Abstract
Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.
Original language | English |
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Title of host publication | ACM International Conference Proceeding Series |
Publisher | Association for Computing Machinery |
ISBN (Print) | 9781450327220 |
DOIs | |
Publication status | Published - 2014 |
Event | 26th International Conference on Scientific and Statistical Database Management - Aalborg, United Kingdom Duration: 30 Jun 2014 → 2 Jul 2014 |
Conference
Conference | 26th International Conference on Scientific and Statistical Database Management |
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Abbreviated title | SSDBM 2014 |
Country/Territory | United Kingdom |
City | Aalborg |
Period | 30/06/14 → 2/07/14 |
Keywords
- Benchmarks
- Query processing
- Wireless sensor networks
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software