Data-centric Storage Scheme Research Articles

A data-centric storage scheme for high storage utilization in wireless sensor networks

In wireless sensor networks, a data-centric storage (DCS) scheme is one of representative researches to store sensor readings and to process a query efficiently. The DCS scheme assigns distributed data regions to sensor nodes and stores sensor readings to the sensor node which is responsible for the data region to process the query efficiently. However, the existing DCS schemes have some drawbacks that the sensor nodes have the fixed ranges to store sensor readings. Because the ranges of the sensor readings change periodically in real world applications, the existing DCS schemes have problems that they use storage space unevenly in entire sensors and their network lifetimes are reduced. To overcome this problem, we propose a novel DCS scheme for high storage utilization in wireless sensor networks. The proposed scheme stores the sensed data equally in the entire sensor network to improve the storage utilization. To show the superiority of our proposed scheme, we compare it with the existing DCS schemes. Our experimental results show that our proposed scheme improves about 498 % storage utilization and about 377.7 % network lifetime over the existing schemes on average.

무선 센서 네트워크 데이터 중심 저장 환경을 위한 소실 데이터 근사 복구 기법

The data centric storage (DCS) scheme is one of representative methods to efficiently store and maintain data generated in wireless sensor networks. In the DCS schemes, each node has the specified data range for storing data. This feature is highly vulnerable to the faults of nodes. In this paper, we propose a new recovery scheme for the lost data caused by the faults of nodes in DCS environments. The proposed scheme improves the accuracy of query results by recovering the lost data using the spatial continuity of physical data. To show the superiority of our proposed scheme, we simulate it in the DCS environments with the faults of nodes. In the result, our proposed scheme improves the accuracy by about 28% through about 2.5% additional energy consumption over the existing scheme.

데이터 중심 저장 기법을 위한 효율적인 센서 데이터 압축 기법

데이터 중심 저장 기법은 센서 네트워크에서 측정값을 효율적으로 저장하고 관리하기 위한 대표적인 연구 중 하나이다. 이 기법은 센서가 센싱한 데이터를 특정 센서 노드로 보내 저장한다. 하지만, 측정값을 네트워크 내부의 특정 노드로 전송하는 과정에서 많은 에너지를 소모하는 문제점을 가지고 있다. 본 논문에서는 데이터 중심 저장 기법에서 데이터의 전송 비용을 줄이기 위한 새로운 센서 데이터 압축 기법을 제안한다. 제안하는 기법은 측정값의 안전영역(Safe Region) 범위를 설정하고, 측정값이 안전영역을 벗어나는 경우만 데이터를 전송한다. 이를 통해 데이터의 전송을 줄이고 네트워크의 수명을 연장 시킨다. 성능평가 결과, 기존 기법에 비해 제안하는 기법의 에너지 소모가 60% 감소하였다. Data-centric storage schemes(DCS) are one of representative researches that efficiently store and manage sensor readings in sensor nodes in the sensor networks. In DCS, a sensor sends the sensed data to a specific node in order to store them. However, it has a problem that sensor nodes consume a lot of energy for transmitting their readings to remote sensor node. In this paper, we propose a novel sensor data compression algorithm to reduce communication costs for DCS. The proposed algorithm establishes a safe region and transmits the sensed data only when current measurement is out of the safe region, As a result, the proposed algorithm extends network life time and reduces data transmission. It is shown through performance evaluation that our proposed algorithm reduces energy consumption by about 60% over the conventional algorithm.

An efficient data-centric storage method using time parameter for sensor networks

In wireless sensor networks, various schemes have been proposed to efficiently store and process sensed data. Among them, the data-centric storage (DCS) scheme is one of the most well-known. The DCS scheme distributes data regions and stores the data in the sensor that is responsible for the region. The DCS based scheme was proposed to reduce the communication cost for transmitting data and to efficiently process exact queries and range queries. Recently, a KDDCS scheme was proposed to overcome storage hot-spots by dynamically readjusting the distributed data regions to sensors based on the K-D tree. However, the existing DCS based schemes including KDDCS suffer from query hot-spots that are formed when query regions are not uniformly distributed. As a result, it reduces the lifetime of the sensor network.In this paper, we propose a new DCS based scheme, called Time-Parameterized Data-Centric Storage (TPDCS), that avoids the problems of storage hot-spots and query hot-spots. To decentralize the skewed data and queries, the data regions are assigned by a time dimension as well as data dimensions in our proposed scheme. Therefore, TPDCS extends the lifetime of sensor networks. It is shown through various experiments that our scheme outperforms the existing schemes.

The Research of Data Storage and Retrieval Scheme for Wireless Sensor Networks

Recently, several data storage schemes have been developed to store massive sensor data in the wireless sensor networks (WSNs). A crucial task of WSNs is to disseminate useful information to users efficiently and handle the data storage architecture incorporating their extreme resource constraints. A Distributed Index based Multi-resolution Storage Architecture (DIMSA) for data storage and retrieval at multiple levels of detail in WSNs is proposed in this paper. The proposed scheme could automatically disseminate useful information to users in correspondence to the user defined level of detail to save energy. In the condition that some attributes are included in many events, the values for these attributes have to be replicated and stored at different places in the network for each individual event in traditional data-centric storage schemes. This will consume some extra energy. To address this problem, DIMSA deploys an attribute allocation scheme for finding a good distribution of attributes to the sensor networks. In addition, a distributed index scheme is also proposed to avoid query flooding and extra data transmission. Analysis and simulations are conducted to evaluate the performance of the proposed scheme. The results show that DIMSA outperforms the traditional data-centric storage scheme like GHT.

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.