ISLPED '99 Proceedings of the 1999 international symposium on Low power electronics and design
System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Silent Stores and Store Value Locality
IEEE Transactions on Computers
Maté: a tiny virtual machine for sensor networks
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
An ultra low-power processor for sensor networks
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
An Ultra Low Power System Architecture for Sensor Network Applications
Proceedings of the 32nd annual international symposium on Computer Architecture
Avrora: scalable sensor network simulation with precise timing
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Reducing energy dissipation of wireless sensor processors using silent-store-filtering motecache
PATMOS'06 Proceedings of the 16th international conference on Integrated Circuit and System Design: power and Timing Modeling, Optimization and Simulation
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Today, wireless sensor networks (WSNs) enable us to run a new range of applications from habitat monitoring, to military and medical applications. A typical WSN node is composed of several sensors, a radio communication interface, a microprocessor, and a limited power supply. In many WSN applications, such as forest fire monitoring or intruder detection, user intervention and battery replenishment is not possible. Since the battery lifetime is directly related to the amount of processing and communication involved in these nodes, optimal resource usage becomes a major issue. A typical WSN application may sense and process very close or constant data values for long durations, when the environmental conditions are stable. This is a common behavior that can be exploited to reduce the power consumption of WSN nodes. This study combines two orthogonal techniques to reduce the energy dissipation of the processor component of the sensor nodes. First, we briefly discuss silent-store filtering MoteCache. Second, we utilize Content-Aware Data MAnagement (CADMA) on top of MoteCache architecture to achieve further energy savings and performance improvements. The complexity increase introduced by CADMA is also compensated by further complexity reduction in MoteCache. Our optimal configuration reduces the total node energy, and hence increases the node lifetime, by 19.4% on the average across a wide variety of simulated sensor benchmarks. Our complexity-aware configuration with a minimum MoteCache size achieves not only energy savings up to 16.2% but also performance improvements up to 4.3%, on the average.