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

2019 ◽  
Vol 8 (4) ◽  
pp. 4000-4005

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.

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Fatemehzahra Gholami Tirkolaei ◽  
Faramarz E. Seraji

<p>Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.</p><p>There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.</p><p>In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.</p>


Wireless Sensor Network (WSN) is a huge collection of sensor nodes deployed without any predetermined infrastructure. They are powered by batteries and energy consumption is one of the major issues in WSN. Hence to prolong the lifetime of the networks, it is important to design the energy efficient optimized routing algorithm. In this paper, two hop forwarding scheme in AODV and Fuzzy Logic is proposed to find an optimal routing protocol and intermediate node acknowledgement is deducted by the use of Fuzzy rules. The parameters such as remaining energy, data packet transmission, packet received acknowledgement and number of rounds is given as input to the fuzzy system which gives an optimized routing decision. The efficacy of the proposed algorithm is evaluated using NS2 and compared with Fuzzy-based Energy-Aware Routing Mechanism (FEARM). The simulation results shows that the Fuzzy based AODV routing algorithm reduces the energy consumption, minimizes the routing response packets and improves the network life time compared to other similar routing protocols.


Author(s):  
Wan Isni Sofiah Wan Din ◽  
Asyran Zarizi Bin Abdullah ◽  
Razulaimi Razali ◽  
Ahmad Firdaus ◽  
Salwana Mohamad ◽  
...  

<span lang="EN-US">Wireless Sensor Network (WSN) is a distributed wireless connection that consists many wireless sensor devices. It is used to get information from the surrounding activities or the environment and send the details to the user for future work. Due to its advantages, WSN has been widely used to help people to collect, monitor and analyse data. However, the biggest limitation of WSN is about the network lifetime. Usually WSN has a small energy capacity for operation, and after the energy was used up below the threshold value, it will then be declared as a dead node. When this happens, the sensor node cannot receive and send the data until the energy is renewed. To reduce WSN energy consumption, the process of selecting a path to the destination is very important. Currently, the data transmission from sensor nodes to the cluster head uses a single hop which consumes more energy; thus, in this paper the enhancement of previous algorithm, which is MAP, the data transmission will use several paths to reach the cluster head. The best path uses a small amount of energy and will take a short time for packet delivery. The element of Shortest Path First (SPF) Algorithm that is used in a routing protocol will be implemented. It will determine the path based on a cost, in which the decision will be made depending on the lowest cost between several connected paths. By using the MATLAB simulation tool, the performance of SPF algorithm and conventional method will be evaluated. The expected result of SPF implementation will increase the energy consumption in order to prolong the network lifetime for WSN.</span>


Wireless Sensor Network is distributed networks of sensors which have the ability to sense, process and communicate. Sensor nodes are also responsible for collection of data. Due to the limited battery power of sensor node energy consumption is an essential issue. To reduce the energy consumption balancing of node load is one of the major task. In this paper, we have used switching algorithm to switch the nodes to balance the node load which further increases the life time of each node by finding the shortest path to destination from the source node based on the threshold energy. Further we applied base localization algorithm to check the lifetime of each node.


2020 ◽  
pp. 1440-1458
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.


Robust and efficient algorithms for routing and other process for a wireless sensor network are under active development due to technological advancements on wireless transmission systems. Each of the sensor nodes in a wireless sensor network either transmits or forwards the data packets to the base station. The main objective of the majority of the work in the literature is to save the energy consumption efficiently. The cluster based routing mechanism helps to achieve low energy consumption within the network. The network organizes its nodes as a cluster and selects a particular node as cluster head to manage the transmission within and between clusters. The majority of the clustering approach selects the cluster head using a thresholding based approach. Nodes having energy level higher than the threshold are the candidates for the cluster head selection. In the proposed approach the nodes remaining energy and the sum of distance between individual nodes to the cluster head node is considered. Optimal cluster head selection will help to increase the overall life time of the network. The distance between the sensor nodes is estimated using RSSI (Received Signal Strength Indicator) and other parameters measured from the physical layer. Experiments are conducted with simulation environment created with the NS-2 simulator and efficiency of the approach is analyzed in detail.


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.


2020 ◽  
Vol 21 (3) ◽  
pp. 555-568
Author(s):  
Anshu Kumar Dwivedi ◽  
A. K. Sharma

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.


2017 ◽  
Vol 4 (4) ◽  
pp. 82-100 ◽  
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.


Author(s):  
S. Venkatesan ◽  
M. Ramakrishnan

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


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