• Journal of KIISE:Databases
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• v.35 no.3
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• pp.218-230
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• 2008

The temporal aggregate in temporal databases is an extension of the conventional aggregate to include the time on the range condition of aggregation. It is a useful operation for Historical Data Warehouses, Call Data Records, and so on. In this paper, we propose a structure for the temporal aggregation with multiple selection predicates, called the ITA-tree, and an aggregate processing method based on the structure. In the ITA-tree, we transform the time interval of a record into a single value, called the T-value. Then, we index records according to their T-values like a $B^+$-tree style. For possible hot-spot situations, we also propose an improvement of the ITA-tree, called the eITA-tree. Through analyses and experiments, we evaluate the performance of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3219-3236
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• 2012

A tree routing structure is often adopted for many-to-one data gathering and aggregation in sensor networks. For real-time scenarios, considering lossy wireless links, it is an important issue how to construct a maximum-lifetime data gathering tree with delay constraint. In this work, we study the problem of lifetime-preserving and delay-constrained tree construction in unreliable sensor networks. We prove that the problem is NP-complete. A greedy approximation algorithm is proposed. We use expected transmissions count (ETX) as the link quality indicator, as well as a measure of delay. Our algorithm starts from an arbitrary least ETX tree, and iteratively adjusts the hierarchy of the tree to reduce the load on bottleneck nodes by pruning and grafting its sub-tree. The complexity of the proposed algorithm is $O(N^4)$. Finally, extensive simulations are carried out to verify our approach. Simulation results show that our algorithm provides longer lifetime in various situations compared to existing data gathering schemes.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.94-97
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• 2022

The emerging energy harvesting technology, which has been successfully integrated into Wireless Sensor Networks, enables sensor batteries to be charged using renewable energy sources. In the meantime, the problem of Minimum Latency Aggregation Scheduling (MLAS) in battery-powered WSNs has been well studied. However, because sensors have limited energy harvesting capabilities, captured energy is limited and varies greatly between nodes. As a result, all previous MLAS algorithms are incompatible with Battery-Free Wireless Sensor Networks (BF-WSNs). We investigate the MLAS problem in BF-WSNs in this paper. To make the best use of the harvested energy, we build an aggregation tree that leverages the energy harvesting rates of the sensor nodes with an intuitive explanation. The aggregation tree, which determines sender-receiver pairs for data transmission, is one of the two important phases to obtain a low data aggregation latency in the BF-WSNs.

• Journal of KIISE
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• v.44 no.7
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• pp.703-709
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• 2017

Outsourcing databases is to offload storage and computationally intensive tasks to the third party server. Therefore, data owners can manage big data, and handle queries from clients, without building a costly infrastructure. However, because of the insecurity of network systems, the third-party server may be untrusted, thus the query results from the server may be tampered with. This problem has motivated significant research efforts on authenticating various queries such as range query, kNN query, function query, etc. Although aggregation queries play a key role in analyzing big data, authenticating aggregation queries has not been extensively studied, and the previous works are not efficient for data with high dimension or a large number of distinct values. In this paper, we propose the AMR-tree that is a data structure, applied to authenticate aggregation queries. We also propose an efficient proof construction method and a verification method with the AMR-tree. Furthermore, we validate the performance of the proposed algorithm by conducting various experiments through changing parameters such as the number of distinct values, the number of records, and the dimension of data.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1418-1427
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• 1999

시간지원 데이타베이스 시스템은 자료의 과거 및 현재, 그리고 미래의 상태까지 관리함으로써, 사용자에게 시간에 따라 변화하는 자료에 대한 저장 및 질의 수단을 제공한다. 시간지원 데이타베이스는 경향 분석, 버전 관리, 의료 기록 관리 및 비디오 데이타 관리 등과 같이 자료의 시간적 특성이 중요시 되는 모든 분야에 폭 넓게 응용될 수 있다. 시간지원 데이타베이스에서의 집계는 시간 애트리뷰트를 고려하지 않은 기존의 집계와는 큰 차이가 있으며, 기존의 집계 처리 기법을 이용하여 효과적으로 처리될 수 없다. 본 논문에서는 시간지원 집계를 효율적으로 처리하기 위한 새로운 자료 구조인 PA-트리를 제안하고, 이를 이용한 시간지원 집계 처리 기법을 제안한다. 또한 본 논문에서는 제안된 PA-트리를 이용한 기법과 기존의 집계 트리를 이용한 기법의 성능을 최악 경우 분석과 실험을 통해 비교한다.Abstract Temporal databases manage time-evolving data. They provide built-in supports for efficient recording and querying of temporal data. Many application area such as trend analysis, version management, and medical record management have temporal aspects, and temporal databases can handle these temporal aspects efficiently. The aggregate in temporal databases, that is, temporal aggregate is an extension of conventional aggregate on the domain and range of aggregation to include time concept. The basic techniques behind computing aggregates in conventional databases are not efficient when applied to temporal databases. In this paper, we propose a new tree structure for temporal aggregation, called PA-tree, and aggregate processing method based on the PA-tree. We compare the PA-tree with the existing aggregation tree which has been proposed for temporal aggregate.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1071-1075
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• 2010

Because a sensor node in wireless sensor networks(WSNs) has limited resources, such as battery capacity and memory, data aggregation techniques have been studied to manage the limited resources efficiently. Because sensor network uses wireless communication, a data can be disclosed by attacker. Thus, the study on data protection schemes for data aggregation is essential in WSNs. But the existing data aggregation methods require both a large number of computation and communication, in case of network construction and data aggregation processing. To solve the problem, we propose a data protection scheme based on Hilbert-curve for data aggregation. Our scheme can minimizes communications among neighboring sensor nodes by using tree-based routing. Moreover, it can protect the data from attacker by doing encryption through a Hilbert-curve technique based on a private seed, Finally, we show that our scheme outperforms the existing methods in terms of message transmission and average sensor node lifetime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1295-1304
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• 2010

This paper proposes a fault-tolerant data aggregation which provides energy efficient and reliable data collection in wireless sensor networks. The traditional aggregation scheme does not provide the countermeasure to packet loss or the countermeasure scheme requires a large amount of energy. The proposed scheme applies caching and re-transmission based on the track topology to the adaptive timeout scheduling. The proposed scheme uses a single-path routing based on the traditional tree topology at normal, which reduces the dissipated energy in sensor nodes without any countermeasure against packet loss. The proposed scheme, however, retransmits the lost packet using track topology under event occurrences in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that the proposed scheme decrease by 8% in terms of the dissipated energy and enhances data accuracy 41% when the potential of event occurrence exists as compared with TAG data aggregation. And the proposed scheme decrease by 53% in terms of the dissipated energy and shows a similar performance in data accuracy when the potential of event occurrence exists as compared with PERLA data aggregation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.612-627
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• 2009

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.303-316
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• 2011

Data aggregation is important in wireless sensor networks. However, it also introduces many security problems, one of which is that a compromised node may inject false data or drop a message during data aggregation. Most existing solutions rely on encryption, which however requires high computation and communication cost. But they can only detect the occurrence of an attack without finding the attacking node. This makes sensor nodes waste their energy in sending false data if attacks occur repeatedly. Even an existing work can identify the location of a false data injection attack but it has a limitation that at most 50% of total sensor nodes can participate in data transmission. Therefore, a novel approach is required such that it can identify an attacker and also increase the number of nodes which participate in data transmission. In this paper, we propose a monitoring-based secure data aggregation protocol to prevent against a compromised aggregator which injects false data or drops a message. The proposed protocol consists of aggregation tree construction and secure data aggregation. In secure data aggregation, we use integration of abnormal data detection with monitoring and a minimal cryptographic technique. The simulation results show the proposed protocol increases the number of participating nodes in data transmission to 95% of the total nodes. The proposed protocol also can identify the location of a compromised node which injects false data or drops a message. A communication overhead for tracing back a location of a compromised node is O(n) where n is the total number of nodes and the cost is the same or better than other existing solutions.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1438-1449
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• 2011

UWSNs(Underwater Wireless Sensor Networks) need effective modeling fitted to the customized type of application and its covering area. In particular it requires an energy efficient data aggregation method for such customized application. In this paper, we envisage the application oriented model for monitoring the pollution or intrusion detection over a given underwater area. The suggested model is based on the honeycomb array of hexagonal prisms. In this model, the purpose of data aggregation is that the head node of each layer(cluster) receives just one event data arrived firstly and transfer this and its position data to the base station effectively in the manner of energy efficiency and simplicity without duplication. Here if we apply the existent data aggregation methods to this kind of application, the result is far from energy efficiency due to the complexity of the data aggregation process based on the shortest path or multicast tree. In this paper we propose three energy efficient and simple data aggregation methods in the domain of cluster and three in the domain of inter-cluster respectively. Based on the comparative performance analysis of the possible combination pairs in the two domains, we derive the best energy efficient data aggregation method for the suggested application.