On the Optimization of Wireless Multimedia Sensor Networks: A Goal Programming Approach

García-Sánchez, Antonio-Javier; García‐Sánchez, Felipe; Rodenas-Herráiz, David; García-Haro, Joan

doi:10.3390/s120912634

Cited by 10 publications

(3 citation statements)

References 41 publications

(73 reference statements)

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“…In addition to the more commonly used algorithms as discussed in the preceding subsections, there are many other algorithms which have been used to address different multi-objective optimization problems relating to wireless sensor networks. For example in [ 8 ], a goal programming approach has been used to solve a multi-objective optimization formulation for maximizing network life time and maximizing the throughput for multimedia wireless sensor networks. In [ 27 ], Lagrangean relaxation technique has been used to solve a multi-objective optimization based channel constrained data aggregation routing algorithm in multi radio wireless sensor networks to minimize the total transmission.…”

Section: Solution Types/algorithmsmentioning

confidence: 99%

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Iqbal

Naeem

Anpalagan

et al. 2015

Sensors

121

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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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Section: Solution Types/algorithmsmentioning

confidence: 99%

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Iqbal

Naeem

Anpalagan

et al. 2015

Sensors

121

View full text Add to dashboard Cite

show abstract

“…In this regard, we assess the metrics of throughput and message delivery ratio for different data generation rates and under the premise that network lifetime is at least 5 months. This value is selected in accordance with our experience in WSN applications developed for the precision agriculture field [51,52]. In particular, we reproduce a complete agronomic cycle to monitor a melon (Cucumis melo L. variety) crop, where the network devices handle periodical measurements about different physical parameters such as the soil moisture, temperature and humidity.…”

Section: Comparison Among Proposals Compatible With Asesmentioning

confidence: 99%

On the influence of the hidden and exposed terminal problems on asynchronous IEEE 802.15.5 networks

Rodenas-Herráiz

García‐Sánchez

García-Sánchez

2015

Computer Standards & Interfaces

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a b s t r a c t Hidden and exposed terminal problems are known to negatively impact wireless communications, degrading potential computing services on top. These effects are more significant in Wireless Mesh Sensor Networks (WMSNs), and, particularly, in those based on the IEEE 802.15.5 Low-Rate Wireless Personal Area Network (LR-WPAN mesh) standard, a promising solution for enabling low-power WMSNs. The first contribution of this paper is a quantitative evaluation of these problems under the IEEE 802.15.5 Asynchronous Energy Saving (ASES) mode, which is intended for asynchronous data-collection applications. The results obtained show a sharp deterioration of the network performance. Therefore, this paper also reviews the most relevant approaches that cope with these problems and are compatible with ASES. Finally, a set of these proposals is assessed to find out those more suitable for their potential integration with ASES, which constitutes the second major contribution of the paper.

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“…Usually, the problem formulation is done as an initial phase, where the desired scenarios are formulated as multi-objective optimization problems, and are solved by using different algorithms. The multiple objectives may or may not be conflicting, but in most of the cases, the objectives conflict with each other [7][8][9][10]. Therefore, it is very less probable to find a global optimal solution, contrary to the problems of the single objective optimization [11].…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Iqbal¹,

Naeem²,

Anpalagan³

et al. 2021

Preprint

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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.

show abstract

On the Optimization of Wireless Multimedia Sensor Networks: A Goal Programming Approach

Cited by 10 publications

References 41 publications

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Wireless Sensor Network Optimization: Multi-Objective Paradigm

On the influence of the hidden and exposed terminal problems on asynchronous IEEE 802.15.5 networks

Wireless Sensor Network Optimization: Multi-Objective Paradigm

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