Sensor Scheduling for Aggregate Monitoring inWireless Sensor Networks

Data aggregation scheduling in ubiquitous sensor networks is a major research interest for many researchers. Very little research is carried out to schedule the nodes in ubiquitous sensor networks for maximizing the throughput and utilize the hardware resources effectively. The traditional graph model does not model the interferences occurring from the concurrent transmissions in the Ubiquitous Sensor Networks. Hence in this paper we propose a new network model for the USN called a power control collision interference free model and a novel distributed data aggregation scheduling protocol which is adaptive to the rate and power. We tested the protocol in a USN consisting of 50, 100, 150, 200, and 250 number of nodes with different topologies and varying degree 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, . . ., 40. We compared our results with the other protocols and proved that our proposed power control collision interference free model yields better results.

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“…Hence our proposed PCCFI method outperforms the SDA [16], PAS [17], DAS [18], SAS [19], WIRES-BSPT [15], and First Fit methods by 30-50%.…”

Section: Resultsmentioning

confidence: 85%

A Dynamic and Distributed Scheduling for Data Aggregation in Ubiquitous Sensor Networks Using Power Control

Madhavi

Kim

2013

International Journal of Distributed Sensor Networks

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“…In WSNs', Networks are divided into three categories, first is tree based [4], second is cluster based [5], and third is hybrid topology. In tree based structure, the root of tree is called sink node.…”

Section: Network Topology and Communication Patternmentioning

confidence: 99%

A Survey on Scheduling Algorithms for Wireless Sensor Networks

Kumar¹,

Chauhan²

2011

IJCA

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Wireless sensor networks(WSN) have wide range of application such as traffic analysis, environmental monitoring, industrial process monitoring, and tactical systems. Large-scale wireless sensor networks are expected to play increasingly important role in future civilian and military application. Designing of MAC layer protocol for wireless sensor network is a challenging task due to limited battery power and limited bandwidth. Time Division Multiple Access Protocol solves both problems at the level of MAC layer. Various scheduling method for TDMA protocol with different objective have been proposed for wireless sensor networks. In this paper, we first outline the sensor network properties that are crucial for the design of TDMA protocols and then, we describe several TDMA protocols which are proposed for sensor networks. Finally, we point out open research issue with regard to TDMA protocols.

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“…Some focus on computing simple functions over the readings of sensor networks, e.g., [15], [19], [24]. Madden et al develop Tiny AGggregation (TAG), a generic aggregation service for sensor networks.…”

Section: Related Workmentioning

confidence: 99%

“…Przydatek et al [19] focus on the security aspects of data aggregation. Trading aggregation accuracy with communication cost is studied in [24]. Giridhar and Kumar [9] characterize the rate at which certain classes of functions can be computed and communicated in sensor networks.…”

Section: Related Workmentioning

confidence: 99%

Contour maps: Monitoring and diagnosis in sensor networks

Meng

Nandagopal²,

Li³

et al. 2006

Computer Networks

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Large-scale sensor networks impose energy and communication constraints, thus it is difficult to collect data from each individual sensor node and process it at the sink. In this paper, we propose an efficient data-collection scheme that can be used for event monitoring or network-wide diagnosis. Our scheme relies on the well-known representation of data -contour maps, which trade off accuracy with the amount of samples. The scheme consists of three novel algorithms to build contour maps: distributed spatial and temporal data suppression, contour reconstruction at the sink via interpolation and smoothing, and an efficient mechanism to convey routing information over multiple hops. By reducing the number of transmissions required to convey relevant information to the sink, the proposed contour mapping scheme saves energy and improves network lifetime. In a sharp contrast to related work in this area, the scheme does not require all nodes to explicitly share information.The contour mapping scheme can be applied for tasks such as: (1) presenting a global picture of the network in both temporal and spatial domains. (2) being used as a diagnosis tool, e.g., to detect faulty sensors and to scan for residual energy. (3) working in concert with in-network aggregation schemes to further reduce the communication overhead of aggregation schemes. The proposed scheme imposes little processing and storage overhead, allowing for the sensor networking paradigm of "dumb sensor, smart sink" which enables economical deployment of large-scale sensor networks.Simulation results show that our scheme is resilient to both high packet loss rate and measurement noise. The design is also energy efficient, resulting in up to an-order-of-magnitude power savings when compared with the base line scheme where every sensor sends its report to the sink.

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Sensor Scheduling for Aggregate Monitoring inWireless Sensor Networks

Cited by 18 publications

References 19 publications

A Dynamic and Distributed Scheduling for Data Aggregation in Ubiquitous Sensor Networks Using Power Control

A Dynamic and Distributed Scheduling for Data Aggregation in Ubiquitous Sensor Networks Using Power Control

A Survey on Scheduling Algorithms for Wireless Sensor Networks

Contour maps: Monitoring and diagnosis in sensor networks

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