• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.35-40
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• 2011

In this paper, we compare and analyze data aggregation methods based on event area in wireless sensor networks. Data aggregation methods consist of two methods: the direct transmission method and the aggregation node method. The direct aggregation method has some problems that are data redundancy and increasing network traffic as all nodes transmit own data to neighbor nodes regardless of same data. On the other hand the aggregation node method which aggregate neighbor's data can prevent the data redundancy and reduce the data. This method is based on location of nodes. This means that the aggregation node can be selected the nearest node from a sink or the centered node of event area. So, we describe the benefits of data aggregation methods that make up for the weak points of direct data dissemination of sensor nodes. We measure energy consumption of the existing ways on data aggregation selection by increasing event area. To achieve this, we calculated the distance between an event node and the aggregation node and the distance between the aggregation node and a sink node. And we defined the equations for distance. Using these equations with energy model for sensor networks, we could find the energy consumption of each method.

• Journal of Internet Technology
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• v.22 no.6
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• pp.1287-1297
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• 2021

Data aggregation is the significant process in which the information is gathered and combines data to decrease the amount of data transmission in the WSN. The sensor devices are susceptible to node attacks and security issues such as data confidentiality and data privacy are extremely important. A novel technique called Ruzicka Index Regressive Homomorphic Ephemeral Key Benaloh Cryptography (RIRHEKBC) technique is introduced for enhancing the security of data aggregation and data privacy in WSN. By applying the Ruzicka Index Regressive Homomorphic Ephemeral Key Benaloh Cryptography, Ephemeral private and public keys are generated for each sensor node in the network. After the key generation, the sender node performs the encryption using the receiver public key and sends it to the data aggregator. After receiving the encrypted data, the receiver node uses the private key for decrypting the ciphertext. The key matching is performed during the data decryption using Ruzicka Indexive regression function. Once the key is matched, then the receiver collects the original data with higher security. The simulation result proves that the proposed RIRHEKBC technique increases the security of data aggregation and minimizes the packet drop, and delay than the state-of-the- art methods.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.358-364
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• 2007

This paper suggests MPLS restoration method that use an aggregation tree. For the restoration of the MPLS network, this paper presents a scheme that reconstruct multiple path through aggregation tree that grow from many node to a target node. Contrary to a multicast tree where a message that send at one node is passed to a group of node, an aggregation tree is a tree that data is passed from many node to one destination node. Through an experiment we confirmed that the restoration scheme that uses aggregation tree shows taster speed comparing with the existing other restoration scheme.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.209-218
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• 2009

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.237-244
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• 2007

In this paper we investigate the benefits of a data aggregation to prolong the lifetime of wireless sensor networks. To reduce the overload of messages from source node to sink node, data aggregation technique is generally used at intermediate node in path. The DD-G(Directed Diffusion-Greedy) can diminish the consumption of node energy by establishing energy effective single path from source to destination. In this case, the nodes near sink node have some problems, i) overly concentration of energy consumption, ii) increase of message delay time. To solve these problems, we propose a new data aggregation method which consider distribution of network overload, especially at the nodes close to sink node. The result shows that it can save energy and network delay time.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1529-1541
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• 2006

Moving objects have been widely employed in traffic and logistic applications. Spatio-temporal aggregations mainly describe the moving object's behavior in the spatial data warehouse. The previous works usually express the object moving in some certain region, but ignore the object often moving along as the trajectory. Other researches focus on aggregation and comparison of trajectories. They divide the spatial region into units which records how many times the trajectories passed in the unit time. It not only makes the storage space quite ineffective, but also can not maintain spatial data property. In this paper, a spatio-temporal aggregation index structure for moving object trajectory in constrained network is proposed. An extended B-tree node contains the information of timestamp and the aggregation values of trajectories with two directions. The network is divided into segments and then the spatial index structure is constructed. There are the leaf node and the non leaf node. The leaf node contains the aggregation values of moving object's trajectory and the pointer to the extended B-tree. And the non leaf node contains the MBR(Minimum Bounding Rectangle), MSAV(Max Segment Aggregation Value) and its segment ID. The proposed technique overcomes previous problems efficiently and makes it practicable finding moving object trajectory in the time interval. It improves the shortcoming of R-tree, and makes some improvement to the spatio-temporal data in query processing and storage.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.115-122
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• 2017

In this paper, we propose an adaptive data aggregation and compression scheme for wireless sensor networks with energy-harvesting nodes, which increases the amount of data arrived at the sink node by efficient use of the harvested energy. In energy-harvesting wireless sensor networks, sensor nodes can have more than necessary energy because they harvest energy from environments continuously. In the proposed scheme, when a node judges that there is surplus energy by estimating its residual energy, the node compresses and transmits the aggregated data so far. Conversely, if the residual energy is estimated to be depleted, the node turns off its transceiver and collects only its own sensory data to reduce its energy consumption. As a result, this scheme increases the amount of data collected at the sink node by preventing the blackout of relay nodes and facilitating data transmission. Through simulation, we show that the proposed scheme suppresses the occurrence of blackout nodes and collect the largest amount of data at the sink node compared to previous schemes.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.121-129
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• 2011

In wireless sensor networks, a compromised sensor node can inject false data during data aggregation. Existing solutions of securing data aggregation require high communication cost in securing data aggregation. In this paper, we propose a monitoring-based secure data aggregation protocol that minimizes communication cost of identifying the location of false data injection attacks. The main idea is that when monitoring nodes find an injected false data, their reporting messages along with Message Authentication Codes (MACs) are summarized in a single message before sending it to the Base Station (BS). Then the BS identifies the attacking node. The simulation shows that energy consumption of the proposed protocol with short and normal concatenations of MACs are 45% and 36% lower than that of an existing protocol, respectively.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.119-126
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• 2012

Local monitoring is an effective technique in securing data of wireless sensor networks. Existing solutions require high communication cost for detecting false data and this results in a network lifetime being shortened. This paper proposes novel techniques of monitoring based secure data aggregation and filtering false data in wireless sensor networks. The aim is to reduce energy consumption in securing data aggregation. An aggregator and its monitoring node perform data aggregation in a 60o sextant cluster. By checking Message Authentication Codes (MAC), aggregation data will be dropped by a forward aggregator if data aggregated by the aggregator and data monitored by the monitoring node are inconsistent. The simulation shows that the proposed protocol can reduce the amount of average energy consumption about 64% when comparing with the Data Aggregation and Authentication protocol (DAA)[1]. Additionally, the network lifetime of the proposed protocol is 283% longer than that of DAA without any decline in data integrity.