Robust Deployment of Wireless Sensor Networks Using Gene Regulatory Networks

Nazi, Azade; Raj, Mayank; Francesco, Mario Di; Ghosh, Preetam; Das, Sajal K.

doi:10.1007/978-3-642-35668-1_14

Cited by 16 publications

(10 citation statements)

References 20 publications

(35 reference statements)

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“…Gene Regulatory Networks (GRNs) [16] Face maximize efficiency problem in which sensor nodes should be vigorous and flexible to any failures Improve the algorithm to be more efficient A novel solution to obtain robust WSNs [59] Improving the robustness of communications in WSNs by exploiting principles of biological robustness at Nano scale Evaluate the application of GRNs to other network scenarios, such as the Internet.…”

Section: Robustnessmentioning

confidence: 99%

Wireless Sensor Networks (WSNs): New trends in Secure Routing Techniques

Abdel-hamid¹,

Labib²,

Ibrahim³

et al. 2018

IJCA

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Wireless Sensor Networks (WSNs), considered as one of the successfully distributed applications that are currently used to acquire knowledge and collect information from the wirelessly devices seamlessly. The distinctive architecture of WSNs contributed to deploy it in an extensive range of modern industrial applications such as surveillance, monitoring, predicted, and automated control systems which can help in bridging the divide between user requirements and technologies. Moreover, WSNs face several challenges such as Topology control, Robustness, Placement, Power consuming, Scalability, Reliability, Resource Utilization, QoS, Data availability and Security. The main objective of this paper can be classified into two parts; the first one is to illustrate WSNs architecture, applications, challenges, and recent research directions. The second one is highlighting on routing and security design issues, security threats, countermeasures against network layer attacks to achieve secure routing, as the efficiency of the communication process is mainly based on determining the best path between nodes. We also highlight the advantages and performance issues of each secure routing technique. At the end of this paper the possible future research areas are concluded.

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Section: Robustnessmentioning

confidence: 99%

Wireless Sensor Networks (WSNs): New trends in Secure Routing Techniques

Abdel-hamid¹,

Labib²,

Ibrahim³

et al. 2018

IJCA

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“…From Fig. 2, we can observe that the proposed system can drive the activating probability of each node to the target state by adjusting system parameters k m , η, k p , μ according to (23) and (24).…”

Section: System Parameter Controlmentioning

confidence: 99%

“…If we define the target state as p * = 0.5, we can select the system parameters as k pi = μ i = η i = 0.1, k mi = 2 × e −0.5 (i = 1, 2) according to (23). From (22), we can get the positive matrix P: Note that A is lower triangular matrix, thus its eigenvalues are the elements on the diagonal line.…”

Section: Numerical Analysismentioning

confidence: 99%

“…The evolution process of genes in GRNs inspires solutions to many problems in WSNs, such as maximising network coverage, topology control, routing, duty-cycle adaptation, and clustering [23][24][25][26][27][28][29]. Nazi et al [23] determined the locations of wireless sensor nodes using GRN topology to achieve robustness and resilience to node failures. Das et al [24] proposed a GRN model to solve the issue of optimal coverage in WSNs.…”

Section: Introductionmentioning

confidence: 99%

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Energy‐balancing node scheduling inspired by gene regulatory networks for wireless sensor networks

Byun

Yang

2017

IET Communications

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“…They are passed from parent to offspring through reproduction. [1] Azad nazi and et.l. designed the biological gene structure to design wireless sensor networks.…”

Section: The Human Organ Components For Wsn Applicationmentioning

confidence: 99%

Energy Optimization in Wireless Sensor Network through Natural Science Computing: A Survey

Wagh¹,

Prasad

2013

JGE

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Nature-inspired computational algorithms are attracting engineering research for artificial intelligence solutions. The Natural science modelling for designing intelligent artefacts gives good results which reliably execute in the system. Some time it is expensive in terms of space and time to create reliable artefacts with conventional process that design the elements like intelligence, controlling operations, process optimization, threat and security, design of the future ideas, and so on. The paper addresses the natural science processes and solution directions. It integrates contrasting techniques of Genetic systems, Neural System, Immune systems and Cellular automata inspired from human organs to give solutions for energy conservation problems in Wireless sensor network domain. The non-human aspects of natural science like, swarm optimization, social insects like ant honey bees, wasps, termites and many more are also discussed to solve many real-world problems. The paper gives insights into the creation of innovative improvements over algorithm performance, potential applications on various practical tasks, and combination of different techniques for energy optimization in wireless sensor networks.

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Robust Deployment of Wireless Sensor Networks Using Gene Regulatory Networks

Cited by 16 publications

References 20 publications

Wireless Sensor Networks (WSNs): New trends in Secure Routing Techniques

Wireless Sensor Networks (WSNs): New trends in Secure Routing Techniques

Energy‐balancing node scheduling inspired by gene regulatory networks for wireless sensor networks

Energy Optimization in Wireless Sensor Network through Natural Science Computing: A Survey

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