Therefore, we consider the communication cost aspect and we propose an Incremental Join Algorithm (IJA) as an innetwork join strategy which is an efficient join processing in sensor networks and minimizes communication cost.

Real Time Support and Energy Efficiency in WSN 11 1. Introduction Advances in wireless communication made it possible to develop wireless sensor networks (WSN) consisting of small devices, which collect information by cooperating with each other. These small sensing devices are called nodes and consist of CPU (for data processing),

Title: Adaptive aggregation tree transformation for energyefficient query processing in sensor networks Authors : MuHuan Chiang, Gregory T. Byrd Addresses : Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA.

This paper studies the issues of energyefficient query optimization for wireless sensor networks. Different from existing query optimization techniques that consider only query plans for extracting data from sensors at individual nodes, our approach takes into account both of the sensing and communication cost in query plans.

Recent sensor networks research has produced a class of data storage and query processing techniques called DataCentric Storage that leverages localitypreserving distributed indexes like DIM, DIFS, and GHT to efficiently answer multidimensional range and rangeaggregate queries. These distributed indexes offer a rich design space of a) logical decompositions of sensor relation schema into indexes, as well .

Innetwork join: that performs join query at a node or a set of nodes in the network. The number of transmitted messages is then decreased and the performance heighted. Join types in wireless sensor network . There are two types of joins queries in wireless sensor networks [7].

However, in sensor network, minimizing the communication cost is the main performance criteria. In this paper, the focus is on proposing an energy efficient processing of join queries over sensor networks. Users query the sensor network to manipulate the sensed data on the monitored environment.

In the field of wireless sensor networks, the secure range query technique is a challenging issue. In twotiered wireless sensor networks, a verifiable privacypreserving range query processing method is proposed that is based on bucket partition, information identity authentication, and checkcode fusion.

Query Processing in Sensor Networks From the database perspective, in{network aggregation is a mode for evaluating aggregate queries over the sensor network. The common approach to (aggregate) query processing in sensor networks has two phases: .

Intuitively centralized processing on Base Station can accomplish area queries via collecting information from all sensor nodes. However, this method is not suitable for wireless sensor networks with limited energy since a large amount of energy is wasted for reporting useless data. This motivates us to propose an energyefficient innetwork area query processing scheme.

Yongxuan Lai, Xing Gao, Tian Wang, Ziyu Lin: Efficient Iceberg Join Processing in Wireless Sensor Networks. International Journal of Embedded Systems 9(4): 365378 (2017) Yongxuan Lai, Jinshan Xie, Ziyu Lin, Tian Wang, Minghong Liao: Adaptive Data Gathering in Mobile Sensor Networks Using Speedy Mobile Elements.

We show that our proposed scheme is energy efficient for query and data processing heuristically. Our proposed scheme, sectioned tree, is finally simulated in sparse and dense networks to show the energy saving for query and data processing in the sensor network.

Processing approximate aggregate queries in wireless sensor networks, For monitoring queries that aggregate the observed values from a group of sensor nodes,, Y Yao, J GehrkeThe Cougar approach to innetwork query processing in sensor networks

communication technologies, wireless sensor networks (WSNs) become important data sources and have been widely used in many applications [13]. In the database view, a WSN can be regarded as a distributed database, and efficient query processing methods for various types of queries in WSN become a hot topic in research community [46].

paper, we consider a twotiered sensor network architecture in which storage nodes gather data from nearby sensors and answer queries from the sink of the network. The storage nodes serve as an intermediate tier between the sensors and the sink for storing data and processing queries. Storage nodes bring three main benefits to sensor networks.

Energy Efficient Skyline Query Processing in Wireless Sensor Networks Bibtex entry for this abstract Preferred format for this abstract (see Preferences ) Find Similar Abstracts:

The large volume of data generated by sensors needs to be processed to respond to the users queries. However, efficient processing of queries in sensor networks poses great challenges due to the unique characteristics imposed on sensor networks including slow processing capability, limited storage, and energylimited batteries, etc.

This work minimizes the cost of answering queries in wireless sensor networks. To answer a query, data generated by the sensors needs to be collected and processed. We optimize the cost by constructing sophisticated query trees. Queries are divided into two categories: queries that need data from ...

In this paper, we propose a new algorithm called KVC (vKNN queries based on value clustering ) to process the vKNN queries in wireless sensor networks in an energy efficient way. KVC takes advantage of the rich resources in the base station to do some optimizations to filter the irrelevant nodes and push down the vKNN query into the network.

Abstract. Abstract — This paper studies the issues of energyefficient query optimization for wireless sensor networks. Different from existing query optimization techniques that consider only query plans for extracting data from sensors at individual nodes, our approach takes into account both of the sensing and communication cost in query plans.

Our innetwork area query processing scheme is energyefficient in various circumstance. Conclusions An energyefficient innetwork area query processing scheme. Gray Code based GID for area description. Reporting and merging through a reporting tree. Incremental updating strategy for continuous queries, avoiding unnecessary reports.

Abstract: In order to address the problem of energy and timeefficient execution of spatial queries in multisink wireless sensor networks, an efficient hybrid spatial query processing algorithm (EHSQP) is proposed in this paper. In EHSQP, sink nodes perform the sector selection for the query region and seek the query route to a query region ...