efficient iceberg query processing in sensor networks

Energy‐efficient representation and dissemination of queries as well as the collection of interested data are of major concern in the design of query processing algorithms. The chapter also describes the query representation approaches and aggregation issues in WSNs in general. Abstract— Sensor networks are collection of sensor nodes which co-operatively send sensed data to base station. As sensor nodes are battery driven, an efficient utilization of power is essential in order to use networks for long duration hence it is needed to

Sensors

We investigate the in-network processing of an iceberg join query in wireless sensor networks (WSNs). An iceberg join is a special type of join where only those joined tuples whose cardinality exceeds a certain threshold (called iceberg threshold) are qualified for the result. Processing such a join involves the value matching for the join predicate as well as the checking of the cardinality

2006/1/16In this paper, we propose an energy efficient design for window query processing in sensor networks. A new design is structured to process the window queries. The use of distributed form of spatial indexing introduces greater flexibility and robustness as compared to the previous centralized approach, which lacked proper semantics and evaluation of window queries, in sensor networks.

213 TEDI: Efficient Shortest Path Query Answering on Graphs Fang Wei, University of Freiburg 217 Processing Continuous Join Queries in Sensor Networks: a Filtering Approach Mirco Stern, Universitaet Karlsruhe (TH); Erik Buchmann, Universitaet Karlsruhe

Energy‐efficient representation and dissemination of queries as well as the collection of interested data are of major concern in the design of query processing algorithms. The chapter also describes the query representation approaches and aggregation issues in WSNs in general.

A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend the operational time.


Location

Query processing on mobile sensor networks requires efficient indexing and partitioning of the data space to support efficient routing as the network scales up. Building an index structure in an ad hoc manner requires two operations: localization to discover the sensor's position; and assignment to each sensor of the appropriate data space partition. We propose a fully distributed, cost

Dynamic Routing Algorithm for Spatio-Temporal Query Processing in Sensor Networks Authors : Jeong-Joon Kim Abstract: A GR-tree method and a query aggregation (Query Aggregation) method have been proposed for spatial query processing with space query processing techniques for existing wireless sensor networks.

2013/1/1K. Park, B. Lee, R. Elmasri, Energy efficient spatial query processing in wireless sensor networks, in: 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW), 2007, pp. 719–724.

2012/5/9But nowadays researchers have focused on heterogeneous sensor networks where the sensor nodes are unlike to each other in terms of their energy. In ( Han et al., 2010 ), the authors addresses the problem of deploying relay nodes to provide fault tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different

improve performance the performance of wireless sensor networks. In this scheme, in a zone nodes share their data which shows limited nodes problems and limited query latency at a node to prolong lifetime of wireless sensor networks. a cache discovery

Efficient query processing in sensor networks involves identifying groups of nodes that coordinate to satisfy applications' requests. In this thesis, we propose a query domain abstraction that allows an application to dynamically specify the nodes best suited to answering a particular query.

from sensor networks, and telecom call records. Stream processing differs from computation over traditional stored An iceberg query [FSGM 98] performs an aggregate function over an attribute (or a set of attributes) of a relation and eliminates those 2.

iceberg query. In this paper, we propose an energy-efficient iceberg query processing technique in sensor networks. COUNT, SUM and AVG are considered as aggregate functions of the iceberg queries. To reduce the size of data transmitted, a lossless data

Routing Techniques in Wireless Sensor Networks: A Survey

Routing Techniques in Wireless Sensor Networks: A Survey⁄ Jamal N. Al-Karaki Ahmed E. Kamal Dept. of Electrical and Computer Engineering Iowa State University, Ames, Iowa 50011 Email: fjkaraki, kamalgiastate.edu Abstract WirelessSensorNetworks(WSNs

from sensor networks, and telecom call records. Stream processing differs from computation over traditional stored An iceberg query [FSGM 98] performs an aggregate function over an attribute (or a set of attributes) of a relation and eliminates those 2.

Query processing. General Terms Algorithms, Design, Performance, Experimentation Keywords Sensor Networks, Collision Domains, Query Optimization, Data Transmission Algebra, Whirlpool 1. INTRODUCTION Recent advances in wirelessnetworks.

MACAQUE is an uncertainty-aware data collection system that provides energy- and bandwidth-efficient querying in resource-limited environments, such as sensor or other wireless networks. MACAQUE provides an SQL-like query interface for specifying when and where data should be acquired.

Query processing. General Terms Algorithms, Design, Performance, Experimentation Keywords Sensor Networks, Collision Domains, Query Optimization, Data Transmission Algebra, Whirlpool 1. INTRODUCTION Recent advances in wirelessnetworks.

Sensor networks offer an additional set of challenges: Due to cost and space constraints, typical nodes in sensor networks have very limited processing power. Additionally, wireless networks are usually very lossy, suffering from undetectable packet losses, packet collisions and other forms of interference.

Routing Techniques in Wireless Sensor Networks: A Survey⁄ Jamal N. Al-Karaki Ahmed E. Kamal Dept. of Electrical and Computer Engineering Iowa State University, Ames, Iowa 50011 Email: fjkaraki, kamalgiastate.edu Abstract WirelessSensorNetworks(WSNs

Wireless Sensor Network is a network of a few to several thousand sensors deployed over an area to sense data and report that data back to the base station. There are many applications of wireless sensor networks including environment monitoring, wildlife tracking, troop tracking etc. The deployed sensors have many constraints like limited battery, limited memory and very little processing

TinyDB: An Acquisitional Query Processing System for Sensor Networks (PDF) Mate: A Tiny Virtual Machine for Sensor Networks (PDF) TinyLIME: Bridging Mobile and Sensor Networks through Middleware (PDF) 4. MAC Protocols MAC Overview (Characteristics

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