Neighbor discovery is a fundamental service for initialization and managing network dynamics in wireless sensor networks and mobile sensing applications. In this paper, we present a novel design principle named Talk More Listen Less (TMLL) to reduce idle-listening in neighbor discovery protocols by learning the fact that more beacons lead to fewer wakeups. We propose an extended neighbor discovery model for analyzing wakeup schedules in which beacons are not necessarily placed in the wakeup slots. Furthermore, we are the first to consider channel occupancy rate in discovery protocols by introducing a new metric to trade off among duty-cycle, latency and channel occupancy rate. Guided by the TMLL principle, we have designed Nihao, a family of energy-efficient asynchronous neighbor discovery protocols for symmetric and asymmetric cases. We compared Nihao with existing state of the art protocols via analysis and real-world testbed experiments. The result shows that Nihao significantly outperforms the others both in theory and practice.
U-Connect @cite_17 presents a better wakeup schedule than Quorum with fewer active slots. By providing a Listen-Listen model of the asynchronous neighbor discovery problem, U-Connect proves that it is 1.5-approximation to the optimal using the power-latency product metric. We have used similar notations with U-Connect to formalize performance metrics and extend the Listen-Listen model to better analyze the wakeup schedules that beacons are not inside the wakeup slots.
@cite_17
2168924024
Mobile sensor nodes can be used for a wide variety of applications such as social networks and location tracking. An important requirement for all such applications is that the mobile nodes need to actively discover their neighbors with minimal energy and latency. Nodes in mobile networks are not necessarily synchronized with each other, making the neighbor discovery problem all the more challenging. In this paper, we propose a neighbor discovery protocol called U-Connect, which achieves neighbor discovery at minimal and predictable energy costs while allowing nodes to pick dissimilar duty-cycles. We provide a theoretical formulation of this asynchronous neighbor discovery problem, and evaluate it using the power-latency product metric. We analytically establish that U-Connect is an 1.5-approximation algorithm for the symmetric asynchronous neighbor discovery problem, whereas existing protocols like Quorum and Disco are 2-approximation algorithms. We evaluate the performance of U-Connect and compare the performance of U-Connect with that of existing neighbor discovery protocols. We have implemented U-Connect on our custom portable FireFly Badge hardware platform. A key aspect of our implementation is that it uses a slot duration of only 250μs, and achieves orders of magnitude lower latency for a given duty cycle compared to existing schemes for wireless sensor networks. We provide experimental results from our implementation on a network of around 20 sensor nodes. Finally, we also describe a Friend-Finder application that uses the neighbor discovery service provided by U-Connect.