Simulation Based Topology Optimization in Wireless Sensor Network

2019 ◽  
Vol 13 (3) ◽  
pp. 274-280
Author(s):  
Jeetu Sharma ◽  
Reema Singh Chauhan ◽  
Akanksha Shukla
Keyword(s):  
Data Aggregation ◽  
Performance Metrics ◽  
Research Work ◽  
Environmental Parameters ◽  
Sensor Nodes ◽  
Node Placement ◽  
Optimum Performance ◽  
Nodal Distance ◽  
End To End Delay ◽  
End To End

Background: Wireless Sensor Network (WSN) is among the most promising technologies that can be used to monitor crucial ambient conditions. WSNs are capable of effectively monitoring the environmental parameters and any habitat necessary to be investigated. Sometimes, it is very important to periodically monitor the critical environmental parameters such as humidity, temperature, soil moisture, fire, volcanic eruptions, Tsunamis, seismic waves and many more to react proactively to save lives and assets. This research work is an endeavor to present the importance and to determine the precise inter- nodal distance required for distinct applications. The networks of the different terrain area and internodal distance are deployed to evaluate and analyze the performance metrics such as a number of messages received average end to end delay (secs), throughput (bps) and jitter (secs). The influence of varying inter-nodal distance on the performance of WSN is determined to select the most appropriate value of the distance between nodes in particular monitoring application. The patents related to the topology based analysis of wireless nodes are reconsidered. Methods: The placement of nodes and inter-nodal distance significantly influences the operation and performance of WSNs by diverging the ability of sensors to observe an event of interest and transmission of information to data aggregation nodes (sink nodes). Moreover, effective sensor placement also affects the resource management. The investigation of specific regions and habitats has peculiar constraints of node placement and inter-nodal distance making it highly application specific. In this research work, the intent is to monitor an entire area to attain optimum coverage to detect the occurrence of a significant event. The node placement and inter-nodal distance can be classified on the basis of the role played by the deployed nodes, like, placement of ordinary sensor nodes/Reduced Function Devices (RFDs) and relay nodes/Full Function Devices (FFDs), respectively. The sensors are compatible with IEEE 802.15.4/ZigBee protocol and application implemented is Constant Bit Rate (CBR) generator. This paper analyzed and evaluated the influence of placement and inter-nodal distance of RFDs to the data aggregation ability of sink node. The terrain area (m2) of different sensor networks deployed are 110×110, 200×200, 300×300, 400×400 and 500×500, respectively. The number of sensor nodes is constant equal to 100 to evaluate their ability to provide optimum performance. The parameter internodal distance is varied, keeping all other parameters constant to effectively evaluate its influence. The simulations are carried out on QualNet 6.1 simulator. Results: The variation in inter-nodal distance significantly influences the performance metrics of the network such as the number of messages received, average end to end delay, throughput and jitter. In this paper, the distance between sensor nodes and terrain areas of grid topology is varied accordingly to deduce that which value of the inter-nodal distance and network provides optimum performance. The thorough evaluation of the simulation results presented that the inter-nodal distance of 30 m and terrain area of 300×300 m2 has generated optimum performance by providing the highest number of messages received (208) and highest throughput (2544.34 bps). It is also capable of providing minimum end to end delay (14.45 secs) and lowest jitter (6.67 secs). Conclusion: The objective of this paper to determine the optimum inter-nodal distance and terrain area of a WSN of 100 nodes is successfully achieved. It is analyzed and evaluated that the inter-nodal distance of 30 m and terrain area of 300×300 m2 enhance and optimize the network performance significantly.

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

2016 ◽  
Vol 1 (2) ◽  
pp. 1-7
Author(s):  
Karamjeet Kaur ◽  
Gianetan Singh Sekhon
Keyword(s):  
Sensor Networks ◽  
Threshold Value ◽  
Critical Issue ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Research Subjects ◽  
Malicious Nodes ◽  
Intermediate Node ◽  
End To End Delay ◽  
End To End

Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

Secure Buffer-Based Routing Protocol for WMN

2017 ◽  
Vol 13 (1) ◽  
pp. 28-44
Author(s):  
Geetanjali Rathee ◽  
Hemraj Saini
Keyword(s):  
Routing Protocol ◽  
Performance Metrics ◽  
Packet Delivery Ratio ◽  
Secure Routing ◽  
Delivery Ratio ◽  
Link Failure ◽  
Packet Delivery ◽  
End To End Delay ◽  
End To End ◽  
Network Metrics

Secure routing is considered as one of a key challenge in mesh networks because of its dynamic and broadcasting nature. The broadcasting nature of mesh environment invites number of security vulnerabilities to come and affect the network metrics drastically. Further, any node/link failure of a routed path may reduce the performance of the entire network. A number of secure routing protocols have been proposed by different researchers but enhancement of a single network parameter (i.e. security) may affect another performance metrics significantly i.e. throughput, end to end delay, packet delivery ratio etc. In order to ensure secure routing with improved network metrics, a Secure Buffer based Routing Protocol i.e. SBRP is proposed which ensures better network performance with increased level of security. SBRP protocol uses buffers at alternate positions to fasten re-routing mechanism during node/link failure and ensures the security using AES encryption. Further the protocol is analyzed against mAODV protocol in both static and dynamic environment in terms of security, packet delivery ratio, end to end delay and network throughput.

Geometric sequence based multipath routing protocol for multi-hop ad hoc networks

2016 ◽  
Vol 12 (4) ◽  
pp. 394-407 ◽  
Author(s):  
Yahya M. Tashtoush ◽  
Mohammad A. Alsmirat ◽  
Tasneem Alghadi
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Transmission Rate ◽  
Multipath Routing ◽  
Delivery Ratio ◽  
Content Type ◽  
End To End Delay ◽  
Geometric Sequence ◽  
End To End

Purpose The purpose of this paper is to propose, a new multi-path routing protocol that distributes packets over the available paths between a sender and a receiver in a multi-hop ad hoc network. We call this protocol Geometric Sequence Based Multipath Routing Protocol (GMRP). Design/methodology/approach GMRP distributes packets according to the geometric sequence. GMRP is evaluated using GloMoSim simulator. The authors use packet delivery ratio and end-to-end delay as the comparison performance metrics. They also vary many network configuration parameters such as number of nodes, transmission rate, mobility speed and network area. Findings The simulation results show that GMRP reduces the average end-to-end delay by up to 49 per cent and increases the delivery ratio by up to 8 per cent. Originality/value This study is the first to propose to use of geometric sequence in the multipath routing approach.

scholarly journals Energy Efficient Technique for Data Aggregation in Internet of Things

2020 ◽  
Vol 8 (6) ◽  
pp. 1812-1815
Keyword(s):  
Energy Consumption ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Research Work ◽  
Base Station ◽  
Sensor Nodes ◽  
Fixed Size ◽  
Cluster Heads ◽  
Leach Protocol ◽  
Reduce Energy Consumption

The IOT network is the decentralized type of network which can sense the information and pass it to base station. Due to small size of the sensor nodes, the energy consumption is the major issue of the network. The LEACH is the energy efficient protocol which can divide whole network into fixed size clusters. In each cluster, cluster heads are selected which can transmit data to base station. In this research work, the LEACH protocol is improved to reduce energy consumption of the wireless sensor networks. In the proposed improvement, the cache nodes are deployed which can aggregate data from the cluster heads and then pass data to base station. The simulation of the proposed technique is done in MATLAB and results are compared with the existing approach in terms of certain parameters. It is analyzed that proposed technique performs well as compared to existing technique.

scholarly journals Improving Animal-Human Cohabitation withMachine Learning in Fiber-Wireless Networks

2018 ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Francisco Carpio ◽  
Admela Jukan
Keyword(s):  
Machine Learning ◽  
Fog Computing ◽  
Warning System ◽  
Access Networks ◽  
Sensor Nodes ◽  
Base Stations ◽  
Dynamic Allocation ◽  
End To End Delay ◽  
Processing Data ◽  
End To End

In this paper, we investigate an animal-human cohabitation problem with the help of machine learning and fiber-wireless (FiWi) access networks integrating cloud and edge (fog) computing. We propose an early warning system which detects wild animals nearby road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing. Additionally, we show that animals' detection at the earliest and the related processing, if possible, at sensors would reduce the energy consumption of edge devices and the end-to-end delay in notifying vehicles, as compared to the scenarios where raw sensed data needs to be transferred up the base stations or the cloud. At the same time, machine learning helps in classification of captured images at edge devices, and in predicting different time-varying traffic profiles-- distinguished by latency and bandwidth requirements-- at base stations, including animal appearance events at sensors, and allocating bandwidth in FiWi access networks accordingly. We compare three scenarios of processing data at sensor nodes, base stations and a hybrid case of processing sensed data at either sensors or at base stations, and showed that dynamic allocation of bandwidth in FiWi access networks and processing data at its origin leads to lowering the congestion of network traffic at base stations and reducing the average end-to-end delay.

scholarly journals A Message Transfer Framework for Enhanced Reliability in Delay-Tolerant Networks

2015 ◽  
Vol 7 (3) ◽  
pp. 52
Author(s):  
Farzana Yasmeen ◽  
Uyen Trang Nguyen ◽  
Nurul Huda ◽  
Shigeki Yamada ◽  
Cristian Borcea
Keyword(s):  
Network Performance ◽  
Performance Metrics ◽  
Delay Tolerant Networks ◽  
Delivery Ratio ◽  
Message Delivery ◽  
Delivery Performance ◽  
End To End Delay ◽  
End To End ◽  
Deadline Constraints ◽  
Delay Tolerant

Delay-tolerant networks (DTNs) can tolerate disruption on end-to-end paths by taking advantage of temporal links emerging between nodes as nodes move in the network. Intermediate nodes store messages before forwarding opportunities become available. A series of encounters (i.e., coming within mutual transmission range) among different nodes will eventually deliver the message to the desired destination. The message delivery performance in a DTN (such as delivery ratio and end-to-end delay) highly depends on the time elapsed between encounters and the time two nodes remain in each others communication range once a contact is established. As messages are forwarded opportunistically among nodes, it is important to have sufficient contact opportunities in the network for faster, more reliable delivery of messages. We propose a simple yet efficient method for improving the performance of a DTN by increasing the contact duration of encountered nodes (i.e., mobile devices). Our proposed sticky transfer framework and protocol enable nodes in DTNs to collect neighbors’ information, evaluate their movement patterns and amounts of data to transfer in order to make decisions of whether to “stick” with a neighbor to complete the necessary data transfers. The sticky transfer framework can be combined with any DTN routing protocol to improve its performance. We evaluate ourframework through simulations and measure several network performance metrics. Simulation results show that the proposed framework can improve the message delivery ratio, end-to-end delay, overhead ratio, buffer occupancy, number of disrupted message transmissions and so on. It can be well adopted for challenged scenarios where larger messages sizes need to be delivered with application deadline constraints. Furthermore, performance of the DTN improved (upto 43%) at higher node densities and (up to 49%) under increased mobility conditions.

scholarly journals Energy Consumption Analysis in WSN Based on Node Placement Strategies

2018 ◽  
Vol 7 (3.12) ◽  
pp. 531
Author(s):  
R Shanmugavalli ◽  
P Subashini
Keyword(s):  
Energy Consumption ◽  
Power Distribution ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Finite Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Node Placement ◽  
Comparison Results

Wireless Sensor Networks (WSNs) is a collection of devices and sensor nodes connected with wireless network and communicate with one another via radio signals. Sensor in WSN is an autonomous (self-configuring) device used to sense the light, heat, motion, moisture and pressure etc that communicate with their neighbor nodes. Node placement is a technique that places the nodes effectively in the specified network environment. In WSN basically, wireless sensor network includes different topologies namely star, point-to-point, ring, bus, mesh and hybrid. In recent years, research has been carried out on different node placement strategies and produced different results based on its performance that includes power distribution and energy consumption of sensors. Energy consumption and network lifetime are considered to be the critical issues as the nodes are powered by the batteries which have finite energy reservoirs. In this paper, three different node placements namely Random, Uniform and Grid with respect to AODV (Ad hoc On-Demand Distance Vector) protocol is evaluated in order to analyze the energy factor during wireless communication. The performance metrics used to measure the analysis are Energy Consumption Average Jitter, Average End-to-End Delay, Average Throughput and Average Packet Delivery Ratio. The comparison results suggests that Grid node placement performs well in grid scenarios and shows best for specific performance metrics.  

scholarly journals Improving Animal-Human Cohabitation with Machine Learning in Fiber-Wireless Networks

2018 ◽  
Vol 7 (3) ◽  
pp. 35 ◽  
Author(s):  
Sandeep Singh ◽  
Francisco Carpio ◽  
Admela Jukan
Keyword(s):  
Machine Learning ◽  
Fog Computing ◽  
Warning System ◽  
Access Networks ◽  
Sensor Nodes ◽  
Base Stations ◽  
Dynamic Allocation ◽  
End To End Delay ◽  
Processing Data ◽  
End To End

In this paper, we investigate an animal-human cohabitation problem with the help of machine learning and fiber-wireless (FiWi) access networks integrating cloud and edge (fog) computing. We propose an early warning system which detects wild animals near the road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing. Additionally, we show that animals’ detection at the earliest and the related processing, if possible, at sensors would reduce the energy consumption of edge devices and the end-to-end delay in notifying vehicles, as compared to the scenarios where raw sensed data needs to be transferred up the base stations or the cloud. At the same time, machine learning helps in classification of captured images at edge devices, and in predicting different time-varying traffic profiles— distinguished by latency and bandwidth requirements—at base stations, including animal appearance events at sensors, and allocating bandwidth in FiWi access networks accordingly. We compare three scenarios of processing data at sensor nodes, base stations and a hybrid case of processing sensed data at either sensors or at base stations, and showed that dynamic allocation of bandwidth in FiWi access networks and processing data at its origin lead to lowering the congestion of network traffic at base stations and reducing the average end-to-end delay.

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