Scheduling real-time transactions: a performance evaluation
ACM Transactions on Database Systems (TODS)
Real-time transaction scheduling: a cost conscious approach
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Value-based scheduling in real-time database systems
The VLDB Journal — The International Journal on Very Large Data Bases
Multiclass Query Scheduling in Real-Time Database Systems
IEEE Transactions on Knowledge and Data Engineering
An adaptive scheduler for distributed real-time database systems
Information Sciences: an International Journal
Flexible power scheduling for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Distributed Cross-Layer Scheduling for In-Network Sensor Query Processing
PERCOM '06 Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications
Towards optimal sleep scheduling in sensor networks for rare-event detection
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Energy and quality aware query processing in wireless sensor database systems
Information Sciences: an International Journal
Data Quality and Query Cost in Wireless Sensor Networks
PERCOMW '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops
MaD-WiSe: a distributed stream management system for wireless sensor networks
Software—Practice & Experience
Dynamic QoS-aware event sampling for community-based participatory sensing systems
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Less is more: selecting sources wisely for integration
Proceedings of the VLDB Endowment
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We study query scheduling in Wireless Sensor Networks (WSNs) with a focus on two important metrics: Quality of Service (QoS) and Quality of Data (QoD). The motivation comes from our observation that most WSN scheduling techniques ignore the quality requirements of queries. As a result, they are inefficient or inapplicable to quite a few applications that have different quality requirements. In this paper, we propose a distributed Quality Aware Scheduling (QAS) framework to address this problem. QAS works on top of existing quality-unaware query scheduling protocols and allows individual users to specify their QoS and QoD requirements on their queries. Given these quality requirements, QAS determines the target qualities to be provided in scheduling and the execution order of these queries so as to maximize the total system profit. Our preliminary results show that QAS significantly outperforms the baseline scheduling algorithms in terms of system profit.