Toward Sensor-Cloud Integration as a Service: Optimizing Three-tier Communication in Cloud-integrated Sensor Networks

Phan, Dung H.; Suzuki, Junichi; Omura, Shingo; Oba, Katsuya

doi:10.4108/icst.bodynets.2013.253639

Cited by 15 publications

(9 citation statements)

References 24 publications

(19 reference statements)

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“…In sensor networks, optimization is done separately in every layer, but in sensor cloud the same strategies are not perfectly fit to do the mechanism so after broadly study in [25,26,33] optimization technique for push and pull mechanism is used. To improve the performance in sensor cloud, there is optimization problem because of this reason we are seeking help of push and pull communication mechanism to improve overall efficiency, network lifetime and to overcome sensor cloud problems which is related to our work [27,28].…”

Section: Proposed Workmentioning

confidence: 99%

Network Lifetime Optimization in Sensor Cloud

Sangulagi

Sutagundar²,

Rashid³

2019

IJANA

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Sensor cloud is a new technological development and improvement of numerous day to day life applications. It is in the form to embed for cloud computing with wireless Sensor network. As wireless no more furnishes with processing, information storage and exploring but it all done by the use of cloud and also it help to overcome problems like efficiency, lifespan and energy supply. The proposed methodology works on push pull mechanisms to save the node's energy and to improve the network lifetime. The two way communication from sensor to cloud is made possible along with making nodes in active and sleep mode to preserve the node's energy and prolong the lifespan of network. Push mechanism is responsible for sending the active nodes data to cloud server and push is operated for two ways communication i.e. user request are executed by communicating with sensor nodes from cloud server and intern sensor network provide the required data to cloud server. The result shows that there is an improvement in saving node energy, less end to end delay and hence prolonging network lifetime.

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Section: Proposed Workmentioning

confidence: 99%

Network Lifetime Optimization in Sensor Cloud

Sangulagi

Sutagundar²,

Rashid³

2019

IJANA

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“…In particular, physical sensors perform sensing and forward sensing data to the sensor-cloud. The sensor-cloud provides sensing services to multiple users/applications [ 13 ] through virtual sensors. The sensor-cloud virtualizes physical sensor nodes into virtual sensors.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

Dinh

Kim

2016

Sensors

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This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

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“…Solar power sensor network design approach has been proposed in [ 62 ] to maximize the throughput in order to better utilize the solar power and to ensure fairness for all nodes across the network. The design of a cloud-integrated sensor network architecture has been proposed in [ 63 ] by using a multi-objective optimization algorithm to maximize the throughput and minimize the bandwidth and energy consumption. The design of efficient spectrum sensing and power allocation techniques have been proposed in [ 64 ] to maximize the throughput and minimize the interference.…”

Section: Classification Of Optimization Objectivesmentioning

confidence: 99%

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Iqbal

Naeem

Anpalagan

et al. 2015

Sensors

117

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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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Toward Sensor-Cloud Integration as a Service: Optimizing Three-tier Communication in Cloud-integrated Sensor Networks

Cited by 15 publications

References 24 publications

Network Lifetime Optimization in Sensor Cloud

Network Lifetime Optimization in Sensor Cloud

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

Wireless Sensor Network Optimization: Multi-Objective Paradigm

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