Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm

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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A Secure Routing Scheme Based on Multi-Objective Optimization in Wireless Sensor Networks

2008 International Conference on Computational Intelligence and Security ◽

10.1109/cis.2008.34 ◽

2008 ◽

Cited By ~ 3

Author(s):

Xuanxia Yao ◽

Xuefeng Zheng

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Secure Routing ◽

Wireless Sensor ◽

Multi Objective Optimization ◽

Multi Objective ◽

Routing Scheme

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Wireless Sensor Network Optimization: Multi-Objective Paradigm

10.32920/14640045 ◽

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.

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