Minimum Data-Latency-Bound $k$-Sink Placement Problem in Wireless Sensor Networks

2011 ◽  
Vol 19 (5) ◽  
pp. 1344-1353 ◽  
Author(s):  
Donghyun Kim ◽  
Wei Wang ◽  
Nassim Sohaee ◽  
Changcun Ma ◽  
Weili Wu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Placement Problem ◽  
Minimum Data ◽  
Data Latency

Exploring Coverage within Wireless Sensor Networks through Evolutionary Computations

2010 ◽  
pp. 191-200
Author(s):  
Sami Habib
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Search Space ◽  
Service Area ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Evolutionary Computations ◽  
Placement Problem ◽  
Sensor Devices ◽  
Computationally Intensive

The evolutionary search approach has demonstrated its effectiveness in many real world applications, such as the coverage problem in wireless sensor networks. It is to place sensor devices in a service area so that the entire service area is covered. We have modeled the coverage problem as two sub-problems: floorplan and placement. The floorplan problem is to partition the service area into well-defined geometric cells, where the placement problem is to assign the sensor devices into a set of cells. Even though the search space has been transformed from continuous into discrete, the complexity of the coverage problem is computationally intensive. The objective function is to maximize the coverage of the service area while not exceeding a given budget. The merged optimization problem has been coded into the genetic algorithm (GA) and the experimental results reveal the versatility of GA to adapt and find a good solution in a short time.

Bi-criteria Gateway Placement Problem in Wireless Sensor Networks

2010 ◽  
Vol 56 (3) ◽  
pp. 215-222 ◽  
Author(s):  
Maria Czajko ◽  
Jacek Wojciechowski
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Effective ◽  
Wireless Sensor ◽  
Placement Problem ◽  
Connection Management ◽  
Gateway Placement ◽  
Network Operation ◽  
Random Manner ◽  
Gateway Deployment

Bi-criteria Gateway Placement Problem in Wireless Sensor NetworksOver the last few years, wireless sensor networks (WSNs) have started to play more and more important role in civil and military applications. A typical sensor network consists of resource-constrained sensing nodes, which monitor environment and send the data to more powerful gateway nodes. The goal of gateway nodes is to aggregate, process and send the data to other gateways or directly to sink nodes. The proper placement of nodes is needed to provide good network operation. Sensing nodes are often placed in a random manner unlike gateways. Gateways, due to their role and cost, are installed rather in a controlled way. In this paper, a bi-criteria gateway placement problem is introduced. The problem is shown to be NP-hard. We formulate it as a linear programming problem, then we develop the Multi-criteria Simulated Allocation (MSAL) heuristic algorithm, for the purpose of cost-effective gateway deployment and power-effective wireless connection management. Finally, we evaluate the efficiency of the algorithm by comparison with the exact method.

Solving the k-Coverage and m-Connected Problem in Wireless Sensor Networks through the Imperialist Competitive Algorithm

2020 ◽  
Vol 20 (01) ◽  
pp. 2050002
Author(s):  
HEMMAT SHEIKHI ◽  
WAFA BARKHODA
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Mathematical Formulation ◽  
Imperialist Competitive Algorithm ◽  
Wireless Sensor ◽  
Placement Problem ◽  
Competitive Algorithm ◽  
Np Hard Problem ◽  
Node Count

This study presents a new method based on the imperialist competitive algorithm (ICA-based) to solve the k-coverage and m-connected problem in wireless sensor networks (WSNs) through the least sensor node count, where the candidate positions for placing nodes are pre-specified. This dual featured problem in WSNs is a nondeterministic polynomial (NP)-hard problem therefore, ICA the social-inspired evolutionary algorithm is assessed and ICA-based scheme is designed to solve the problem. This newly proposed ICA-based scheme provides an efficient algorithm for representing the imperialistic competition among some of the best solutions to the problem in order to decrease the network cost. The mathematical formulation is presented for the node placement problem. The main issue of concern here is the deployed sensor node count. The simulation results confirm that ICA-based method can reduce the required sensor node count unlike other genetic-based and biogeography-based evolutionary algorithms. The experimental results are presented for WSN_Random and WSN_Grid scenarios.

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