Data Aggregation Scheduling Algorithms in Wireless Sensor Networks: Solutions and Challenges

Bagaa, Miloud; Challal, Yacine; Ksentini, Adlen; Derhab, Abdelouahid; Badache, Nadjib

doi:10.1109/surv.2014.031914.00029

Cited by 82 publications

(44 citation statements)

References 40 publications

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“…Until now, researchers have proposed many data aggregation algorithms for data of wireless sensor networks. With respect to the objective of aggregation, these algorithms can be classified into data centered [3], remaining energy based [4], optimized [5] and performance based [6] algorithms. The main idea of these algorithms is that, decrease the collision probability of data in wireless channels by reducing the transmitting data, and thus improve the efficiency of data collecting; check the validity of sensor nodes by comparing data collected from adjacent nodes, discard the data from the disabled nodes to reinforcement the accuracy of data; and aggregate the data sensed from different kinds of sensors to bridge the gap between the high-level user requirements with the low-level raw sensed data [7].…”

Section: Introductionmentioning

confidence: 99%

Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks

Hu¹,

Zhang²

2016

Int. J. Onl. Eng.

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Abstract-In wireless sensor networks, efficient and effective data aggregation algorithms can prolong the network lifecycle by reducing communication of redundant data and improve the security of the networks. Tradition data aggregation algorithms in wireless sensor networks mainly aim to improve the energy utilization, and ignore the security and lifecycle. In order to get a good trade-off between these requirements, we proposed a data aggregation algorithm based on constructing a data aggregation tree. After give a formalism description of the problem, we proposed a data aggregation tree constructing algorithm. By minimize the maximal energy consumption of nodes, the algorithm can prolong the lifecycle. In data aggregation scheduling algorithm, we select the number of communications carefully to get the trade-off between low weighted delay and high network lifecycle. The simulation experiments show that, the proposed data aggregation algorithm consumes less energy while aggregating data from sensor nodes, and thus can prolong the network lifecycle.

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Section: Introductionmentioning

confidence: 99%

Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks

Hu¹,

Zhang²

2016

Int. J. Onl. Eng.

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“…A large volume of data will be generated in the monitoring. Thus, the data aggregation in TSIE is a critical issue for the efficiency of data collection in such kind of IoT, and it should be addressed firstly [7][8][9][10][11][12]. 1 Network layer aggregation protocol design problem and application layer aggregation algorithm design problem are two key research issues in the design of the network layer aggregation protocol [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

An Efficient and Robust Data Integrity Verification Algorithm Based on Context Sensitive

Xie¹,

Hu²

2016

IJSIA

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“…There are various secure data aggregation methods available in the literature [5,6]. Many researchers have proposed the DA process with the use of cryptography methods.…”

Section: Introductionmentioning

confidence: 99%

Secure data aggregation and intrusion detection in wireless sensor networks

Vamsi

Kant

2015

2015 International Conference on Signal Processing and Communication (ICSC)

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Data Aggregation (DA) is a technique of data gathering in Wireless Sensor Networks (WSNs). It provide advantages such as reporting consolidated data, reducing data redundancy, improving network lifetime etc. However, deploying WSNs in hostile and remote environments presents security vulnerabilities that can lead to various security attacks such as energy based attacks, attacks on data aggregation etc. Numerous secure DA techniques have been proposed in the literature. However, lightweight models using Trust Monitoring System (TMS) and Intrusion Detection Systems (IDS) are limited. This paper presents a secure data aggregation framework for Wireless Sensor Networks (WSNs) using TMS at node level and IDS at Base Station (BS) side. Each node in the network assesses the behavior of its neighbors using trust ratings and performs the network activities such as cluster head selection, data aggregation, and reporting to the BS. Then, BS analyzes the received information using IDS and reports the information about the malicious activities back to nodes in the network. In this way, the proposed model identifies and isolates the malicious nodes from the data aggregation process. Simulation results show the effectiveness of this model.

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Data Aggregation Scheduling Algorithms in Wireless Sensor Networks: Solutions and Challenges

Cited by 82 publications

References 40 publications

Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks

Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks

An Efficient and Robust Data Integrity Verification Algorithm Based on Context Sensitive

Secure data aggregation and intrusion detection in wireless sensor networks

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