DE Based Node Placement Optimization for Wireless Sensor Networks

Hojjatoleslami, Samaneh; Aghazarian, Vahe; Aliabadi, Ali

doi:10.1109/isa.2011.5873254

Cited by 9 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Extended cases for irregular areas are shown by [28], in which the interference rate is included and how much nodes are turned on at same time. In [29], the problem is divided in uniformity (node spreading) and connectivity (node clustering) regarding the area; the energy is analyzed by dividing the problem in operational consumed energy and data-exchange consumed energy.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach

Céspedes-Mota

Castañón

Martínez-Herrera

et al. 2016

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Location information for wireless sensor nodes is needed in most of the routing protocols for distributed sensor networks to determine the distance between two particular nodes in order to estimate the energy consumption. Differential evolution obtains a suboptimal solution based on three features included in the objective function: area, energy, and redundancy. The use of obstacles is considered to check how these barriers affect the behavior of the whole solution. The obstacles are considered like new restrictions aside of the typical restrictions of area boundaries and the overlap minimization. At each generation, the best element is tested to check whether the node distribution is able to create a minimum spanning tree and then to arrange the nodes using the smallest distance from the initial position to the suboptimal end position based on the Hungarian algorithm. This work presents results for different scenarios delimited by walls and testing whether it is possible to obtain a suboptimal solution with inner obstacles. Also, a case with an area delimited by a star shape is presented showing that the algorithm is able to fill the whole area, even if such area is delimited for the peaks of the star.

show abstract

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…The main difference with [28] is that the overlap considered as the interference is also managed in terms of restrictions to minimize the overlap very quickly. It also applies for [29]. Besides, an extra parameter called random-is used in the mutation operator to avoid the stagnation of DEA as suggested in [25].…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach

Céspedes-Mota

Castañón

Martínez-Herrera

et al. 2016

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…In this paper, author presents a survey of routing protocols for WSN and compares their strengths and limitations. In this paper [5] author presents a multi-objective optimization methodology for node placement in wireless sensor network design. Emerging computational intelligence leads to optimization of NP-hard problem in a simple way, differential evolution approach is used as a tool for optimization of most important parameters in node placement process of wireless sensor network.…”

Section: Related Workmentioning

confidence: 99%

Multiple Node Placement Strategy for Efficient Routing in Wireless Sensor Networks

Bendigeri¹,

Mallapur²

2015

WSN

View full text Add to dashboard Cite

The advances in recent technology have lead to the development of wireless sensor nodes forming a wireless network, which over the years is used from military application to industry, household, medical etc. The deployment pattern of sensor nodes in Wireless Sensor Network (WSN) is always random for most of the applications. Such technique will lead to ineffective utilization of the network; for example fewer nodes are located at far distance and dense nodes are located at some reason and part of the region may be without the surveillance of any node, where the networks do consume additional energy or even may not transfer the data. The proposed work is intended to develop the optimized network by effective placement of nodes in circular and grid pattern, which we call as uniformity of nodes to be compared with random placement of nodes. Each of the nodes is in optimized positions at uniform distance with neighbors, followed by running a energy efficient routing algorithm that saves an additional energy further to provide connectivity management by connecting all the nodes. Simulation results are compared with the random placement of nodes, the residual energy of a network, lifetime of a network, energy consumption of a network shows a definite improvement for uniform network as that of with the random network.

show abstract

“…For instance, it was shown in [4] that only 44% of ADS-B messages in central Europe are received by four or more sensors, while the remaining areas are either covered by fewer sensors or not covered at all. Optimal sensor placement has typically been investigated as an availability problem: How to place the receivers such that they provide the best coverage for a geographical area [8,12,26]? Placing them too close to each other leads to high and possibly unnecessary redundancy, whereas placing them too far apart may result in lost observation areas because the wireless channel is faulty and messages may get lost.…”

mentioning

confidence: 99%

Towards Security-Optimized Placement of ADS-B Sensors

Darabseh,

Pöpper

2022

Preprint

View full text Add to dashboard Cite

Automatic Dependent Surveillance-Broadcast (ADS-B) sensors deployed on the ground are central to observing aerial movements of aircraft. Their unsystematic placement, however, results in overdensification of sensor coverage in some areas and insufficient sensor coverage in other areas. ADS-B sensor coverage has so far been recognized and analyzed as an availability problem; it was tackled by sensor placement optimization techniques that aim for covering large enough areas. In this paper, we demonstrate that the unsystematic placement of ADS-B sensors leads to a security problem, since the realization and possible deployment of protective mechanisms is closely linked to aspects of redundancy in ADS-B sensor coverage. In particular, we model ADS-B sensor coverage as a multi-dimensional security problem. We then use multi-objective optimization techniques to tackle this problem and derive securityoptimized near-optimal placement solutions. Our results show how the location of sensors play a significant role in reducing the success rate of attackers by providing a sufficient number of sensors within a specific geographical area to verify location claims and reducing the exposure to jamming attacks. CCS CONCEPTS• Security and privacy → Mobile and wireless security.

show abstract

DE Based Node Placement Optimization for Wireless Sensor Networks

Cited by 9 publications

References 14 publications

Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach

Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach

Multiple Node Placement Strategy for Efficient Routing in Wireless Sensor Networks

Towards Security-Optimized Placement of ADS-B Sensors

Contact Info

Product

Resources

About