scholarly journals Multiorder Fusion Data Privacy-Preserving Scheme for Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Mingshan Xie ◽  
Yong Bai ◽  
Mengxing Huang ◽  
Zhuhua Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Privacy Protection ◽  
Data Privacy ◽  
Large Scale ◽  
Privacy Preserving ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Fusion Data ◽  
Data Privacy Protection

Privacy-preserving in wireless sensor networks is one of the key problems to be solved in practical applications. It is of great significance to solve the problem of data privacy protection for large-scale applications of wireless sensor networks. The characteristics of wireless sensor networks make data privacy protection technology face serious challenges. At present, the technology of data privacy protection in wireless sensor networks has become a hot research topic, mainly for data aggregation, data query, and access control of data privacy protection. In this paper, multiorder fusion data privacy-preserving scheme (MOFDAP) is proposed. Random interference code, random decomposition of function library, and cryptographic vector are introduced for our proposed scheme. In multiple stages and multiple aspects, the difficulty of cracking and crack costs are increased. The simulation results demonstrate that, compared with the typical Slice-Mix-AggRegaTe (SMART) algorithm, the algorithm proposed in this paper has a better data privacy-preserving ability when the traffic load is not very heavy.

scholarly journals Swarm Intelligence-based Partitioned Recovery in Wireless Sensor Networks

2018 ◽  
Vol 3 ◽  
pp. 70-81
Author(s):  
Gaurav Kumar ◽  
Virender Ranga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Grey Wolf ◽  
Relay Nodes ◽  
Network Partition ◽  
Heterogeneous Wireless Sensor Networks

The failure rate of sensor nodes in Heterogeneous Wireless Sensor Networks is high due to the use of low battery-powered sensor nodes in a hostile environment. Networks of this kind become non-operational and turn into disjoint segmented networks due to large-scale failures of sensor nodes. This may require the placement of additional highpower relay nodes. In this paper, we propose a network partition recovery solution called Grey Wolf, which is an optimizer algorithm for repairing segmented heterogeneous wireless sensor networks. The proposed solution provides not only strong bi-connectivity in the damaged area, but also distributes traffic load among the multiple deployed nodes to enhance the repaired network’s lifetime. The experiment results show that the Grey Wolf algorithm offers a considerable performance advantage over other state-of-the-art approaches.

scholarly journals Query Privacy Preserving for Data Aggregation in Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
X. Liu ◽  
X. Zhang ◽  
J. Yu ◽  
C. Fu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Sensor Nodes ◽  
Experimental Simulation ◽  
Wireless Sensor ◽  
Communication Overhead

Wireless Sensor Networks (WSNs) are increasingly involved in many applications. However, communication overhead and energy efficiency of sensor nodes are the major concerns in WSNs. In addition, the broadcast communication mode of WSNs makes the network vulnerable to privacy disclosure when the sensor nodes are subject to malicious behaviours. Based on the abovementioned issues, we present a Queries Privacy Preserving mechanism for Data Aggregation (QPPDA) which may reduce energy consumption by allowing multiple queries to be aggregated into a single packet and preserve data privacy effectively by employing a privacy homomorphic encryption scheme. The performance evaluations obtained from the theoretical analysis and the experimental simulation show that our mechanism can reduce the communication overhead of the network and protect the private data from being compromised.

scholarly journals Average Load Definition in Random Wireless Sensor Networks: The Traffic Load Case

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 112
Author(s):  
Apostolos Demertzis ◽  
Konstantinos Oikonomou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Network Performance ◽  
Random Variable ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Load Case ◽  
Average Value ◽  
Average Load

Load is a key magnitude for studying network performance for large-scale wireless sensor networks that are expected to support pervasive applications like personalized health-care, smart city and smart home, etc., in assistive environments (e.g., those supported by the Internet of Things). In these environments, nodes are usually spread at random, since deliberate positioning is not a practical approach. Due to this randomness it is necessary to use average values for almost all networks’ magnitudes, load being no exception. However, a consistent definition for the average load is not obvious, since both nodal load and position are random variables. Current literature circumvents randomness by computing the average value over nodes that happen to fall within small areas. This approach is insufficient, because the area’s average is still a random variable and also it does not permit us to deal with single points. This paper proposes a definition for the area’s average load, based on the statistical expected value, whereas a point’s average load is seen as the load of an area that has been reduced (or contracted) to that point. These new definitions are applied in the case of traffic load in multi-hop networks. An interesting result shows that traffic load increases in steps. The simplest form of this result is the constant step, which results in an analytical expression for the traffic load case. A comparison with some real-world networks shows that most of them are accurately described by the constant step model.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

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