Data aggregator

About: Data aggregator is a research topic. Over the lifetime, 2615 publications have been published within this topic receiving 40265 citations.

Architecture of Distributed Data Aggregation Service

Abstract: The ever-growing trend of deploying applications over the Internet has resulted in increasingly tougher constraints and requirements. Data management systems are a major concern when it comes to scalability, flexibility and reliability due to being implemented in a distributed way. In this paper we present a Distributed Data Aggregation Service relying on a storage system designed to meet these demands, namely Blob Seer. The primary goal is to serve as a repository backend for complex analysis and automatic mining of scientific data (like bibtex entries). Several requirements, derived from this objective, match Blob Seer's features: versioning used for lock-free access to data and different granularity of read / write operations. We proposed a model to perform the correct translation between Blob Seer's unstructured view of data and the user's structured view. We implemented a client providing a formal description for the data retrieval queries and a specification for a search API. A benchmark tool relying on a performance model of Blob Seer, will be used to automatically determine the best Blob Seer deployment configuration for a specific data aggregation pattern.

Preserving data and key privacy in Data Aggregation for Wireless Sensor Networks

Abstract: Reliable and trustful data aggregation is needed for most application in Wireless Sensor Networks. In this paper, we propose a new approach to attain data and key privacy protection in data aggregation called Preserving Data and Key Privacy in Data Aggregation for Wireless Sensor Networks (PDKP).Existing privacy preserving protocol provide more computational and communicational overhead in the sensor nodes. It increases the consumption of energy among the nodes. In our scheme, the encrypted content of the data is shared without revealing the data and key to other nodes by using simple technique. It preserves the key and data from an adversary with less computational and communication overhead. The base station can identify the distrustful groups related to the set of group aggregates and the retransmission of data is performed only for the abnormal data sensing intermediate nodes. It preserves the various security issues such as data freshness, data integrity, data confidentiality in data aggregation. Our simulation result showed that implementation of PDKP reduces the communication overhead and increases energy efficiency.

Secure data aggregation in wireless sensor networks

Abstract: In-network data aggregation is an effective method to reduce the amount of data transmitted and therefore saves energy consumption in sensor networks. However, an adversary may compromise some sensor nodes, and use them to forge false values as the aggregation result. Previous secure data aggregation schemes have tackled this problem from different angles. The goal of those algorithms is to ensure that the Base Station (BS) does not accept any forged aggregation results. Based on our survey of existing research efforts for ensuring secure data aggregation, a novel approach that uses homomorphic encryption and Message Authentication Codes (MAC) to achieve confidentiality, authentication and integrity for secure data aggregation in wireless sensor networks is proposed. Our experiments show that our proposed secure aggregation method significantly reduces computation and communication overhead.

A Signature-Based Data Security Technique for Energy-Efficient Data Aggregation in Wireless Sensor Networks

Abstract: Data aggregation techniques have been widely used in wireless sensor networks (WSNs) to solve the energy constraint problems of sensor nodes. They can conserve the significant amount of energy by reducing data packet transmission costs. However, many data aggregation applications require privacy and integrity protection of the real data while transmitting data from the sensing nodes to a sink node. The existing schemes for supporting both privacy and integrity, that is, iCDPA, and iPDA, suffer from high communication cost, high computation cost, and data propagation delay. To resolve the problems, we propose a signature-based data security technique for protecting sensitive data aggregation in WSNs. To support privacy-preserving data aggregation and integrity checking, our technique makes use of the additive property of complex numbers. Out of two parts of a complex number, the real part is used to hide the sampled data of a sensor node from its neighboring nodes and adversaries, whereas the imaginary part is used for data integrity checking at both data aggregators and the sink node. Through a performance analysis, we prove that our privacy-preserving data aggregation scheme outperforms the existing schemes up to 50% in terms of communication and computation overheads as well as up to 3 times in terms of integrity checking and data propagation delay.