GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Multicast tree construction and flooding in wireless ad hoc networks
Proceedings of the 3rd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
The broadcast storm problem in a mobile ad hoc network
Wireless Networks - Selected Papers from Mobicom'99
Distributed localization in wireless sensor networks: a quantitative comparison
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Wireless sensor networks
Energy-efficient collision-free medium access control for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance
IEEE Transactions on Mobile Computing
Proceedings of the 6th ACM conference on Embedded network sensor systems
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
In-network aggregation techniques for wireless sensor networks: a survey
IEEE Wireless Communications
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This paper presents IRIS, an integrated interest dissemination and convergecasting solution for wireless sensor networks (WSNs). The interest dissemination protocol is used to build and maintain the network topology and for task/instruction assignment, while convergecasting implements data gathering at the network sink. Convergecasting heavily exploits cross-layering in that MAC and routing operation are performed jointly and relay selection is based on flexible cost functions that take into account information from different layers. The definition of the IRIS cost function enables tradeoff between key end-to-end performance metrics. In addition, it provides mechanisms for supporting efficient network behavior such as in-network data aggregation or processing. Energy usage is minimized by exploiting density estimation, sleeping modes and duty cycle control in a distributed and autonomous manner and as a function of the traffic intensity. Finally, IRIS is self adaptive, highly localized and imposes limited control overhead. IRIS performance is evaluated through ns2 simulations as well as through experiments on a WSN testbed. Comparative performance results show that IRIS outperforms previous cross-layer solutions. The flexibility introduced by the IRIS cross-layer approach results in higher robustness than that of well-known approaches such as BoX-MAC and CTP.