A MULTI-OBJECTIVE OPTIMIZATION PROBLEMS OF CLUSTERING PROTOCOLS FOR WIRELESS SENSOR NETWORKS USING META-HEURISTIC TECHNIQUES

2018 ◽  
Vol 1 (1) ◽  
pp. 21-27
Author(s):  
Svitlana Antoshchuk ◽  
Igor Shamin ◽  
Bhushan Shashi Sharma ◽  
Galina Shcherbakova
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Problems ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Heuristic Techniques ◽  
Clustering Protocols

scholarly journals Wireless Sensor Network Optimization: Multi-Objective Paradigm

2021 ◽  
Author(s):  
Muhammad Iqbal ◽  
Muhammad Naeem ◽  
Alagan Anpalagan ◽  
Ashfaq Ahmed ◽  
Muhammad Azam
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Input Variables

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planning and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

scholarly journals Wireless Sensor Network Optimization: Multi-Objective Paradigm

2021 ◽  
Author(s):  
Muhammad Iqbal ◽  
Muhammad Naeem ◽  
Alagan Anpalagan ◽  
Ashfaq Ahmed ◽  
Muhammad Azam
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Input Variables

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planning and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

MONet

2017 ◽  
Vol 13 (4) ◽  
pp. 345-369
Author(s):  
Kamel Barka ◽  
Azeddine Bilami ◽  
Samir Gourdache
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Efficiency ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Trade Offs

Purpose The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet). Design/methodology/approach In MONet, the middleware level of each network node autonomously adjusts its routing parameters according to dynamic network conditions and seeks optimal trade-offs among performance objectives for a balance of its global performance. MONet controls the cooperation between agents (network nodes) while varying transmission paths to reduce and distribute power consumption equitably on all the sensor nodes of network. MONet-runtime uses a modified TinyDDS middleware platform. Findings Simulation results confirm that MONet allows power efficiency to WSN nodes while adapting their sleep periods and self-heal false-positive sensor data. Originality/value The framework implementation is lightweight and efficient enough to run on resource-limited nodes such as sensor nodes.

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