Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach

2016 ◽  
Vol 6 (6) ◽  
pp. 3080 ◽  
Author(s):  
Rajiv R Bhandari ◽  
K Rajasekhar
Keyword(s):  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Routing Algorithm ◽  
Life Time ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Main Task ◽  
Network Life Time

<p>In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer &amp; Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.</p>

scholarly journals Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach

2016 ◽  
Vol 6 (6) ◽  
pp. 3080
Author(s):  
Rajiv R Bhandari ◽  
K Rajasekhar
Keyword(s):  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Routing Algorithm ◽  
Life Time ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Main Task ◽  
Network Life Time

<p>In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer &amp; Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.</p>

scholarly journals An Enhanced Energy Optimization Routing Protocol with Fuzzy Logic in Wireless Sensor Network

2020 ◽  
Vol 9 (5) ◽  
pp. 1200-1206
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Routing Algorithm ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Intermediate Node

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.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2020 ◽  
pp. 1440-1458
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

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.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2017 ◽  
Vol 4 (4) ◽  
pp. 82-100 ◽  
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

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.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

scholarly journals The Improvement of LEACH Algorithm in Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 46 ◽  
Author(s):  
Shujuan Dong ◽  
Cong Li
Keyword(s):  
Routing Algorithm ◽  
Critical Evaluation ◽  
Life Time ◽  
Correlated Data ◽  
Sensor Nodes ◽  
Time Simulation ◽  
Leach Protocol ◽  
Frame Work ◽  
Network Life Time ◽  
Almost All

This paper covers a novel routing algorithm called Multi-Group based LEACH (MG-LEACH) that has been utilized the redundant deployed sensor nodes to improve the network life time. It has been suppressing the correlated data gathered by the sensor nodes by monitoring the similar event. Thus reduces not only the data transmission inside the clusters but also conserve the energy of deployed sensor nodes consequently improve the overall network lifetime. This is a simple idea that has been implemented over LEACH protocol however it is valid for almost all clustering based routing algorithms/protocols specially those variants based upon frame work of LEACH. The proposed routing algorithm has been simulated using MATLAB to verify the efficiency in enhancing network life time. A critical evaluation of routing algorithm is conducted to determine the relevance and applicability in increasing network life time. Simulation results confirmed that it has performed better than LEACH and enhanced network life time up to approximately 90%.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

scholarly journals ENERGY-AWARE SECURITY ROUTING PROTOCOL FOR WSN IN BIG-DATA APPLICATIONS

2019 ◽  
Vol 01 (01) ◽  
pp. 39-55 ◽  
Author(s):  
Smys S
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Routing Protocol ◽  
Life Time ◽  
Wireless Sensor ◽  
Data Generation ◽  
Energy Aware ◽  
Security Issues ◽  
Network Latency ◽  
Network Life Time

The dense deployment of the wireless sensor networks has caused enormous data flow leading to a Big-Data generation. To enable a continuous transmission for the huge volume of data packets, it becomes necessary to readapt the routing protocol to facilitate the routing in handling the Big-data scenario. Since energy is the main constraint in the wireless sensor network, as the sensor are battery powered, and the routing methods consuming enormous of the energy for route discovery thereby reducing the network life time, many conventional methods were developed to address the problem of energy consumption with the, increased network latency, overhead, security issues and delay. So the paper proposes the energy-aware routing protocol that could handle the security issues, arising in the enormous data generation satisfying the QOS requirements. The node with substantial resources are selected to overcome the problems of energy consumption and the network life time handling the security issues , delay, network latency and the overhead problem. Further validation of the proposed method in the Network Simulator-3 is performed to evaluate the network latency, packet delivery ratio, throughput, power consumption, network lifetime and Cost.

scholarly journals Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity

2013 ◽  
pp. 259-273
Author(s):  
Femi A. Aderohunmu ◽  
Jeremiah D. Deng ◽  
Martin Purvis
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Research Question ◽  
Energy Levels ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Complex Functions

While wireless sensor networks (WSN) are increasingly equipped to handle more complex functions, in-network processing still requires the battery-powered sensors to judiciously use their constrained energy so as to prolong the elective network life time. There are a few protocols using sensor clusters to coordinate the energy consumption in a WSN, but how to deal with energy heterogeneity remains a research question. The authors propose a modified clustering algorithm with a three-tier energy setting, where energy consumption among sensor nodes is adaptive to their energy levels. A theoretical analysis shows that the proposed modifications result in an extended network stability period. Simulation has been conducted to evaluate the new clustering algorithm against some existing algorithms under different energy heterogeneity settings, and favourable results are obtained especially when the energy levels are significantly imbalanced.

scholarly journals LEVEL PARTITIONING OF NODES TO ENHANCE THE NETWORK LIFETIME DURING INTRUSION DETECTION IN WIRELESS SENSOR NETWORKS

2013 ◽  
pp. 21-26
Author(s):  
A. BABU KARUPPIAH ◽  
KEERTHINATH KEERTHINATH ◽  
M. KUNDRU MALAI RAJAN ◽  
K.ASHIF ISMAIL SHERIFF ◽  
S. RAJARAM
Keyword(s):  
Sensor Networks ◽  
Intrusion Detection ◽  
Cluster Head ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Efficient Operation ◽  
Network Life Time ◽  
Power Capability

A Wireless Sensor Network (WSN) consists of many sensor nodes with low cost and power capability Based on the deployment, in the sensing coverage of a sensor node, typically more nodes are covered. A major challenge in constructing a WSN is to enhance the network life time. Nodes in a WSN are usually highly energy-constrained and expected to operate for long periods from limited on-board energy reserves. To permit this, nodes and the embedded software that they execute – must have energy-aware operation. Because of this, continued developments in energy-efficient operation are paramount, requiring major advances to be made in energy hardware, power management circuitry and energy aware algorithms znd protocols. During Intrusion Detection in sensor networks, some genuine nodes need to communicate with the Cluster Head to inform about the details of malicious nodes. For such applications in sensor networks, a large number of sensor nodes that are deployed densely in specific sensing environment share the same sensing tasks. Due to this, the individual nodes might waste their energy in sensing data that are not destined to it and as a result the drain in the energy of the node is more resulting in much reduced network life time. In this paper, a novel algorithm is developed to avoid redundancy in sensing the data thereby enhancing the life time of the network. The concept of Power Factor bit is proposed while a node communicates with the Cluster Head. The simulation results show that the network life time is greatly enhanced by the proposed method.

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