A Query Result Merging Scheme for Providing Energy Efficiency in Underwater Sensor Networks

109

Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field.

Section: Underwater Communicationsmentioning

confidence: 99%

Underwater Sensor Nodes and Networks

Lloret

2013

109

“…Nowadays, as new applications of wireless sensor network need data processing with temporal constraints in their tasks, one of the new challenges for wireless sensor networks is the handling of data access [ 11 , 12 ]. There are three research aspects in wireless sensor network data access: data storage [ 13 , 14 , 15 , 16 ], data aggregation [ 17 , 18 , 19 , 20 ] and data query [ 21 , 22 , 23 , 24 ]. These prior studies have looked at maximizing the energy efficiency in order to increase the lifetime of wireless sensor network, or focus on the time performance on data access of the wireless sensor network from a single aspect.…”

Section: Related Workmentioning

confidence: 99%

Data Access Based on a Guide Map of the Underwater Wireless Sensor Network

Wei

Song

Yin

et al. 2017

Underwater wireless sensor networks (UWSNs) represent an area of increasing research interest, as data storage, discovery, and query of UWSNs are always challenging issues. In this paper, a data access based on a guide map (DAGM) method is proposed for UWSNs. In DAGM, the metadata describes the abstracts of data content and the storage location. The center ring is composed of nodes according to the shortest average data query path in the network in order to store the metadata, and the data guide map organizes, diffuses and synchronizes the metadata in the center ring, providing the most time-saving and energy-efficient data query service for the user. For this method, firstly the data is stored in the UWSN. The storage node is determined, the data is transmitted from the sensor node (data generation source) to the storage node, and the metadata is generated for it. Then, the metadata is sent to the center ring node that is the nearest to the storage node and the data guide map organizes the metadata, diffusing and synchronizing it to the other center ring nodes. Finally, when there is query data in any user node, the data guide map will select a center ring node nearest to the user to process the query sentence, and based on the shortest transmission delay and lowest energy consumption, data transmission routing is generated according to the storage location abstract in the metadata. Hence, specific application data transmission from the storage node to the user is completed. The simulation results demonstrate that DAGM has advantages with respect to data access time and network energy consumption.

“…In this category, when each sensor node receives queries from monitoring and control stations, it transmits only the resulting sensor data corresponding to each query as its responses. Thereby, this method reduces the number of sensor data transmissions, avoiding constant transmission [34,35,36,37,38]. Additionally, query aggregation and results merging methods have been presented for avoiding redundancy in the response results [37,38].…”

Section: Related Workmentioning

confidence: 99%

“…Thereby, this method reduces the number of sensor data transmissions, avoiding constant transmission [ 34 , 35 , 36 , 37 , 38 ]. Additionally, query aggregation and results merging methods have been presented for avoiding redundancy in the response results [ 37 , 38 ].…”

Section: Related Workmentioning

confidence: 99%

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

Kim

Shin

2017

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.