scholarly journals Estimating the impact of adding sensor nodes to biomedical wireless sensor networks

2015 ◽  
Author(s):  
Carlos Abreu ◽  
Francisco Miranda ◽  
Paulo Mateus Mendes
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Impact

An energy minimizing score based optimal data gathering in wireless sensor networks

2018 ◽  
Vol 7 (2.31) ◽  
pp. 161
Author(s):  
P Balamurugan ◽  
M Shyamala Devi ◽  
V Sharmila
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Manner ◽  
High Level ◽  
The Impact

In wireless sensor networks, Sensor nodes are arranged randomly in unkind physical surroundings to collect data and distribute the data to the remote base station. However the sensor nodes have to preserve the power source that has restricted estimation competence. The sensed information is difficult to be transmitted over the sensor network for a long period of time in an energy efficient manner.  In this paper, it finds the problem of communication data between sink nodes and remote data sources via intermediate nodes in sensor field. So this paper proposes a score based data gathering algorithm in wireless sensor networks. The high-level contribution of this study is the enhancement of a score- based data gathering algorithm and the impact of energy entity for Wireless Sensor Networks.  Then the energy and delay of data gathering are evaluated. Unlike PEGASIS and LEACH, the delay for every process of data gathering is considerably lower when SBDG is employed.  The energy consumed per round of data gathering for both SBDG and EE-SBDG is less than half of that incurred with PEGASIS and LEACH. Compared with LEACH and PEGASIS, SBDG and EE-SBDG are fair with node usage because of the scoring system and residual energy respectively.  Overall, the Score-based data gathering algorithm provides a significant solution to maximize the network lifetime as well as minimum delay per round of data gathering.

scholarly journals Analysis of AODV protocol under sinkhole attack in wireless sensor network

2018 ◽  
Vol 7 (2.4) ◽  
pp. 153
Author(s):  
Harkesh Sehrawat ◽  
Yudhvir Singh ◽  
Vikas Siwach
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Attacks ◽  
Aodv Protocol ◽  
The Impact

A Wireless Sensor Network (WSNs) is a collection of number of sensor nodes which are left open in an unsecured environment. Sensor nodes work and communicate together to attain the desired goals. They are placed at the locations where monitoring is otherwise impossible. Wireless Sensor Networks are resource constrained which may be computational power, memory capacity, battery power etc. As Wireless Sensor Networks are implemented in the unattended environment, they are prone to discrete type of security attacks. Because of their limitations these networks are easily targeted by intruders. Sinkhole attack is one of the security attacks which try to disturb the ongoing communication in wireless sensor network. In sinkhole attack, the intruder or the malicious node try to attract the network traffic towards itself, that sensor nodes will pass data packets through this compromised node thereby manipulating messages which sensor nodes are transferring to the base station. In this paper we analyze the impact of Sinkhole attack on AODV protocol under various conditions. We analyzed the impact of Sinkhole attack on AODV protocol with varying number of attacker nodes.  

scholarly journals Machine Learning Based Localization in Large-Scale Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4179 ◽  
Author(s):  
Ghulam Bhatti
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Regression Model ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Support Vector ◽  
Regression Problem ◽  
The Impact

The rapid proliferation of wireless sensor networks over the past few years has posed some serious technical challenges to researchers. The primary function of a multi-hop wireless sensor network (WSN) is to collect and forward sensor data towards the destination node. However, for many applications, the knowledge of the location of sensor nodes is crucial for meaningful interpretation of the sensor data. Localization refers to the process of estimating the location of sensor nodes in a WSN. Self-localization is required in large wireless sensor networks where these nodes cannot be manually positioned. Traditional methods iteratively localize these nodes by using triangulation. However, the inherent instability in wireless signals introduces an error, however minute it might be, in the estimated position of the target node. This results in the embedded error propagating and magnifying rapidly. Machine learning based localizing algorithms for large wireless sensor networks do not function in an iterative manner. In this paper, we investigate the suitability of some of these algorithms while exploring different trade-offs. Specifically, we first formulate a novel way of defining multiple feature vectors for mapping the localizing problem onto different machine learning models. As opposed to treating the localization as a classification problem, as done in the most of the reported work, we treat it as a regression problem. We have studied the impact of varying network parameters, such as network size, anchor population, transmitted signal power, and wireless channel quality, on the localizing accuracy of these models. We have also studied the impact of deploying the anchor nodes in a grid rather than placing these nodes randomly in the deployment area. Our results have revealed interesting insights while using the multivariate regression model and support vector machine (SVM) regression model with radial basis function (RBF) kernel.

Network-Wide Broadcast Service in Wireless Sensor Networks

2010 ◽  
pp. 404-421
Author(s):  
Feng Wang ◽  
Jiangchuan Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Lower Bounds ◽  
Adaptive Algorithm ◽  
Network Size ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wide Range ◽  
The Common ◽  
The Impact

Network-wide Broadcast is one of the most fundamental services in wireless sensor networks (WSNs). It facilitates sensor nodes to propagate messages across the whole network, serving a wide range of higher-level operations and thus being critical to the overall network design. A distinct feature of WSNs is that many sensor nodes alternate between the active state and the dormant state, so as to conserve energy and extend the lifetime of the network. Unfortunately, the impact of such cycles has been largely ignored in existing network-wide broadcast implementations that adopt the common assumption of all sensor nodes being active all over the whole broadcast process. In this chapter, we first provide a brief survey on previous research works on network-wide broadcast services. We then revisit the network-wide broadcast problem by remodeling it with active/dormant cycles and showing the practical lower bounds for the time and message costs, respectively. We also propose an adaptive algorithm named RBS (Reliable Broadcast Service) for dynamic message forwarding scheduling in this context, which enables a reliable and efficient broadcast service with low delay. The performance of the proposed solution is evaluated under diverse network configurations. The results suggest that the proposed solution is close to the lower bounds of both time and forwarding costs, and it well resists to the network size and wireless loss increases.

scholarly journals An improved node localization algorithm based on DV-Hop for wireless sensor networks

2011 ◽  
Vol 8 (4) ◽  
pp. 953-972 ◽  
Author(s):  
Qingji Qian ◽  
Xuanjing Shen ◽  
Haipeng Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Location Error ◽  
Node Localization ◽  
Localization Algorithms ◽  
Node Location ◽  
The Impact

Sensor node localization is the basis for the entire wireless sensor networks. Because of restricted energy of the sensor nodes, the location error, costs of communication and computation should be considered in localization algorithms. DV-Hop localization algorithm is a typical positioning algorithm that has nothing to do with distance. In the isotropic dense network, DV-Hop can achieve position more precisely, but in the random distribution network, the node location error is great. This paper summed up the main causes of error based on the analysis on the process of the DV-Hop algorithm, aimed at the impact to the location error which is brought by the anchor nodes of different position and different quantity, a novel localization algorithm called NDVHop_Bon (New DV-Hop based on optimal nodes) was put forward based on optimal nodes, and it was simulated on Matlab. The results show that the new proposed location algorithm has a higher accuracy on localization with a smaller communication radius in the circumstances, and it has a wider range of applications.

scholarly journals Reliability and Energy Efficiency of DEAR Protocol with Cooperative Caching in IEEE802.15.4 based large ubiquitous Wireless Sensor Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 2140-2145
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Reliability ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cooperative Caching ◽  
Sink Node ◽  
Energy Aware ◽  
The Impact

Reliability and Energy Consumption issues in large ubiquitous Wireless Sensor Networks are a cause of concern especially because there is an inherent conflict between the two: an increase in reliability usually leads to an increase in energy consumption. Conversely, energy conservation has been a priority research concern in wireless sensor nodes. Data aggregation from various nodes and its transmission to the sink node through multiple hops which is important for network reliability increases the overall energy consumption in the network. Several schemes were proposed in the past to address the reliability needs and also to minimize the energy consumption in the network. In this context, this paper proposes a novel strategy for IEEE802.15.4/ZigBee based networks by incorporating a Distributed Energy Aware Routing (DEAR) protocol with a localized Cooperative Caching algorithm that addresses the query generated by a requester node or sink node with datum already existing in the locally available cache memory or in the memory of its one-hop neighbors or by the source node. The DEAR protocol considers battery level as a key factor to include nodes in its routing path. The proposed model is evaluated on the basis of three scenarios which were considered to illustrate the impact of energy consumption on the reliability of WSNs.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

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