scholarly journals Clustered IEEE 802.15.4 Sensor Networks with Data Aggregation: Energy Consumption and Probability of Error

2013 ◽  
Vol 2 (1) ◽  
pp. 70-73 ◽  
Author(s):  
Marco Martalo ◽  
Chiara Buratti ◽  
Gianluigi Ferrari ◽  
Roberto Verdone
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Ieee 802.15.4 ◽  
Probability Of Error

Secured data aggregation in wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Sathya D. ◽  
Ganesh Kumar P.
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Computation Time ◽  
Wireless Sensor ◽  
Content Type ◽  
Homomorphic Cryptosystem ◽  
Secured Data ◽  
Time And Energy

PurposeThis study aims to provide a secured data aggregation with reduced energy consumption in WSN. Data aggregation is the process of reducing communication overhead in wireless sensor networks (WSNs). Presently, securing data aggregation is an important research issue in WSNs due to two facts: sensor nodes deployed in the sensitive and open environment are easily targeted by adversaries, and the leakage of aggregated data causes damage in the networks, and these data cannot be retrieved in a short span of time. Most of the traditional cryptographic algorithms provide security for data aggregation, but they do not reduce energy consumption.Design/methodology/approachNowadays, the homomorphic cryptosystem is used widely to provide security with low energy consumption, as the aggregation is performed on the ciphertext without decryption at the cluster head. In the present paper, the Paillier additive homomorphic cryptosystem and Bonehet al.’s aggregate signature method are used to encrypt and to verify aggregate data at the base station.FindingsThe combination of the two algorithms reduces computation time and energy consumption when compared with the state-of-the-art techniques.Practical implicationsThe secured data aggregation is useful in health-related applications, military applications, etc.Originality/valueThe new combination of encryption and signature methods provides confidentiality and integrity. In addition, it consumes less computation time and energy consumption than existing methods.

scholarly journals An Energy Efficient Secure Data Aggregation in Wireless Sensor Networks

2021 ◽  
Author(s):  
Jenice Prabu A ◽  
Hevin Rajesh D
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Data Communication ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Malicious Nodes ◽  
Aggregated Data

Abstract In Wireless sensor network, the major issues are security and energy consumption. There may be several numbers of malicious nodes present in sensor networks. Several techniques have been proposed by the researchers to identify these malicious nodes. WSNs contain many sensor nodes that sense their environment and also transmit their data via multi-hop communication schemes to the base station. These sensor nodes provides power supply using battery and the energy consumption of these batteries must be low. Securing the data is to avoid attacks on these nodes and data communication. The aggregation of data helps to minimize the amount of messages transmitted within the network and thus reduces overall network energy consumption. Moreover, the base station may distinguish the encrypted and aggregated data based on the encryption keys during the decryption of the aggregated data. In this paper, two aspects of the problem is concerned, we investigate the efficiency of data aggregation: first, how to develop cluster-based routing algorithms to achieve the lowest energy consumption for aggregating data, and second, security issues in wsn. By using Network simulator2 (NS2) this scheme is simulated. In the proposed scheme, energy consumption, packet delivery ratio and throughput is analyzed. The proposed clustering, routing, and protection protocol based on the MCSDA algorithm shows significant improvement over the state-of - the-art protocol.

Adaptive IEEE 802.15.4 MAC Protocol for Wireless Sensor Networks

2015 ◽  
pp. 109-123 ◽  
Author(s):  
Yousef S. Kavian ◽  
Hadi Rasouli
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Duty Cycle ◽  
Network Traffic ◽  
Ieee 802.15.4 ◽  
Extreme Environments ◽  
Wireless Sensor ◽  
Media Access ◽  
The Coordinator

The energy efficiency is a main challenging issue for employing wireless sensor networks (WSNs) in extreme environments where the media access progress consumes the main part of network energy. The IEEE 802.15.4 is adopted in low complexity, ultra-low power and low data rate wireless sensor applications where the energy consumption of nodes should be managed carefully in harsh and inaccessible environments. The beacon-enabled mode of the IEEE 802.15.4 provides a power management scheme. When the network traffic is variable, this mode does not work as well and the coordinator is not capable for estimating the network traffic and adjusting proper duty cycle dynamically. In this chapter an approach for estimating network traffic in star topology is proposed to overcome this issue where the coordinator could estimate the network traffic and dynamically adjusts duty cycle proportion to the variation of network traffic. The simulation results demonstrate the superiority of proposed approach for improving the energy consumption, throughput and delay in comparison with the IEEE 802.15.4 under different traffic conditions.

Body Sensors and Healthcare Monitoring

2012 ◽  
pp. 26-55
Author(s):  
Begonya Otal ◽  
Luis Alonso ◽  
Christos V. Verikoukis
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Ieee 802.15.4 ◽  
Body Sensor Networks ◽  
Mac Layer ◽  
Medical Systems ◽  
Battery Lifetime ◽  
Body Sensors ◽  
Healthcare Monitoring

The aging population and the high expectations towards quality of life in our society lead to the need of more efficient and affordable medical systems and monitoring solutions. The development of wireless Body Sensor Networks (BSNs) offers a platform to establish such a healthcare monitoring systems. However, BSNs in the healthcare domain operate under conflicting requirements. These are the maintenance of the desired reliability and message latency of data transmissions (i.e. quality of service), while simultaneously maximizing battery lifetime of individual body sensors. In doing so, the characteristics of the entire system, especially the Medium Access Control (MAC) layer, have to be considered. For this reason, this chapter aims for the optimization of the MAC layer by using energy-saving techniques for BSNs. The fact that the IEEE 802.15.4 MAC does not fully satisfy BSNs requirements highlights the need for the design of new scalable MAC solutions, which guarantee low-power consumption to the maximum number of body sensors in high density areas (i.e., in saturation conditions). In order to emphasize IEEE 802.15.4 MAC limitations, this chapter presents a detailed overview of this de facto standard for Wireless Sensor Networks (WSNs), which serves as a link for the introduction and description of the here proposed Distributed Queuing (DQ) MAC protocol for BSN scenarios. Within this framework, an extensive DQ MAC energy-consumption analysis in saturation conditions is presented to be able to evaluate its performance in relation to IEEE 802.5.4 MAC in highly dense BSNs. The obtained results show that the proposed scheme outperforms IEEE 802.15.4 MAC in average energy consumption per information bit, thus providing a better overall performance that scales appropriately to BSNs under high traffic conditions. These benefits are obtained by eliminating back-off periods and collisions in data packet transmissions, while minimizing the control overhead.

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 IESDAD :improved energy efficient structure- free data aggregation and delivery protocol in WSN

2018 ◽  
Vol 7 (2.27) ◽  
pp. 132
Author(s):  
Avneet Kaur ◽  
Neeraj Sharma
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Transmission ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Sensor Node ◽  
Base Station ◽  
Wireless Sensor ◽  
Gateway Node ◽  
Free Data

The wireless sensor is deployed to sense large amount of data from the far places. With the large deployment of the sensor networks, it faces major issues like energy consumption, dynamic routing and security. The Energy efficient structure-free data aggregation and delivery (ESDAD) is the protocol which is hierarchal in nature. The ESDAD protocol can be further improved to increase lifetime of wireless sensor networks. The base station localizes the position of each sensor node and defines level of each node for the data transmission. In the ESDAD protocol, the next hop node is selected based on cost function for the data transmission. In this research work, improved in ESDAD protocol is proposed in which gateway nodes are deployed after each level for the data transmission. The sensor node will sense the information and transmit it to gateway node. The gateway node aggregates data to the base station and simulation results show that improved ESDAD protocol performs well in terms of energy consumption and number of throughput. 

Cluster Trisecting Based Data Aggregation Scheme for Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 1126-1130
Author(s):  
Jiang Hong Guo ◽  
De Li Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Important Method ◽  
Cluster Aggregation ◽  
Aggregation Scheme ◽  
Reduce Energy Consumption

Data aggregation is an important method to reduce energy consumption in wireless sensor networks (WSN). Auth-ors proposed a cluster trisecting based data aggregation scheme for wireless sensor networks in which the cluster was trisected and some reporters were assigned to each region. The nodes have same reading and located in same region with reporter will keep silent in data aggregating, thus reducing the inner-cluster transmissions. Analysis and simulation show that the transmissions of inner-cluster aggregation in our scheme lower than that of related schemes and the decrease of trans-missions is obvious when redundancy of sensor readings is high.

scholarly journals A Hybrid Structure for Data Aggregation in Wireless Sensor Network

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hedieh Sajedi ◽  
Zahra Saadati
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Data Aggregation ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Communication Protocol ◽  
Base Station ◽  
Wireless Sensor

In recent years, wireless sensor networks have been used for various applications such as environmental monitoring, military and medical applications. A wireless sensor network uses a large number of sensor nodes that continuously collect and send data from a specific region to a base station. Data from sensors are collected from the study area in the common scenario of sensor networks. Afterward, sensed data is sent to the base station. However, neighboring sensors often lead to redundancy of data. Transmission of redundant data to the base station consumes energy and produces traffic, because process is run in a large network. Data aggregation was proposed in order to reduce redundancy in data transformation and traffic. The most popular communication protocol in this field is cluster based data aggregation. Clustering causes energy balance, but sometimes energy consumption is not efficient due to the long distance between cluster heads and base station. In another communication protocol, which is based on a tree construction, because of the short distance between the sensors, energy consumption is low. In this data aggregation approach, since each sensor node is considered as one of the vertices of a tree, the depth of tree is usually high. In this paper, an efficient hierarchical hybrid approach for data aggregation is presented. It reduces energy consumption based on clustering and minimum spanning tree. The benefit of combining clustering and tree structure is reducing the disadvantages of previous structures. The proposed method firstly employs clustering algorithm and then a minimum spanning tree is constructed based on cluster heads. Our proposed method was compared to LEACH which is a well-known data aggregation method in terms of energy consumption and the amount of energy remaining in each sensor network lifetime. Simulation results indicate that our proposed method is more efficient than LEACH algorithm considering energy consumption.

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