Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
An efficient routing protocol for wireless networks
Mobile Networks and Applications - Special issue: routing in mobile communications networks
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
Reactive routing overhead in networks with unreliable nodes
Proceedings of the 9th annual international conference on Mobile computing and networking
Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
ExOR: opportunistic multi-hop routing for wireless networks
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
FansyRoute: adaptive fan-out for variably intermittent challenged networks
ACM SIGMOBILE Mobile Computing and Communications Review
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We study a routing problem in wireless sensor networks where sensors are duty-cycled. When sensors alternate between on and off modes, delay encountered in packet delivery due to loss in connectivity can become a critical problem, and how to achieve delay-optimality is non-trivial. For instance, when sensors' sleep schedules are uncoordinated, it is not immediately clear whether a sensor with data to transmit should wait for a particular neighbor (who may be on a short route) to become available/active before transmission, or simply transmit to an available/active neighbor to avoid waiting. To obtain some insight into this problem, in this paper we formulate the above problem as an optimal stochastic routing problem, where the randomness in the system comes from random duty cycling, as well as the uncertainty in packet transmission due to channel variations. Similar framework has been used in prior work which results in optimal routing algorithms that are sample-path dependent, also referred to as opportunistic in some cases. We show such algorithms are no longer optimal when duty cycling is introduced. We first develop and analyze an optimal centralized stochastic routing algorithm for randomly duty-cycled wireless sensor network, and then simplify the algorithm when local sleep/wake states of neighbors are available. We further develop a distributed algorithm utilizing local sleep/wake states of neighbors which performs better than some existing distributed algorithms such as ExOR.