• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.1
• /
• pp.35-40
• /
• 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 Korea Multimedia Society
• /
• v.14 no.11
• /
• pp.1438-1449
• /
• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.3
• /
• pp.115-122
• /
• 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
• /
• v.17 no.2
• /
• pp.119-126
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.109-114
• /
• 2013

In underwater wireless sensor networks, sensing data such temperature and salinity can be merged by averaging them. Data aggregation is a good choice to reduce the amount of packets and save energy in underwater wireless sensor networks. However, data aggregation could bring about packet delay and non-directional transmission to the sink. In this paper, we propose a new path building algorithm based on data aggregation to mitigate these problems. The paper reduces the delay without wireless interferences and maximizes the energy efficiency by removing the non-directional transmission to the sink. Experimental results show that the proposed algorithm outperforms in terms of the energy efficiency and the packet delay.

• Journal of the Korea Computer Industry Society
• /
• v.8 no.4
• /
• pp.237-244
• /
• 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 Spatial Information System Society
• /
• v.12 no.1
• /
• pp.10-17
• /
• 2010

Sensor nodes used in Geosensor network are resource limited and power constrained. So it is necessary to research on routing protocols to gather data by using energy efficiently. Wireless sensor networks collect data gathered from sensor nodes by transfering it to the sink using multihop. However, it has two problems. First, the existing works require unnecessary data transmission for choosing a proper parent node to transfer data. Secondly, they have a large number of data transmission because each sensor node has a different path. To solves the problems, we, in this paper, propose a designated path based data aggregation scheme for efficient energy management in WSNs. The proposed scheme can reduce unnecessary data transmission by pre-determining a set of paths and can enable all the sensor nodes to participate in gathering data by running them in round-robin fashion. We show from performance analysis that the proposed scheme is more energy efficient than the existing directed diffusion(DD) and the hierarchical data aggregation(HDA).

• Journal of IKEEE
• /
• v.22 no.3
• /
• pp.729-732
• /
• 2018

This paper performs Agregation for supplementing the additional generator when reflecting the plan DB based on a number of renewable power sources, line and transformer data. In this study, modeling of a line and a generator through a Collector method and a Step-Up-Transformer among Aggregation execution methods is conducted.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.5B
• /
• pp.326-333
• /
• 2008

In wireless sensor networks, a sensor node with in-network aggregation adjusts the timeout which is a waiting time to receive messages from child nodes. This paper proposes a novel timeout scheduling scheme for data aggregation in wireless sensor networks, which adaptively configures its timeout according to changing data patterns in order to improve energy efficiency and data accuracy during data aggregation. The proposed scheme decreases the timeout when the temporal difference of collected data(data variation) from children is lower than a pre-defined threshold because there is no occurrence of critical events. Conversely, it increases the timeout when the data variation is higher than the pre-defined threshold in order to fulfill more accurate data aggregation. Extensive simulation reveals that the proposed scheme outperforms the cascading-based scheme in terms of energy consumption and data accuracy.

• Journal of KIISE:Information Networking
• /
• v.35 no.4
• /
• pp.326-336
• /
• 2008

Wireless sensor networks have been studied with two typical applications called event-driven and periodic monitoring. Although these applications have different core requirements, they have the same low latency requirement. However, main issue of the protocol in wireless sensor networks was focused on an energy efficiency, so it has not considered the latency problem. In this paper, we propose the RA-MAC, an energy efficient and low latency MAC protocol using a new channel access mechanism and the RTS Aggregation scheme for wireless sensor networks. Our simulation results show that the RA-MAC provides energy savings and latency reduction.