scholarly journals A review on classification of imbalanced data for wireless sensor networks

2020 ◽  
Vol 16 (4) ◽  
pp. 155014772091640 ◽  
Author(s):  
Harshita Patel ◽  
Dharmendra Singh Rajput ◽  
G Thippa Reddy ◽  
Celestine Iwendi ◽  
Ali Kashif Bashir ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Imbalanced Data ◽  
Review Article ◽  
Wireless Sensor ◽  
Uneven Distribution ◽  
Present Decade

Classification of imbalanced data is a vastly explored issue of the last and present decade and still keeps the same importance because data are an essential term today and it becomes crucial when data are distributed into several classes. The term imbalance refers to uneven distribution of data into classes that severely affects the performance of traditional classifiers, that is, classifiers become biased toward the class having larger amount of data. The data generated from wireless sensor networks will have several imbalances. This review article is a decent analysis of imbalance issue for wireless sensor networks and other application domains, which will help the community to understand WHAT, WHY, and WHEN of imbalance in data and its remedies.

Application of Computational Intelligence Techniques in Wireless Sensor Networks the State of the Art

2020 ◽  
pp. 1580-1600
Author(s):  
Subhendu Kumar Pani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Computational Intelligence ◽  
State Of The Art ◽  
Area Coverage ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Sensor Devices ◽  
Huge Variety

A wireless sensor network may contain hundreds or even tens of thousands of inexpensive sensor devices that can communicate with their neighbors within a limited radio range. By relaying information on each other, they transmit signals to a command post anywhere within the network. Worldwide market for wireless sensor networks is rapidly growing due to a huge variety of applications it offers. In this chapter, we discuss application of computational intelligence techniques in wireless sensor networks on the coverage problem in general and area coverage in particular. After providing different types of coverage encountered in WSN, we present a possible classification of coverage algorithms. Then we dwell on area coverage which is widely studied due to its importance. We provide a survey of literature on area coverage and give an account of its state-of-the art and research directions.

Application of Computational Intelligence Techniques in Wireless Sensor Networks the State of the Art

2016 ◽  
pp. 441-461
Author(s):  
Subhendu Kumar Pani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Computational Intelligence ◽  
State Of The Art ◽  
Area Coverage ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Sensor Devices ◽  
Huge Variety

A wireless sensor network may contain hundreds or even tens of thousands of inexpensive sensor devices that can communicate with their neighbors within a limited radio range. By relaying information on each other, they transmit signals to a command post anywhere within the network. Worldwide market for wireless sensor networks is rapidly growing due to a huge variety of applications it offers. In this chapter, we discuss application of computational intelligence techniques in wireless sensor networks on the coverage problem in general and area coverage in particular. After providing different types of coverage encountered in WSN, we present a possible classification of coverage algorithms. Then we dwell on area coverage which is widely studied due to its importance. We provide a survey of literature on area coverage and give an account of its state-of-the art and research directions.

scholarly journals Hierarchical classification of time series data aggregation in underwater wireless sensor networks

2020 ◽  
Vol 37 (2) ◽  
pp. 53-64
Author(s):  
Durairaj Ruby ◽  
Jayachandran Jeyachidra
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Error Rate ◽  
Data Aggregation ◽  
Hierarchical Classification ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks

Environmental fluctuations are continuous and provide opportunities for further exploration, including the study of overground, as well as underground and submarine, strata. Underwater wireless sensor networks (UWSNs) facilitate the study of ocean-based submarine and marine parameters details and data. Hardware plays a major role in monitoring marine parameters; however, protecting the hardware deployed in water can be difficult. To extend the lifespan of the hardware, the inputs, processing and output cycles may be reduced, thus minimising the consumption of energy and increasing the lifespan of the devices. In the present study, time series similarity check (TSSC) algorithm is applied to the real-time sensed data to identify repeated and duplicated occurrences of data for reduction, and thus improve energy consumption. Hierarchical classification of ANOVA approach (HCAA) applies ANOVA (analysis of variance) statistical analysis model to calculate error analysis for realtime sensed data. To avoid repeated occurrences, the scheduled time to read measurements may be extended, thereby reducing the energy consumption of the node. The shorter time interval of observations leads to a higher error rate with lesser accuracy. TSSC and HCAA data aggregation models help to minimise the error rate and improve accuracy.

scholarly journals DESIGN ISSUES AND CLASSIFICATION OF WSNS OPERATING SYSTEMS

2013 ◽  
pp. 281-285
Author(s):  
ANIL KUMAR SHARMA ◽  
SURENDRA KUMAR PATEL ◽  
GUPTESHWAR GUPTA
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Operating Systems ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Design Issues ◽  
Wireless Sensor Nodes ◽  
Computing Environments ◽  
Computational Resources

Wireless Sensor Networks is an emerging area of research. Wireless Sensor networks (WSNs) face lot of problems that do not arise in other types of wireless networks and computing environments. Limited computational resources, power constraints, low reliability and higher density of sensor nodes (motes) are just some basic problems that have to be considered when designing or selecting a new operating system in order to evaluate the performance of wireless sensor nodes (motes). In this paper we focused on design issues, challenges and classification of operating systems for WSNs.

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