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Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Iqbal M, Naeem M, Anpalagan A, Ahmed A, Azam M - Sensors (Basel) (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah Campus, Wah Cantt 47040, Pakistan. miqbal1976@gmail.com.

ABSTRACT
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, planing 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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Related in: MedlinePlus

Relation between desirable objectives in wireless sensor networks (WSNs), where “N/B” = network/battery life; “QoS” = quality of service; “Cov” = coverage; “D” = delay; “Cost” = total cost of the system; “T” = throughput of the system; “EE” = energy efficiency; “PER” = packet error rate.
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f3-sensors-15-17572: Relation between desirable objectives in wireless sensor networks (WSNs), where “N/B” = network/battery life; “QoS” = quality of service; “Cov” = coverage; “D” = delay; “Cost” = total cost of the system; “T” = throughput of the system; “EE” = energy efficiency; “PER” = packet error rate.

Mentions: Most of the practical scenarios relating to wireless sensor networks are modeled as multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to choose one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Figure 3 elaborates the relationship between different desirable objectives. Different objectives are connected together with lines having different pattern depending upon the relationship between objectives. Red solid line connects the two objectives which have conflicting relationship, for example, maximization of coverage conflicts with the packet error rate, delay, network/battery life time and the overall cost of the system. Whereas, the line consisting of dashes and dots connects the two objectives which have no direct relationship with each other rather they are design dependent for example, maximization of coverage has not direct relationship with the throughput, energy efficiency and the QoS. The supporting relationship between the two objectives has been shown with line consisting of dashes for example, maximization of network/battery life supports the maximization of energy efficiency and minimization of the overall cost of the system. In the following, we discuss each objective separately and its relation with other objectives.


Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Iqbal M, Naeem M, Anpalagan A, Ahmed A, Azam M - Sensors (Basel) (2015)

Relation between desirable objectives in wireless sensor networks (WSNs), where “N/B” = network/battery life; “QoS” = quality of service; “Cov” = coverage; “D” = delay; “Cost” = total cost of the system; “T” = throughput of the system; “EE” = energy efficiency; “PER” = packet error rate.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541950&req=5

f3-sensors-15-17572: Relation between desirable objectives in wireless sensor networks (WSNs), where “N/B” = network/battery life; “QoS” = quality of service; “Cov” = coverage; “D” = delay; “Cost” = total cost of the system; “T” = throughput of the system; “EE” = energy efficiency; “PER” = packet error rate.
Mentions: Most of the practical scenarios relating to wireless sensor networks are modeled as multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to choose one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Figure 3 elaborates the relationship between different desirable objectives. Different objectives are connected together with lines having different pattern depending upon the relationship between objectives. Red solid line connects the two objectives which have conflicting relationship, for example, maximization of coverage conflicts with the packet error rate, delay, network/battery life time and the overall cost of the system. Whereas, the line consisting of dashes and dots connects the two objectives which have no direct relationship with each other rather they are design dependent for example, maximization of coverage has not direct relationship with the throughput, energy efficiency and the QoS. The supporting relationship between the two objectives has been shown with line consisting of dashes for example, maximization of network/battery life supports the maximization of energy efficiency and minimization of the overall cost of the system. In the following, we discuss each objective separately and its relation with other objectives.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah Campus, Wah Cantt 47040, Pakistan. miqbal1976@gmail.com.

ABSTRACT
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, planing 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.

No MeSH data available.


Related in: MedlinePlus