Sensor Localization in Wireless Sensor Networks Using Cultural Algorithm

2020 ◽  
Vol 11 (4) ◽  
pp. 106-122
Author(s):  
Vaishali Raghavendra Kulkarni ◽  
Veena Desai
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Particle Swarm Optimization Algorithm ◽  
Computing Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cultural Algorithm ◽  
Sensor Localization ◽  
Bee Colony ◽  
Multi Stage

Evolutionary computing-based cultural algorithm (CA) has been developed for anchor-assisted, range-based, multi-stage localization of sensor nodes of wireless sensor networks (WSNs). The results of CA-based localization have been compared with those of swarm intelligence-based algorithms, namely the artificial bee colony algorithm and the particle swarm optimization algorithm. The algorithms have been compared in terms of mean localization error and computing time. The simulation results show that the CA performs the localization in a more accurate manner and at a higher speed than the other two algorithms.

scholarly journals A Swarm Intelligent Algorithm Based Route Maintaining Protocol for Mobile Sink Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoming Wu ◽  
Yinglong Wang ◽  
Yifan Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Network Resources ◽  
Intelligent Algorithm ◽  
Bee Colony ◽  
Alternative Routing

Recent studies have shown that mobile sink can be a solution to solve the problem that energy consumption of sensor nodes is not balanced in wireless sensor networks (WSNs). Caused by the sink mobility, the paths between the sensor nodes and the sink change frequently and have profound influence on the lifetime of WSN. It is necessary to design a protocol that can find efficient routings between the mobile sink and nodes but does not consume too many network resources. In this paper, we propose a swarm intelligent algorithm based route maintaining protocol to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction and adopts the optimal routing selection to maintain the data delivery route in mobile sink WSN. Using the immune based artificial bee colony (IABC) algorithm to optimize the forwarding path, the routing maintaining protocol could find an alternative routing path quickly and efficiently when the coordinate of sink is changed in WSN. The results of our extensive experiments demonstrate that our proposed route maintaining protocol is able to balance the network traffic load and prolong the network lifetime.

scholarly journals Reputation-Based Secure Sensor Localization in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jingsha He ◽  
Jing Xu ◽  
Xingye Zhu ◽  
Yuqiang Zhang ◽  
Ting Zhang ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Evaluation Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Sensor Localization ◽  
Security Scheme ◽  
Beacon Node ◽  
Untrusted Environments

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments.

Dynamic Deployment of Wireless Sensor Networks by an Improved Artificial Bee Colony Algorithm

2014 ◽  
Vol 511-512 ◽  
pp. 862-866
Author(s):  
Pei Yu He ◽  
Ming Yan Jiang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Coverage Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Selection Probability ◽  
Bee Colony ◽  
Dynamic Deployment

The main objective of dynamic deployment in Wireless Sensor Networks is to use the mobility of sensor nodes, trying to increase the coverage area of the networks through dynamically adjusting the node positions. In this paper, with the characteristics of the optimal sensor deployment in theory, we improve the standard artificial bee colony algorithm by introducing the distance factor to improve the onlooker bees selection probability formula, changing the working mode of the scout bee to avoid worse coverage rate and changing the limit l for scout bee to increase the chance to get better solution. Results show that the improved artificial bee colony algorithm has faster convergent speed and higher coverage rate compared with the standard artificial bee colony algorithm.

scholarly journals Coverage and Deployment Algorithms in Wireless Sensor Networks

2017 ◽  
pp. 148-154
Author(s):  
S. Mini ◽  
Siba K. Udgata
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Effective Coverage ◽  
Bee Colony ◽  
Swarm Algorithms ◽  
Management Schemes ◽  
Coverage Problems

Efficient energy management schemes are essential in a wireless sensor network, since sensor nodes are battery powered. To subdue the energy problem, it is important to have efficient deployment and scheduling mechanisms. A heuristic to solve simple coverage problem, which schedules sensor activity so that all sensor nodes need not be active at the same time, is proposed. Results match the theoretical upper bound for all the experiments. The performance of ABC (Artificial Bee Colony) algorithm in solving deployment problem of wireless sensor networks is also investigated. Since random deployment does not always lead to effective coverage, especially if the sensors are inordinately clustered and there is an inadequate concentration of sensors in some parts of the terrain, this type of deployment at computed optimal locations proves effective. Experiments are carried out for complex cases when certain targets in the region need to be monitored with greater certainty. Preliminary results show that swarm algorithms like ABC and PSO can also be effectively used for area and target coverage problems, in 2-D and 3-D terrains.

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.

A Comparative Study of Computational Intelligence Algorithms for Sensor Localization

2019 ◽  
Vol 9 (2) ◽  
pp. 224-236
Author(s):  
Vaishali R. Kulkarni ◽  
Veena Desai ◽  
Raghavendra Kulkarni
Keyword(s):  
Firefly Algorithm ◽  
Heuristic Algorithms ◽  
Computing Time ◽  
Sensor Nodes ◽  
Convergence Time ◽  
Localization Error ◽  
Location Awareness ◽  
Cultural Algorithm ◽  
Localization Accuracy ◽  
Multi Stage

Background & Objective: Location of sensors is an important information in wireless sensor networks for monitoring, tracking and surveillance applications. The accurate and quick estimation of the location of sensor nodes plays an important role. Localization refers to creating location awareness for as many sensor nodes as possible. Multi-stage localization of sensor nodes using bio-inspired, heuristic algorithms is the central theme of this paper. Methodology: Biologically inspired heuristic algorithms offer the advantages of simplicity, resourceefficiency and speed. Four such algorithms have been evaluated in this paper for distributed localization of sensor nodes. Two evolutionary computation-based algorithms, namely cultural algorithm and the genetic algorithm, have been presented to optimize the localization process for minimizing the localization error. The results of these algorithms have been compared with those of swarm intelligence- based optimization algorithms, namely the firefly algorithm and the bee algorithm. Simulation results and analysis of stage-wise localization in terms of number of localized nodes, computing time and accuracy have been presented. The tradeoff between localization accuracy and speed has been investigated. Results: The comparative analysis shows that the firefly algorithm performs the localization in the most accurate manner but takes longest convergence time. Conclusion: Further, the cultural algorithm performs the localization in a very quick time; but, results in high localization error.

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