Data-gathering wireless sensor networks: organization and capacity

Duarte-Melo, Enrique J.; Liu, Mingyan

doi:10.1016/s1389-1286(03)00357-8

Cited by 169 publications

(99 citation statements)

References 15 publications

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“…First, the clustered network model with DCF is compared with the flat network model. Then it is compared with the ideal clustered network without DCF used in [2].…”

Section: Comparative Resultsmentioning

confidence: 99%

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Capacity Analysis for Flat and Clustered Wireless Sensor Networks

Song

2007

International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)

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“…First, the clustered network model with DCF is compared with the flat network model. Then it is compared with the ideal clustered network without DCF used in [2].…”

Section: Comparative Resultsmentioning

confidence: 99%

“…Duarte-Mel and Liu [2] analytically evaluated the capacity of wireless sensor networks. They introduced an overall upper throughput bound as W/n per node.…”

Section: Related Workmentioning

confidence: 99%

Capacity Analysis for Flat and Clustered Wireless Sensor Networks

Song

2007

International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)

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“…Duarte-Melo et al [5] have studied the data delivery capacity in order to identify its limiting factors and try to describe existing method to overcome such limitations. From [5], interference and contention on the wireless medium are one of the major limiting factors and they can be eliminated through multi-channel communication.…”

Section: Multi-channel Utilization: Needs and Challengesmentioning

confidence: 99%

Centralized Control for Dynamic Channel Allocation in IEEE 802.15.4 Based Wireless Sensor Networks

Nirapai

Chantaraskul

2014

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Abstract. Coexistence problem is one of the most important issues in the IEEE 802.15.4 based Wireless Sensor Networks (WSNs), since the system operates on the highly populated 2.4 GHz ISM band. As a result, system performance of WSNs can be greatly impaired by the interference from over powering signal from other systems such as WLAN and Bluetooth. This paper proposes an approach based on centralized control for dynamic channel allocation. The proposed method offers multi-channel utilization with intelligent controlling mechanism in order to provide system performance enhancement in order to cope with variation of interfered environment. Based on centralized control, decision making process is performed by the network coordinator allowing such system flexibility. Simulation model has been developed and it is embedded with this proposed mechanism in order to test the system performance. To observe the system performance under the proposed method, variety of simulation scenarios are performed with the variation of two major factors affecting system performance including the size of the network topology and the scale of interference. Proposed method is evaluated and the simulation results are compared against tradition system as well as system with multichannel utilization method with channel scheduling. The flexibility of the method proposed here allows the system to have better system performance under different test scenarios both in terms of average packet end-to-end delay and system throughput.

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“…We thus desire to have maximum possible throughput for the network. In many-to-one communication models, throughput capacity is defined as the per source data throughput, when all sources are transmitting to a single receiver or sink [10]. It means the amount of data that can be moved from any of the given sources to a single sink in the given time period.…”

Section: Topologymentioning

confidence: 99%

“…And this maximum throughput can be achieved only when every source can directly reach the sink [10]. …”

Section: Topologymentioning

confidence: 99%

Condition-Based Maintenance

Ellis¹

2014

Encyclopedia of Lubricants and Lubrication

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A new application architecture is designed for continuous, real-time, distributed wireless sensor networks. We develop a wireless sensor network for machinery condition-based maintenance (CBM) using commercially available products, including a hardware platform, networking architecture, and medium access communication protocol. We outline the design requirements for wireless sensor network (WSN) systems specifically for CBM and thus take an application driven system design. We also investigate the physical layer of WSN by modeling the battery consumption of radio hardware used on the sensor nodes. We thus incorporate both application requirements and physical layer functionality in the design of our single-hop networking architecture, and User Configured Time Division Multiple Accessing (UCvi TDMA) MAC protocol. In our design, we emphasize energy efficiency and latency requirements posed by resource constrained WSN and our application domain respectively. We use modified RTS-CTS mechanisms for combining contention with scheduling to provide an overall energy efficient, scalable and adaptable MAC protocol with no collisions and minimal protocol overhead.

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Data-gathering wireless sensor networks: organization and capacity

Cited by 169 publications

References 15 publications

Capacity Analysis for Flat and Clustered Wireless Sensor Networks

Capacity Analysis for Flat and Clustered Wireless Sensor Networks

Centralized Control for Dynamic Channel Allocation in IEEE 802.15.4 Based Wireless Sensor Networks

Condition-Based Maintenance

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