A Moving Base Station Strategy Using Fuzzy Logic for Lifetime Enhancement in Wireless Sensor Network

2011 ◽  
Author(s):  
Abhijeet Alkesh ◽  
Ashutosh Kumar Singh ◽  
N. Purohit
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Wireless Sensor ◽  
Moving Base ◽  
Lifetime Enhancement

PROCEDURE OF SELECTING A CLUSTER HEAD NODE IN A WIRELESS SENSOR NETWORK USING FUZZY LOGIC

2018 ◽  
pp. 81-89
Author(s):  
Ekaterina Andreevna Evstifeeva ◽  
Valeriy Dmitrievich Semeykin
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Efficiency ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Head Node ◽  
Input Parameters

Clustering, as one of the energy-efficient approaches, is widely used in wireless sensor networks. This method is based on creating clusters and selecting cluster head nodes in a wireless sensor network. Clustering saves network energy because data transfer is restricted between multiple nodes. Thus, clustering is provided between several nodes, and the service life of the wireless sensor network can be extended. Since the parent cluster node interacts with other nodes of the network, a node with a high level of residual energy must be selected to perform this role. When the energy level of the selected cluster head node becomes lower than the threshold value, then the re-election of this node takes place. It should be noted that multiple patterns of choosing cluster head nodes built using various parameters (residual node energy, distance from the base station to a node, distance between the head node and a cluster member, the number and proximity of neighboring nodes, etc.) lacked for a factor of energy consumption, i.e. how many times nodes communicated to each other. To cope with the problem, this paper presents a prognostic algorithm for selecting a cluster head node using fuzzy logic. This algorithm suggests using a number of input parameters, such as the residual energy of the node, the proximity of neighboring nodes, and the centralization of the node in the cluster. The proposed algorithm has been implemented using the software package MATLAB Fuzzy Logic Toolbox. The simulation results prove the advantages of the proposed technique; application of the input parameters mentioned above helps select optimal cluster head nodes in a wireless sensor network, which increases power efficiency of a wireless sensor network.

A Fuzzy Logic-Based Method to Avert Intrusions in Wireless Sensor Networks Using WSN-DS Dataset

2020 ◽  
Vol 19 (03) ◽  
pp. 2050018
Author(s):  
Neha Singh ◽  
Deepali Virmani ◽  
Xiao-Zhi Gao
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Fuzzy Rule ◽  
Base Station ◽  
Wireless Sensor ◽  
Rule Based ◽  
Intrusion Prevention

Intrusion is one of the biggest problems in wireless sensor networks. Because of the evolution in wired and wireless mechanization, various archetypes are used for communication. But security is the major concern as networks are more prone to intrusions. An intrusion can be dealt in two ways: either by detecting an intrusion in a wireless sensor network or by preventing an intrusion in a wireless sensor network. Many researchers are working on detecting intrusions and less emphasis is given on intrusion prevention. One of the modern techniques for averting intrusions is through fuzzy logic. In this paper, we have defined a fuzzy rule-based system to avert intrusions in wireless sensor network. The proposed system works in three phases: feature extraction, membership value computation and fuzzified rule applicator. The proposed method revolves around predicting nodes in three categories as “red”, “orange” and “green”. “Red” represents that the node is malicious and prevents it from entering the network. “Orange” represents that the node “might be malicious” and marks it suspicious. “Green” represents that the node is not malicious and it is safe to enter the network. The parameters for the proposed FzMAI are packet send to base station, energy consumption, signal strength, a packet received and PDR. Evaluation results show an accuracy of 98.29% for the proposed system. A detailed comparative analysis concludes that the proposed system outperforms all the other considered fuzzy rule-based systems. The advantage of the proposed system is that it prevents a malicious node from entering the system, thus averting intrusion.

scholarly journals Energy Efficient of IDS Using Fuzzy Logic for Lifetime Improvement in Wireless Sensor Network

2021 ◽  
Vol 10 (3) ◽  
pp. 233-238
Author(s):  
S. Venkatesan ◽  
M. Ramakrishnan
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Dijkstra Algorithm

The Wireless Sensor Network (W.S.N.) comprises little batteries fueled sensor gadgets with restricted energy assets. The Sensor hubs used to monitor the physical screen or conditionsbased on normal, theinformation must be private organization to primary area. The Most significant obstacles in a sensing the remote in the particular network which used to make an efficient energy framework. Clustering is the one of the major process in the sensor network based on wireless which used to drag out the life time of an organization lifetime which in turn reduce the energy utilization of the network. It includes gathering hubs into groups and choosing bunch heads (CH) for all the groups. CH gather information from separate group hubs and forward the collected data to the fundamental corner. This paper proposes novel fluffy various dynamic methodology measures: “Energy Efficient Optimal Cluster Head Selection utilizing Fuzzy Logic (EEOCH-FL)” for Wireless Sensor Network. Fluffy different boundary dynamic methodology is used to choose C.H.s utilizing three standards: leftover energy, fixation, the right ways from the principle hubs, and base station. The life cycle of Clustering hub and Clustering Head are grouped, clustering hub which transmitted all data to the Cluster Header Leader (CHL). The bunch head pioneers sent collected information to the Base Station (B.S.) from that point forward. The determination of bunch heads, group head pioneers is controlled and monitored by utilizing a fluffy rationale. The information transmission measure is per-shaped by the briefest energy way chosen to apply Dijkstra Algorithm. The reenactment results show that this methodology is more potent in boosting the availability inside each bunch. Furthermore, the reproduction aftereffects of this examination are contrasted and different conventions LEACH and CEELRP to assess the proposed steering convention's presence. The assessment reasons that convention of steering of this proposed work proved to be an effective in utilization of an energy

scholarly journals INCREASING THE LIFETIME OF HETEROGENEOUS SENSOR NETWORK BY USING GENETIC-FUZZY CLUSTERING

2013 ◽  
pp. 185-189
Author(s):  
SEYED MOHAMMAD ABEDINI ◽  
ABBAS KARIMI
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Process Data ◽  
To Receive

Wireless sensor network is composed of hundreds or thousands of sensor nodes which have computational, energy and memory limitation. Its duty is to receive information from its surrounding environment, analyze and process data and to send the received data to other nodes or base station. In these networks, sensor nodes are dependent on low power batteries to provide their energy. As energy is a challenging issue in these networks, clustering models are used to overcome this problem. In this paper, fuzzy logic and genetic algorithm are combined to increase the lifetime of the wireless sensor network. In other words, fuzzy logic is used to introduce the best nodes, those that in comparison to other nodes have more energy, density and centrality, to base station as cluster head candidate. Then, the number and place of cluster heads are determined in base station by using genetic algorithm. Also, the network acts heterogeneously and includes several nodes with different parameters.

scholarly journals E-FUCA: enhancement in fuzzy unequal clustering and routing for sustainable wireless sensor network

2021 ◽  
Author(s):  
Pawan Singh Mehra
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Average Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Hole ◽  
Intelligent Decision ◽  
Improved Performance

AbstractWith huge cheap micro-sensing devices deployed, wireless sensor network (WSN) gathers information from the region and delivers it to the base station (BS) for further decision. The hotspot problem occurs when cluster head (CH) nearer to BS may die prematurely due to uneven energy depletion resulting in partitioning the network. To overcome the issue of hotspot or energy hole, unequal clustering is used where variable size clusters are formed. Motivated from the aforesaid discussion, we propose an enhanced fuzzy unequal clustering and routing protocol (E-FUCA) where vital parameters are considered during CH candidate selection, and intelligent decision using fuzzy logic (FL) is taken by non-CH nodes during the selection of their CH for the formation of clusters. To further extend the lifetime, we have used FL for the next-hop choice for efficient routing. We have conducted the simulation experiments for four scenarios and compared the propound protocol’s performance with recent similar protocols. The experimental results validate the improved performance of E-FUCA with its comparative in respect of better lifetime, protracted stability period, and enhanced average energy.

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 Security Techniques for Wormhole Attack in Wireless Sensor Networks

2018 ◽  
Vol 7 (2.23) ◽  
pp. 59 ◽  
Author(s):  
Surinder Singh ◽  
Hardeep Singh Saini
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Packet Transmission ◽  
Wireless Sensor ◽  
Security Threat ◽  
Wormhole Attack ◽  
Protocol Security ◽  
Routing Mechanism ◽  
Packet Drop

The wireless sensor network has group of sensors which can sense the data and route this data to base station. As there is no physical connection between sensor and base station the important data can be routed without wires. The broadcast nature of wireless sensor network makes it prone to security threat to the valuable data. The attacker node can detect the data by creating their own data aggregation and routing mechanism .The number of attacks can be possible on the network layer. Out of these attacks wormhole is one of the major attack which can change the routing method of the whole wireless sensor network. In this attack,the attacker node can control the packet transmission of whole network and route it to the tunnel of nodes. The major drawback of this attack is to increase the packet drop and disturbing the routing mechanism. A number of security techniques are developed by the researcher to reduce the packet drop ratio and secure the routing mechanism of the network. Out of all thesetechniquesfew related to packet drop ratio are discussed in this paper. TheLightweight countermeasure for the wormhole attack (LITEWORP) based on Dynamic Source routing (DSR) protocol security technique,Delay Per Hop Indication (Delphi) based on AODV(Avoidance Routing Protocol) Protocol security technique and MOBIWORP based on DSRprotocol security technique reduce the packet loss percentage 40%,43% and 35% respectively.   

scholarly journals An Enhanced Clustering Method for Extending Sensing Lifetime of Wireless Sensor Network

2021 ◽  
pp. 67-82
Author(s):  
Yakubu Abdul-Wahab Nawusu ◽  
Alhassan Abdul-Barik ◽  
Salifu Abdul-Mumin
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Performance ◽  
Rank Order ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Heterogeneous Wireless Sensor Network

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.

scholarly journals Wormhole Detection Mechanism in Wireless Sensor Networks

2020 ◽  
Vol 9 (2) ◽  
pp. 1845-1847
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Health Care Environment ◽  
Detection Mechanism ◽  
Primary Base ◽  
Power And Energy

A Wireless Sensor Network (WSN) is a component with sensor nodes that continuously observes environmental circumstances. Sensor nodes accomplish different key operations like sensing temperature and distance. It has been used in many applications like computing, signal processing, and network selfconfiguration to expand network coverage and build up its scalability. The Unit of all these sensors that exhibit sensing and transmitting information will offer more information than those offered by autonomously operating sensors. Usually, the transmitting task is somewhat critical as there is a huge amount of data and sensors devices are restricted. Being the limited number of sensor devices the network is exposed to different types of attacks. The Traditional security mechanisms are not suitable for WSN as they are generally heavy and having limited number of nodes and also these mechanisms will not eliminate the risk of other attacks. WSN are most useful in different crucial domains such as health care, environment, industry, and security, military. For example, in a military operation, a wireless sensor network monitors various activities. If an event is detected, these sensor nodes sense that and report the data to the primary (base) station (called sink) by making communication with other nodes. To collect data from WSN base Stations are commonly used. Base stations have more resources (e.g. computation power and energy) compared to normal sensor nodes which include more or less such limitations. Aggregation points will gather the data from neighboring sensor nodes to combine the data and forward to master (base) stations, where the data will be further forwarded or processed to a processing center. In this manner, the energy can be preserved in WSN and the lifetime of network is expanded.

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