Efficient fault-tolerant collision-free data aggregation scheduling for wireless sensor networks

Jhumka, Arshad; Bradbury, Matthew; Saginbekov, Sain

doi:10.1016/j.jpdc.2013.09.011

Cited by 14 publications

(6 citation statements)

References 28 publications

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“…Time Division Multiple Access (TDMA) is considered in [1] to perform Data Aggregation Scheduling (DAS) and hence providing fault-tolerant network. Data aggregation scheduling is a basic communication pattern in WSN such that, sensor nodes collect and forward the information to a sink node.…”

Section: Background Workmentioning

confidence: 99%

Traffic scheduling for Green city through energy efficient Wireless sensor Networks

Vijayan¹

2019

IJATCSE

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Due to the exponential growth in the vehicle population it become very much challenging to control the pollution in the green city. As the vehicle waiting time in a traffic signal is diagonally proportional to the increase in pollution the traffic scheduling become essential. The IOT based wireless sensor based monitoring and traffic scheduling is an effective method but it always suffer from the energy efficiency of sensor network which ultimately aversively affect the environment of Green city. A fuzzy logic based traffic scheduling improves the system as the expert knowledge of a traffic police and environment specialist can be incorporated in the control algorithm. Genetic algorithm based or particle swarm optimization based approach will be able to improve the energy efficiency of the network as optimize the performance by considering multiple parameters which affect the environment.

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Section: Background Workmentioning

confidence: 99%

Traffic scheduling for Green city through energy efficient Wireless sensor Networks

Vijayan¹

2019

IJATCSE

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“…Classical models for distributed systems often use abstractions at various levels to compensate for timing non-determinism. 30 Examples are lock-step synchronous models, 31 fixed or no drift in individual clocks 32 and/or delays with fixed bounds 33 (which essentially models a subset of synchronous systems). We consider the Q-modelling technique 34 for the analysis of ad hoc WSNs, as it naturally facilitates modelling of timing aspects of asynchronous communication and queuing delays across the communication paths through the network while considering the precision of data timestamps.…”

Section: Related Workmentioning

confidence: 99%

Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

Kaugerand

Ehala

Motus

et al. 2018

International Journal of Distributed Sensor Networks

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This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

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“…On the other hand, there is bulk of research that focuses on fault tolerance that leaves privacy and security issues either out of scope or just mentioned, not keeping it as a priority. Examples of such work may be found in [22,23,24]. In [8] the authors present an asymptotic lower bound on the error of the aggregation that preserves privacy, showing that in order to reduce the errors, one has to resign from perfect privacy and focus rather on computational variant of the privacy preservation.…”

Section: Previous and Related Workmentioning

confidence: 99%

Practical Fault-Tolerant Data Aggregation

Grining

Klonowski

Syga

2016

Applied Cryptography and Network Security

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During Financial Cryptography 2012 Chan et al. presented a novel privacy-protection fault-tolerant data aggregation protocol. Comparing to previous work, their scheme guaranteed provable privacy of individuals and could work even if some number of users refused to participate.In our paper we demonstrate that despite its merits, their method provides unacceptably low accuracy of aggregated data for a wide range of assumed parameters and cannot be used in majority of real-life systems. To show this we use both analytic and experimental methods. Additionally, we present a precise data aggregation protocol that provides provable level of security even when facing massive failures of nodes. Moreover, the protocol requires significantly less computation (limited exploiting of heavy cryptography) than most of currently known fault tolerant aggregation protocols and offers better security guarantees that make it suitable for systems of limited resources (including sensor networks). To obtain our result we relax however the model and allow some limited communication between the nodes.

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Efficient fault-tolerant collision-free data aggregation scheduling for wireless sensor networks

Cited by 14 publications

References 28 publications

Traffic scheduling for Green city through energy efficient Wireless sensor Networks

Traffic scheduling for Green city through energy efficient Wireless sensor Networks

Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

Practical Fault-Tolerant Data Aggregation

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