• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.35-44
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• 2009

The emerging notion of data stream has brought many new challenges to the research communities as a consequence of its conceptual difference with conventional concepts of just data. One typical example is data stream processing in sensor networks. The range of data processing considerations in a sensor network is very wide, from physical resource restrictions such as bandwidth, energy, and memory to the peculiarities of query processing including continuous and specific types of queries. In this paper, as one of the physical constraints in data stream processing, we consider the problem of limited memory and propose a new scheme for data stream reduction based on the Principal Component Analysis (PCA) technique. PCA can transform a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. We adapt PCA for the data stream of a sensor network assuming the cooperation of a query engine (or application) with a network base station. Our method exploits the spatio-temporal correlation among multiple measurements from different sensors. Finally, we present a new framework for data processing and describe a number of experiments under this framework. We compare our scheme with the wavelet transform and observe the effect of time stamps on the compression ratio. We report on some of the results.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.7-18
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• 2012

It has been studied to support data having multiple properties, called Skyline Query. The skyline query is not exploring data having all properties but only meaningful data, when we retrieve informations in large data base. The skyline query can be used to provide some information about various environments and situations in sensor network. However, the legacy skyline query has a problem that increases the number of comparisons as the number of sensors are increasing in multi-dimensional data. Also important values are often omitted. Therefore, we propose a new method to reduce the complexity of comparison where the large number of sensors are placed. To reduce the complexity, we transfer a CMF(Category Based Member Function) which can identify preference of specific data when interest query from sync-node is transferred to sub-node. To show the validity of our method, we analyzed the performance by simulations. As a result, it showed that the time complexity was reduced when we retrieved information in multiple sensing data and omitted values are detected by great dominance Skyline.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.457-460
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• 2011

For the mobile meteorological services, sensed data should be gathered at a server from various clients like as Ubiquitous Sensor Network, mobile phone or public traffic vehicle by wireless network. The gathered data at server have huge volume and increase continuously. Therefore, a special query method and data structure should be considered. This paper studies on all possible query type on the data and processing steps for the mobile meteorological services. Some query spaces will be discussed. After that, this paper proposes effective data structure for the sensed data to support the query types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2111-2131
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• 2015

Tiered wireless sensor network is a network model of flexibility and robustness, which consists of the traditional resource-limited sensor nodes and the resource-abundant storage nodes. In such architecture, collected data from the sensor nodes are periodically submitted to the nearby storage nodes for archive purpose. When a query is requested, storage nodes also process the query and return qualified data as the result to the base station. The role of the storage nodes leads to an attack prone situation and leaves them more vulnerable in a hostile environment. If any of them is compromised, fake data may be injected into and/or qualified data may be discarded. And the base station would receive incorrect answers incurring malfunction to applications. In this paper, an efficient verifiable top-k query processing scheme called EVTQ is proposed, which is capable of verifying the authentication and completeness of the results. Collected data items with the embedded information of ordering and adjacent relationship through a hashed message authentication coding function, which serves as a validation code, are submitted from the sensor nodes to the storage nodes. Any injected or incomplete data in the returned result from a corresponded storage node is detected by the validation code at the base station. For saving communication cost, two optimized solutions that fuse and compress validation codes are presented. Experiments on communication cost show the proposed method is more efficiency than previous works.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.3-7
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• 2009

Data centric storages for sensor networks have been proposed to efficiently process multi-dimensional range queries as well as exact matches. Usually, a sensor network does not process only one type of the query but supports various types of queries such as range queries, exact matches and skyline queries. Therefore, a sensor network based on a data centric storage for range queries and exact matches should process skyline queries efficiently. However, existing algorithms for skyline queries have not considered the features of data centric storages. Some of the data centric storages store similar data in sensor nodes that are placed on geographically similar locations. Consequently, all data are ordered in a sensor network. In this paper, we propose a new skyline query processing algorithm that exploits the above features of data centric storages.

• The KIPS Transactions:PartC
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• v.15C no.1
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• pp.19-30
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• 2008

Sensor nodes are used as a storage space in the data centric storage method for sensor networks. Sensor nodes save the data to the node which is computed by hash table and users also access to the node to get the data by using hash table. One of the problems which the data centric storage method has is that queries from many users who are interested in the popular data could be concentrated to one node. In this case, responses for queries could be delayed and the energy of heavy loaded node could be dissipated fast. This would lead to reduction of network life time. In this paper, ALT, Data Centric Storage based on Adaptive Local Trajectory, is proposed as scalable data centric storage method for sensor network. ALT constructs trajectory around the storage node. The scope of trajectory is increased or decreased based on the query frequency. ALT distributes the query processing loads to several nodes so that delay of response is reduced and energy dissipation is also distributed.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.176-180
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• 2009

This paper investigates protocol architecture for a web-sensor gateway interconnecting internet and wireless sensor network, in which Zigbee sensors are connected over the IEEE802.15.4 communication protocol standard. The web-sensor gateway is to deliver data between TCP/IP and Zigbee/IEEE802.15.4 protocols, transparently. Since the gateway provides a means to remotely control and aggregate sensor data over the internet, it needs to be designed in the view point of users and in their convenience. In accordance, the common gateway interface technology satisfying users on the web browser to efficiently manage and query the sensors in the wireless sensor networks, ubiquitously, is also introduced. Finally, a simulation prototype for the web-sensor gateway is proposed and verified using OPNET simulation tool.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1525-1530
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• 2011

Techniques for processing continuous queries are required to developing the various types of application services (monitoring services) in ubiquitous environment where the real-time data acquisition from a lot of sensors, analysis, and processing are required. In the previous works of the continuous queries, they have represented all of the continuous queries as the interval queries or region queries, and proposed some methods for processing theses queries. The types of continuous queries, however, are very various, and could be presented by combining the attribute conditions, spatial conditions, and temporal conditions. In this paper, I have classify the types of continuous queries, and have proposed the continuous query model which could be presented by combining those conditions. The contributions of this paper include that it proposes the query model representing the continuous queries and suggests future research directions.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.