Data aggregator

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

NEECP: Novel energy-efficient clustering protocol for prolonging lifetime of WSNs

Abstract: In this paper, a novel energy-efficient clustering protocol (NEECP) for increasing the network lifetime in wireless sensor networks is proposed. This technique selects the cluster heads in an effective way with an adjustable sensing range and performs data aggregation using chaining approach. It also avoids transmission of redundant data by using a redundancy check function for improving the network lifetime. It is implemented by considering the data with aggregation and without aggregation. The NEECP without aggregation increases the network lifetime by 59.76 and 7.17% as compared with the hybrid energy-efficient distributed (HEED) and intra-balanced low-energy adaptive clustering hierarchy (IBLEACH), respectively. It increases the network lifetime by 122.92 and 49.53% over the HEED and IBLEACH, respectively, while considering data aggregation.

Active rules for sensor databases

Abstract: Recent years have witnessed a rapidly growing interest in query processing in sensor and actuator networks. This is mainly due to the increased awareness of query processing as the most appropriate computational paradigm for a wide range of sensor network applications, such as environmental monitoring. In this paper we propose a second database technology, namely active rules, that provides a natural computational paradigm for sensor network applications which require reactive behavior, such as security management and rapid forest fire response. Like query processing, efficient and effective active rule execution mechanisms have to address several technical challenges including language design, data aggregation, data verification, robustness under topology changes, routing, power management and many more. Nonetheless, active rules change the context and the requirements of these issues and hence a new set of solutions is appropriate. To this end, we outline the implications of active rules for sensor networks and contrast these against query processing. We then proceed to discuss work in progress carried out in project Asene that aims to effectively address these issues. Finally, we introduce our architecture for a decentralized event broker based on the publish/subscribe paradigm and our early design of an ECA language for sensor networks.

Data Aggregation and Routing In Wireless Sensor Networks: Optimal and Heuristic Algorithms

Abstract: A fundamental challenge in the design of Wireless Sensor Networks (WSNs) is to maximize their lifetimes especially when they have a limited and non replenishable energy supply. To extend the network lifetime, power management and energy-efficient communication techniques at all layers become necessary. In this paper, we present solutions for the data gathering and routing problem with in-network aggregation in WSNs. Our objective is to maximize the network lifetime by utilizing data aggregation and in- network processing techniques. We particularly focus on the joint problem of optimal data routing with data aggregation en route such that the above mentioned objective is achieved. We present Grid-based Routing and Aggregator Selection Scheme (GRASS), a scheme for WSNs that can achieve low energy dissipation and low latency without sacrificing quality. GRASS embodies optimal (exact) as well as heuristic approaches to find the minimum number of aggregation points while routing data to the Base Station (BS) such that the network lifetime is maximized. Our results show that, when compared to other schemes, GRASS improves system lifetime with acceptable levels of latency in data aggregation and without sacrificing data quality.

A Sensor Network Data Aggregation Technique

Abstract: —Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network's operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

A Meta-Data-Based Data Aggregation Scheme in Clustering Wireless Sensor Networks

Abstract: Energy efficiency has been known as the most significant problem in all facets of the wireless sensor network operations. In this paper, we propose a meta-data-based data aggregation scheme in the clustering wireless sensor networks. For all sensor nodes in the sensing range of an event can detect the event and generate the sensing data, the cluster head will receive the sensing data packets about the same event, and there is likely to be some redundancy. In our scheme, only one of the sensor nodes within the sensing range of an event in a cluster is selected to transmit the sensing data to the cluster head via the meta data negotiation. We also evaluate this scheme with the LEACH protocol. The simulation results show that the cluster protocol with our data aggregation scheme is effective in prolonging the network lifetime and supporting scalable data aggregation.