dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Andreou, Panayiotis G. | en |
dc.contributor.author | Chrysanthis, Panos K. | en |
dc.contributor.author | Samaras, George S. | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Andreou, Panayiotis G. | en |
dc.creator | Chrysanthis, Panos K. | en |
dc.creator | Samaras, George S. | en |
dc.date.accessioned | 2019-11-13T10:43:02Z | |
dc.date.available | 2019-11-13T10:43:02Z | |
dc.date.issued | 2007 | |
dc.identifier.isbn | 978-1-59593-911-1 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/55175 | |
dc.description.abstract | This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter in order to minimize energy consumption while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a message complexity of O(p + n), where p denotes the number of nodes on the perimeter and n the overall number of nodes. For storage and replication we devise a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles and minimum bounding cuboids. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. | en |
dc.source | ACM International Conference Proceeding Series | en |
dc.source | DMSN '07: 4th Workshop on Data Management for Sensor Networks | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-38849091976&doi=10.1145%2f1286380.1286384&partnerID=40&md5=967fc8cfb57d9a0fac0e10df6f778f23 | |
dc.subject | Parallel algorithms | en |
dc.subject | Mobile telecommunication systems | en |
dc.subject | Wireless sensor networks | en |
dc.subject | Telecommunication links | en |
dc.subject | Data acquisition | en |
dc.subject | Query processing | en |
dc.subject | Mobile sensors | en |
dc.subject | Sensing devices | en |
dc.subject | Data availability rates | en |
dc.subject | Perimeter Algorithm (PA) | en |
dc.title | SenseSwarm: A perimeter-based data acquisition framework for mobile sensor networks | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1145/1286380.1286384 | |
dc.description.volume | 273 | |
dc.description.startingpage | 13 | |
dc.description.endingpage | 18 | |
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 | Conference Object | en |
dc.description.notes | <p>Sponsors: Intel | en |
dc.description.notes | Conference code: 71378 | en |
dc.description.notes | Cited By :7</p> | 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 | |