dc.contributor.author | Andreou, Panayiotis G. | en |
dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Pamboris, Andreas | en |
dc.contributor.author | Chrysanthis, Panos K. | en |
dc.contributor.author | Samaras, George S. | en |
dc.creator | Andreou, Panayiotis G. | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Pamboris, Andreas | en |
dc.creator | Chrysanthis, Panos K. | en |
dc.creator | Samaras, George S. | en |
dc.date.accessioned | 2019-11-13T10:38:15Z | |
dc.date.available | 2019-11-13T10:38:15Z | |
dc.date.issued | 2011 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53528 | |
dc.description.abstract | In order to process continuous queries over Wireless Sensor Networks (WSNs), sensors are typically organized in a Query Routing Tree (denoted as T) that provides each sensor with a path over which query results can be transmitted to the querying node. We found that current methods deployed in predominant data acquisition systems construct T in a sub-optimal manner which leads to significant waste of energy. In particular, since T is constructed in an ad hoc manner there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. Additionally, current methods only provide a topological-based method, rather than a query-based method, to define the interval during which a sensing device should enable its transceiver in order to collect the query results from its children. We found that this imposes an order of magnitude increase in energy consumption. In this paper we present MicroPulse+, a novel framework for minimizing the consumption of energy during data acquisition in WSNs. MicroPulse+ continuously optimizes the operation of T by eliminating data transmission and data reception inefficiencies using a collection of in-network algorithms. In particular, MicroPulse+ introduces: (i) the Workload-Aware Routing Tree (WART) algorithm, which is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the critical path method | en |
dc.description.abstract | and (ii) the Energy-driven Tree Construction (ETC) algorithm, which balances the workload among nodes and minimizes data collisions. We show through micro-benchmarks on the CC2420 radio chip and trace-driven experimentation with real datasets from Intel Research and UC-Berkeley that MicroPulse+ provides significant energy reductions under a variety of conditions thus prolonging the longevity of a wireless sensor network. © 2010 Elsevier B.V. All rights reserved. | en |
dc.source | Information Systems | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649481964&doi=10.1016%2fj.is.2010.06.001&partnerID=40&md5=5f3d35972d66cef66a4efd915bd03ac2 | |
dc.subject | Optimization | en |
dc.subject | Algorithms | en |
dc.subject | Topology | en |
dc.subject | Sensor networks | en |
dc.subject | Sensor nodes | en |
dc.subject | Wireless sensor networks | en |
dc.subject | Energy consumption | en |
dc.subject | Data processing | en |
dc.subject | Trees (mathematics) | en |
dc.subject | Data transmission | en |
dc.subject | Energy conversion | en |
dc.subject | Query processing | en |
dc.subject | Real data sets | en |
dc.subject | Continuous queries | en |
dc.subject | Data acquisition system | en |
dc.subject | Energy reduction | en |
dc.subject | Energy-driven | en |
dc.subject | Query routing | en |
dc.subject | Querying nodes | en |
dc.subject | Radio chips | en |
dc.subject | Show through | en |
dc.subject | Source of energy | en |
dc.subject | Tree construction | en |
dc.subject | Consumption of energy | en |
dc.subject | Sensing devices | en |
dc.subject | Energy utilization | en |
dc.subject | Critical path method | en |
dc.subject | Data reception | en |
dc.subject | Network algorithms | en |
dc.subject | Order of magnitude | en |
dc.subject | Query results | en |
dc.subject | Query routing trees | en |
dc.subject | Query-based | en |
dc.subject | Routing trees | en |
dc.subject | Turnaround time | en |
dc.title | Optimized query routing trees for wireless sensor networks | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1016/j.is.2010.06.001 | |
dc.description.volume | 36 | |
dc.description.issue | 2 | |
dc.description.startingpage | 267 | |
dc.description.endingpage | 291 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :20</p> | en |
dc.source.abbreviation | Inf Syst | en |
dc.contributor.orcid | Zeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549] | |
dc.contributor.orcid | Andreou, Panayiotis G. [0000-0002-6369-1094] | |
dc.contributor.orcid | Chrysanthis, Panos K. [0000-0001-7189-9816] | |
dc.gnosis.orcid | 0000-0002-8388-1549 | |
dc.gnosis.orcid | 0000-0002-6369-1094 | |
dc.gnosis.orcid | 0000-0001-7189-9816 | |