Multi-sensor fusion: fundamentals and applications with software
Multi-sensor fusion: fundamentals and applications with software
A performance comparison of multi-hop wireless ad hoc network routing protocols
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
Scenario-based performance analysis of routing protocols for mobile ad-hoc networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Wireless integrated network sensors
Communications of the ACM
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Geography-informed energy conservation for Ad Hoc routing
Proceedings of the 7th annual international conference on Mobile computing and networking
Wireless sensor networks: application driver for low power distributed systems
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Building efficient wireless sensor networks with low-level naming
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Power-Aware Localized Routing in Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
Operating System and Algorithmic Techniques for Energy Scalable Wireless Sensor Networks
MDM '01 Proceedings of the Second International Conference on Mobile Data Management
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Low-Power Wireless Sensor Networks
VLSID '01 Proceedings of the The 14th International Conference on VLSI Design (VLSID '01)
Sink-to-sensors reliability in sensor networks
ACM SIGMOBILE Mobile Computing and Communications Review
Energy-scalable algorithms and protocols for wireless microsensor networks
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Adaptive Optimizations for Surveillance Sensor Network Longevity
International Journal of Distributed Sensor Networks
Hi-index | 0.00 |
Wireless sensor networks will be widely deployed in the future for monitoring important environmental conditions, security, and health care. One of the most important challenges in the implementation of such networks is minimizing energy dissipation. Given that many of the energy optimization problems defined for sensor networks are very hard, heuristics are commonly employed. Evaluating the effectiveness of these heuristics, i.e., how close do they come to the optimal solutions, is a challenge. While algorithms that give optimal solutions cannot be on-line (since they are expensive), if they are used off-line, they can provide invaluable insight to improve existing heuristics and to derive new ones. In this paper, we present an integer linear programming (ILP)-based tool that can be used to evaluate optimal solutions for communication energy optimization in sensor networks under specific constraints. This tool, which is based on the required sensing and communication schedules, determines optimal sensor movement and communication strategies to minimize energy consumption due to inter-sensor communication. The tool can also accommodate several constraints related to movement capabilities of sensor nodes, their battery capacities, and their communication ranges since all these can be expressed in a linear form. In addition, it can also work with objective functions other than minimizing communication energy. Our experience with the tool indicates that it is very useful for studying different scenarios under which an objective function needs to be optimized.