Panda: Neighbor discovery on a power harvesting budget
| Autor: | Guy Grebla, Robert Margolies, Dan Rubenstein, Tingjun Chen, Gil Zussman |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
FOS: Computer and information sciences
Computer Networks and Communications Computer science computer.internet_protocol 02 engineering and technology 01 natural sciences Power budget Neighbor Discovery Protocol Computer Science - Networking and Internet Architecture 0202 electrical engineering electronic engineering information engineering Wireless Electrical and Electronic Engineering Networking and Internet Architecture (cs.NI) business.industry 010401 analytical chemistry Testbed 020206 networking & telecommunications 0104 chemical sciences Transmission (telecommunications) 020201 artificial intelligence & image processing business Energy harvesting computer Wireless sensor network Efficient energy use Computer network |
| Zdroj: | INFOCOM |
| DOI: | 10.1109/infocom.2016.7524505 |
| Popis: | Object tracking applications are gaining popularity and will soon utilize energy harvesting (EH) low-power nodes that will consume power mostly for neighbor discovery (ND) (i.e., identifying nodes within communication range). Although ND protocols were developed for sensor networks, the challenges posed by emerging EH low-power transceivers were not addressed . Therefore, we design an ND protocol tailored for the characteristics of a representative EH prototype : the TI eZ430-RF2500-SEH. We present a generalized model of ND accounting for unique prototype characteristics (i.e., energy costs for transmission/reception, and transceiver state switching times/costs). Then, we present the Power Aware ND Asynchronously (Panda) protocol, in which nodes transition between the sleep, receive, and transmit states. We analyze Panda and select its parameters to maximize the ND rate subject to a homogeneous power budget. We also present Panda-D, designed for non-homogeneous EH nodes. We perform extensive testbed evaluations using the prototypes and study various design tradeoffs. We demonstrate a small difference (less than 2%) between experimental and analytical results, thereby confirming the modeling assumptions. Moreover, we show that Panda improves the ND rate by up to $3\times $ compared with related protocols. Finally, we show that Panda-D operates well under non-homogeneous power harvesting. |
| Databáze: | OpenAIRE |
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