scholarly journals Applications of Prediction approaches in Wireless Sensor Networks

2021 ◽  
Author(s):  
Felicia Engmann ◽  
Kofi Sarpong Adu-Manu ◽  
Jamal-Deen Abdulai ◽  
Ferdinand Apietu Katsriku
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Topology ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Continuous Data ◽  
Duty Cycling ◽  
Ambient Data ◽  
Energy Constrained ◽  
And Performance

Wireless Sensor Networks (WSNs) collect data and continuously monitor ambient data such as temperature, humidity and light. The continuous data transmission of energy constrained sensor nodes is a challenge to the lifetime and performance of WSNs. The type of deployment environment is also and the network topology also contributes to the depletion of nodes which threatens the lifetime and the also the performance of the network. To overcome these challenges, a number of approaches have been proposed and implemented. Of these approaches are routing, clustering, prediction, and duty cycling. Prediction approaches may be used to schedule the sleep periods of nodes to improve the lifetime. The chapter discusses WSN deployment environment, energy conservation techniques, mobility in WSN, prediction approaches and their applications in scheduling the sleep/wake-up periods of sensor nodes.

scholarly journals A Provably Secure Three-Factor Authentication Protocol for Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tsu-Yang Wu ◽  
Lei Yang ◽  
Zhiyuan Lee ◽  
Shu-Chuan Chu ◽  
Saru Kumari ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Formal Analysis ◽  
Authentication Protocol ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Computational Overhead ◽  
And Performance ◽  
Three Factor

The wireless sensor network is a network composed of sensor nodes self-organizing through the application of wireless communication technology. The application of wireless sensor networks (WSNs) requires high security, but the transmission of sensitive data may be exposed to the adversary. Therefore, to guarantee the security of information transmission, researchers propose numerous security authentication protocols. Recently, Wu et al. proposed a new three-factor authentication protocol for WSNs. However, we find that their protocol cannot resist key compromise impersonation attacks and known session-specific temporary information attacks. Meanwhile, it also violates perfect forward secrecy and anonymity. To overcome the proposed attacks, this paper proposes an enhanced protocol in which the security is verified by the formal analysis and informal analysis, Burross-Abadii-Needham (BAN) logic, and ProVerif tools. The comparison of security and performance proves that our protocol has higher security and lower computational overhead.

scholarly journals SECURED DATA AGGREGATION METHODS IN WIRELESS SENSOR NETWORKS USING HOMOMORPHIC OPERATION - A REVIEW

2017 ◽  
Vol 10 (13) ◽  
pp. 328
Author(s):  
Shahina K ◽  
Vaidehi Vijayakumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Issues ◽  
Aggregation Methods ◽  
Energy Constrained ◽  
Secured Data

Wireless sensor networks are energy constrained. Data aggregation is an important mechanism for achieving energy efficiency in such networks. The aggregation reduces redundancy in data transmission which results in improved energy usage. Several security issues are there in data aggregation, which includes data confidentiality, data integrity, availability, and freshness. Such issues become complex since WSN is deployed in hostile and unattended environment. So the sensor nodes may fail and compromised by adversaries. Secured data aggregation in sensor network is a topic of research.  Many solutions are proposed for secured data aggregation, using different encryption methods. Homomorphic encryption is one of such technique. In homomorphic encryption, all the nodes participate in the aggregation. Here, nodes can’t see any intermediate or final result but the aggregation is efficient. In this paper, secured data aggregation methods are classified and the performance is compared in terms of integrity and confidentiality.

scholarly journals Reinforcement Learning-Based Data Forwarding in Underwater Wireless Sensor Networks with Passive Mobility

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 256 ◽  
Author(s):  
Haotian Chang ◽  
Jing Feng ◽  
Chaofan Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mobility Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Energy Constrained

Data forwarding for underwater wireless sensor networks has drawn large attention in the past decade. Due to the harsh underwater environments for communication, a major challenge of Underwater Wireless Sensor Networks (UWSNs) is the timeliness. Furthermore, underwater sensor nodes are energy constrained, so network lifetime is another obstruction. Additionally, the passive mobility of underwater sensors causes dynamical topology change of underwater networks. It is significant to consider the timeliness and energy consumption of data forwarding in UWSNs, along with the passive mobility of sensor nodes. In this paper, we first formulate the problem of data forwarding, by jointly considering timeliness and energy consumption under a passive mobility model for underwater wireless sensor networks. We then propose a reinforcement learning-based method for the problem. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate the validity of the proposed method. Our method outperforms the benchmark protocols in both timeliness and energy efficiency. More specifically, our method gains 83.35% more value of information and saves up to 75.21% energy compared with a classic lifetime-extended routing protocol (QELAR).

A Clustering Algorithm for Wireless Sensor Networks Basing on Distance and Distribution

2011 ◽  
Vol 474-476 ◽  
pp. 1221-1227
Author(s):  
Ying Liao ◽  
Wei Xu Hao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Topology ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Network ◽  
The Common

Wireless sensor networks (WSNs) detect and monitor the outside physical state by the sensor nodes organizing automatically. Utilizing clustering algorithm to form hierarchical network topology is the common method which implements managing network and aggregating data in WSNs. Different from the previous clustering algorithms, this article proposes a clustering algorithm for WSNs based on distance and distribution to generate clusters considering residual energy of nods in WSNs with inhomogeneous distribution. The simulation result indicates that the algorithm can establish more balanceable clustering structure effectively and enhance the network life cycle obviously.<b></b>

scholarly journals Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Ali Shareef ◽  
Yifeng Zhu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Petri Nets ◽  
Petri Net ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimal Energy ◽  
Maximum Utility ◽  
Energy Constrained

Energy consumption of energy-constrained nodes in wireless sensor networks (WSNs) is a fatal weakness of these networks. Since these nodes usually operate on batteries, the maximum utility of the network is dependent upon the optimal energy usage of these nodes. However, new emerging optimal energy consumption algorithms, protocols, and system designs require an evaluation platform. This necessitates modeling techniques that can quickly and accurately evaluate their behavior and identify strengths and weakness. We propose Petri nets as this ideal platform. We demonstrate Petri net models of wireless sensor nodes that incorporate the complex interactions between the processing and communication components of an WSN. These models include the use of both an open and closed workload generators. Experimental results and analysis show that the use of Petri nets is more accurate than the use of Markov models and programmed simulations. Furthermore, Petri net models are extremely easier to construct and test than either. This paper demonstrates that Petri net models provide an effective platform for studying emerging energy-saving strategies in WSNs.

Data Gathering with Multi-Attribute Fusion in Wireless Sensor Networks

2011 ◽  
pp. 159-181 ◽  
Author(s):  
Kai Lin ◽  
Lei Wang ◽  
Lei Shu ◽  
Al-Sakib Khan Pathan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Conservation ◽  
Data Gathering ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Physical Attributes ◽  
And Performance ◽  
Save Energy ◽  
Conservation Efficiency

This chapter addresses the problem of data gathering with multi-attribute fusion over a bandwidth and energy constrained wireless sensor network (WSN). As there are strong correlations between data gathered from sensor nodes in close physical proximity, effective in-network fusion schemes involve minimizing such redundancy and hence reducing the load in wireless sensor networks. Considering a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets; hence, the complexity for the fusion process is increased due to the existence of various physical attributes. In this chapter, by investigating the process and performance of multi-attribute fusion in data gathering of WSNs, we design a self-adaptive threshold to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Then, a novel energy equilibrium routing method is proposed to balance and save energy in WSNs, which is named multi-attribute fusion tree (MAFT). The establishment of MAFT is determined by the remaining energy of sensor nodes and the energy-conservation efficiency of data fusion. Finally, the energy saving performance of the scheme is demonstrated through comprehensive simulations. The chapter concludes by identifying some open research issues on this topic.

scholarly journals Cluster Based Techniques LEACH and Modified LEACH using Optimized Technique EHO in WSN

2019 ◽  
Vol 8 (9S) ◽  
pp. 363-372
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Research Work ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Adaptive Clustering ◽  
Long Time ◽  
And Performance

In the last few years, the Internet of Things (IoT) and the advance wireless networks are becoming very prominent in various domains. Wireless Sensors are facing problems of frequent energy loss which affects to the lifetime of the entire network. There are number of researchers who are working on such energy losses which occur in the wireless sensor nodes by using various approaches. One such method is Low- energy adaptive clustering hierarchy (LEACH) and its number of methods. Despite of various methods of LEACH, there is still immense scope of research as it is highly used in sensor nodes for different scenarios. The emerging growth of energy aware wireless sensor networks for a long time leads to various problems related to the lifetime of nodes in the wireless environment. In our research paper, a new and performance aware approach named Elephant Herd Optimization based Cluster Head Selection is devised and simulated so that the optimization level can be achieved. The nature inspired soft computing approaches are always beneficial for the use of optimization and reduction of various problems which can occur during energy optimization and this is the main focus which is considered in this research work. The main fundamental concept of the cluster head shuffling using EHO and other methods of key exchange are simulated in Contiki-Cooja which is an open source simulator for wireless sensor networks

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.

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