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 1524689014 2101044606 2116345518
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. Neighbor discovery plays a crucial role in the formation of wireless sensor networks and mobile networks where the power of sensors (or mobile devices) is constrained. Due to the difficulty of clock synchronization, many asynchronous protocols based on wake-up scheduling have been developed over the years in order to enable timely neighbor discovery between neighboring sensors while saving energy. However, existing protocols are not fine-grained enough to support all heterogeneous battery duty cycles, which can lead to a more rapid deterioration of long-term battery health for those without support. Existing research can be broadly divided into two categories according to their neighbor-discovery techniques — the quorum based protocols and the co-primality based protocols. In this paper, we propose two neighbor discovery protocols, called Hedis and Todis, that optimize the duty cycle granularity of quorum and co-primality based protocols respectively, by enabling the finest-grained control of heterogeneous duty cycles. We compare the two optimal protocols via analytical and simulation results, which show that although the optimal co-primality based protocol (Todis) is simpler in its design, the optimal quorum based protocol (Hedis) has a better performance since it has a lower relative error rate and smaller discovery delay, while still allowing the sensor nodes to wake up at a more infrequent rate. We present Disco, an asynchronous neighbor discovery and rendezvous protocol that allows two or more nodes to operate their radios at low duty cycles (e.g. 1 ) and yet still discover and communicate with one another during infrequent, opportunistic encounters without requiring any prior synchronization information. The key challenge is to operate the radio at a low duty cycle but still ensure that discovery is fast, reliable, and predictable over a range of operating conditions. Disco nodes pick a pair of prime numbers such that the sum of their reciprocals is equal to the desired radio duty cycle. Each node increments a local counter with a globallyfixed period. If a node's local counter value is divisible by either of its primes, then the node turns on its radio for one period. This protocol ensures that two nodes will have some overlapping radio on-time within a bounded number of periods, even if nodes independently set their own duty cycle. Once a neighbor is discovered, and its wakeup schedule known, rendezvous is just a matter of being awake during the neighbor's next wakeup period,for synchronous rendezvous, or during an overlapping wake period, for asynchronous rendezvous. The rapid deployment of millions of mobile sensors and smartphones has resulted in a demand for opportunistic encounter-based networking to support mobile social networking applications and proximity-based gaming. However, the success of these emerging networks is limited by the lack of effective and energy efficient neighbor discovery protocols. While probabilistic approaches perform well for the average case, they exhibit long tails resulting in high upper bounds on neighbor discovery time. Recent deterministic protocols, which allow nodes to wake up at specific timeslots according to a particular pattern, improve on the worst case bound, but do so by sacrificing average case performance. In response to these limitations, we have designed Searchlight, a highly effective asynchronous discovery protocol that is built on three basic ideas. First, it leverages the constant offset between periodic awake slots to design a simple probing-based approach to ensure discovery. Second, it allows awake slots to cover larger sections of time, which ultimately reduces total awake time drastically. Finally, Searchlight has the option to employ probabilistic techniques with its deterministic approach that can considerably improve its performance in the average case when all nodes have the same duty cycle. We validate Searchlight through analysis and real-world experiments on smartphones that show considerable improvement (up to 50 ) in worst-case discovery latency over existing approaches in almost all cases, irrespective of duty cycle symmetry.