Integrated channel assignment and data aggregation routing problem in wireless sensor networks

Yen, Hong-Hsu; Lin, Chow-Sing

doi:10.1049/iet-com.2008.0239

Cited by 24 publications

(11 citation statements)

References 5 publications

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“…Current research about data fusion can be split into three areas: † Research into the fusion function: The main goals are to suppress redundancy and estimate a system parameter [17]. † Research into system architecture: The main goal is to determine how many data aggregators must be used in the WSN, and where [18]. † Research into trade-offs and resources: This research focuses on different trade-offs, such as energy against estimation accuracy, energy against aggregation latency, and bandwidth against aggregation [19].…”

Section: Application Scenariomentioning

confidence: 99%

Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

et al. 2012

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The study presents a novel computational intelligence algorithm designed to optimise energy consumption in an environmental monitoring process: specifically, water level measurements in flooded areas. This algorithm aims to obtain a tradeoff between accuracy and power consumption. The implementation constitutes a data aggregation and fusion in itself. A harsh environment can make the direct measurement of flood levels a difficult task. This study proposes a flood level estimation, inferred through the measurement of other common environmental variables. The benefit of this algorithm is tested both with simulations and real experiments conducted in Doñana, a national park in southern Spain where flood level measurements have traditionally been done manually. the terrain. Therefore it is important to design robust software and hardware that can be adapted to any incident. † Flexibility: The network must be able to add, move or remove nodes to meet the application requirements. The network must automatically detect the changes, organising the communications in consequence. One of the most important constraints for this application concerns energy consumption. The batteries that provide power supply to these devices have, in general, a short life. To overcome this problem, this study presents an aggregation and data-fusion technique, that allows us to reduce the network's power consumption. The parameter considered in this study is the water level in flooded zones. We studied it using a simulator to determine the advantages of local processing and data fusion to reduce power consumption. The data fusion is based on a local Self-Organised Map (SOM) [5] distributed in each node of the WSN. The results obtained by simulation have been compared with the real deployment of a WSN. The experimental results in real scenarios demonstrate the performance of the system and validate the results obtained by simulation. Since the start of the installation we have collected partial information about the mounted sensors and their reliability. These results are discussed in Section 6. The rest of this study is organised as follows: Section 2 describes the application scenario of the proposed method; Section 3 summarises the state-of-the-art about aggregation and data fusion in WSN; Section 4 describes the proposed aggregation methods with outcome of this method

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Section: Application Scenariomentioning

confidence: 99%

Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

et al. 2012

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“…In [ 19 ], they propose four interesting heuristic algorithms (SPT, GIT, CAGIT and ICADAR) to solve the channel constrained data aggregation routing problem. The first three heuristics are first to identify the data aggregation tree and then perform channel assignment to satisfy the channel constraint, which is a one-shot algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…The fourth algorithm is is an iterative procedure where routing and channel assignment may perform several times to identify a feasible and energy efficient data aggregation tree. However, the radio constraint is not addressed in [ 19 ] such that it might not be feasible in the radio-constrained WSN.…”

Section: Related Workmentioning

confidence: 99%

Optimization-Based Channel Constrained Data Aggregation Routing Algorithms in Multi-Radio Wireless Sensor Networks

Yen

2009

Sensors

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In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers as the link arc weight, the optimization-based heuristics are proposed to get energy-efficient data aggregation tree with better resource (channel and radio) utilization. From the computational experiments, the proposed optimization-based approach is superior to existing heuristics under all tested cases.

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“…Their ultimate purpose is to force base station or other nodes to receive inaccurate information and influence users' decision. Currently, security scheme towards data integrity of data aggregation is mainly divided into four types [10][11][12][13][14][15]:…”

Section: Introductionmentioning

confidence: 99%

A Novel Data Detection Method for Data Aggregation Security in WSN

Zou¹

2013

JNW

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Data aggregation technology can effectively save network energy resource and storage resource so it is extensively applied in wireless sensor network. However, data aggregation technology also brings security problems and it demands that corresponding security schemes should be taken for precaution. Based on the requirement of the data aggregation security on WSN, combined with the features of sensor network, current data aggregation security schemes are analyzed. The defects of SIA scheme are pointed that it cannot provide data aggregation results with effective message authentication code. So an improved scheme based data integrity for data aggregation security in WSN is presented. First, the improved scheme inherits the idea of SIA, in data filtering and cross-layer verification; Second, it expands the adaptability of SIA protocol from a single-path data filtering protocol to a complete data aggregation security scheme. Meanwhile, improved scheme supports that intermediate nodes can execute data aggregation operation to effectively reduce the transmitting overhead. It is also adaptive for more data aggregation operations, which shows better performance in saving storage resource and energy resourc

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Integrated channel assignment and data aggregation routing problem in wireless sensor networks

Cited by 24 publications

References 5 publications

Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

Optimization-Based Channel Constrained Data Aggregation Routing Algorithms in Multi-Radio Wireless Sensor Networks

A Novel Data Detection Method for Data Aggregation Security in WSN

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