logic based clustering protocol (NEEF) which considers primary and secondary factors in fuzzy logic system while selecting cluster heads. After selection of cluster heads, non-cluster head nodes use fuzzy logic for prudent selection of their cluster head for cluster formation. NEEF is simulated and compared with two recent state of the art protocols, namely SCHFTL and DFCR under two scenarios. Simulation results unveil better performance by balancing the load and improvement in terms of stability period, packets forwarded to the base station, improved average energy and extended lifetime.

scholarly journals Design and Development of an Energy Efficient Algorithm for Data Aggregation in Wireless Sensor Network using Unsupervised Learning

2019 ◽  
Vol 9 (2S) ◽  
pp. 124-128
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Machine Learning Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Mobile Sinks ◽  
Cluster Heads ◽  
Battery Power ◽  
New Algorithms

A wireless sensor network generally defined as the collection of sensors that are utilized to track and record the data in real-time on an ongoing basis from different applications. In comparison with other sensor nodes, data transmission obtained through sinks in WSN eliminates the energy in nearby nodes. This issue is identified as one of the major problems in a wireless sensor network. Two new algorithms were proposed in this research paper that mainly focused on the usage of machine learning algorithms to solve the data collection issue in the wireless sensor network. The algorithms proposed will able to create cluster heads to decrease energy usage, this will save about 50% of battery power consumption and mobile sinks are used to record the data from cluster heads in a network. Ultimately, current algorithms such as RLLO, DBRkM, CLIQUE, RL-CRC, and EPMS were compared.

scholarly journals Improvement of cluster-based WSN protocol using fuzzy logic

2020 ◽  
Vol 19 (3) ◽  
pp. 1540
Author(s):  
Jong-Yong Lee ◽  
Daesung Lee
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Increase Energy Efficiency ◽  
Cluster Heads ◽  
Adjacent Cluster ◽  
Optimal Cluster

<span>A wireless sensor network is a collection of wireless nodes with sensor devices that can collect data from the real world. This is because sensor nodes usually use limited-powered batteries. Therefore, if the battery on the sensor node is exhausted, the node will no longer be available. If the battery on some nodes is discharged, the sensor network will not work properly. To maintain sensor network system, there are many wireless sensor network protocols to increase energy efficiency of nodes. One of the energy-efficient methods is cluster-based protocols. These protocols divide the sensor fields into clusters and send and receive data between nodes. Thus, depending on how the cluster is constructed, the network's lifetime may be reduced or increased. Cluster-based protocols cannot always be optimal cluster configurations. These problems have been improved using fuzzy logic. In general, fuzzy logic is used to elect cluster heads based on node residual energy, node concentration and node centrality. However, it is possible that nodes close to each other at a high density area are elected as cluster heads. In this paper, we propose a method to consider the number of adjacent cluster heads instead of Node Concentration to improve the problem.</span>

An Energy Efficient Routing Scheme for Mobile Wireless Sensor Network with Mobile Sink

2017 ◽  
Vol 7 (8) ◽  
pp. 100
Author(s):  
Ravneet Pal Kaur ◽  
Maninder Singh
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Network ◽  
Mobile Wireless Sensor

In wireless sensor network, the sensor nodes find the route towards the sink to transmit the sensory information such as temperature, pressure etc of a particular area. The sensor nodes transmit the data directly to sink or it relays the data through neighbor nodes using single or multi-hop links. Each time when nodes send their data to static sink, the data is passed through the nearer nodes of sink to it. As soon as the nodes near to the sink become dead, the entire network will be useless as there will be no communication to the sink node. So, to conserve the energy we use mobile sink approach. Thus with the inclusion of mobile sink in WSN, new paradigm called mobile wireless sensor network came into existence. In this paper, to conserve energy and to perform energy efficient routing, we have proposed chain-based energy efficient routing scheme for mobile wireless sensor network (CB-EERM)which is using mobile sink and media access approach where sink moves from one position to another position in sensor field and sojourn at a particular location to collect the whole aggregated data from the various  leader(aggregator)nodes in chain using media access approach. The proposed mobile scheme CB-EERM is validated through simulation and compared with traditional static approach using metrics such as energy consumption, throughput, delay and packet delivery ratio where proposed approach outperforms the existing scheme.

scholarly journals Data Transmission Scheme Using Mobile Sink in Static Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Awais Ahmad ◽  
M. Mazhar Rathore ◽  
Anand Paul ◽  
Bo-Wei Chen
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transmission Scheme ◽  
Neighboring Node ◽  
Communication Time ◽  
Selection Of

Multihop communication in wireless sensor network (WSN) brings new challenges in reliable data transmission. Recent work shows that data collection from sensor nodes using mobile sink minimizes multihop data transmission and improves energy efficiency. However, due to continuous movements, mobile sink has limited communication time to collect data from sensor nodes, which results in rapid depletion of node’s energy. Therefore, we propose a data transmission scheme that addresses the aforementioned constraints. The proposed scheme first finds out the group based region on the basis of localization information of the sensor nodes and predefined trajectory information of a mobile sink. After determining the group region in the network, selection of master nodes is made. The master nodes directly transmit their data to the mobile sink upon its arrival at their group region through restricted flooding scheme. In addition, the agent node concept is introduced for swapping of the role of the master nodes in each group region. The master node when consuming energy up to a certain threshold, neighboring node with second highest residual energy is selected as an agent node. The mathematical analysis shows that the selection of agent node maximizes the throughput while minimizing transmission delay in the network.

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