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Pickup game: Acquainting neighbors quickly and efficiently
- in crowd,” in IEEE MASS
, 2014
"... Abstract—Effective and energy efficient neighbor discovery protocol is a crucial component for the success of emerging opportunistic encounter-based mobile (ad hoc) networking for social and gaming. In this work, we design P-Game, an effective neighbor discovery protocol to find a group of neighbors ..."
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Abstract—Effective and energy efficient neighbor discovery protocol is a crucial component for the success of emerging opportunistic encounter-based mobile (ad hoc) networking for social and gaming. In this work, we design P-Game, an effective neighbor discovery protocol to find a group of neighbors. By leveraging a quick estimation of the number of neighbors, we design various protocols for collecting the IDs of these neighboring nodes with the objective of either minimizing the latency of neighbor-discovery process or minimizing the active slots (i.e. energy consumption) of each neighbor. We validate PickupGame through rigorous theoretical analysis. When the required acquaintances k is a constant fraction of neighbors, our protocol is proved to have optimum delay Θ(k) and optimum active slots Θ(1). When we need to find all neighbors, our protocols achieve tradeoffs in the delay and active slots: one approach has discovery latency O(k ln ln k) and active slots O(ln ln k). Our evaluations corroborate our theoretical results and show considerable improvement in discovery latency over existing approaches in almost all cases. I.
Lightweight Neighborhood Cardinality Estimation in Dynamic Wireless Networks
"... Abstract—We address the problem of estimating the neighborhood cardinality of nodes in dynamic wireless networks. Different from previous studies, we consider networks with high densities (a hundred neighbors per node) and where all nodes estimate cardinality concurrently. Performing concurrent esti ..."
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Abstract—We address the problem of estimating the neighborhood cardinality of nodes in dynamic wireless networks. Different from previous studies, we consider networks with high densities (a hundred neighbors per node) and where all nodes estimate cardinality concurrently. Performing concurrent estimations on dense mobile networks is hard; we need estimators that are not only accurate, but also fast, asynchronous (due to mobility) and lightweight (due to concurrency and high density). To cope with these requirements, we propose Estreme, a neighborhood cardinality estimator with extremely low overhead that leverages the rendezvous time of low-power medium access control (MAC) protocols. We implemented Estreme on the Contiki OS and show a significant improvement over the state-of-the-art. With Estreme, 100 nodes can concurrently estimate their neighborhood cardinality with an error of ≈10%. State-of-the-art solutions provide a similar accuracy, but on networks consisting of a few tens of nodes and where only a fraction of nodes estimate the cardinality concurrently.
Privacy-aware High-quality Map Generation with Participatory Sensing
"... Abstract—Accurate maps are increasingly important with the growth of smart phones and the development of location-based services. Several crowdsourcing based map generation protocols that rely on users to provide their traces have been proposed. Being creative, however, those methods pose a signific ..."
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Abstract—Accurate maps are increasingly important with the growth of smart phones and the development of location-based services. Several crowdsourcing based map generation protocols that rely on users to provide their traces have been proposed. Being creative, however, those methods pose a significant threat to user privacy as the traces can easily imply user behavior patterns. On the flip side, crowdsourcing-based map generation method does need individual locations. To address the issue, we present a systematic participatory-sensing-based high-quality map generation scheme, PMG, that meets the privacy demand of individual users. To be specific, the individual users merely need to upload unorganized sparse location points to reduce the risk of exposing users ’ traces and utilize the Crust, a technique from computational geometry for curve reconstruction, to estimate the unobserved map as well as evaluate the degree of privacy leakage. Experiments show that our solution is able to generate high-quality maps for a real environment that is robust to noisy data. The difference between the ground-truth map and the produced map is less than 10m, even when the collected locations are about 32m apart after clustering for the purpose of removing noise. Index Terms—privacy protection, map generation, curve reconstruction, data suppression, participatory sensing F 1
On Heterogeneous Neighbor Discovery in Wireless Sensor Networks
"... Abstract—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 ..."
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Abstract—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 opti-mize 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. Index Terms—Neighbor discovery, heterogeneous duty cycles. I.
1On Heterogeneous Neighbor Discovery in Wireless Sensor Networks
"... Abstract—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 ..."
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Abstract—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 opti-mize 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. Index Terms—Neighbor discovery, heterogeneous duty cycles. I.
Ambient Rendezvous: Energy-Efficient Neighbor Discovery via Acoustic Sensing
"... Abstract—The continual proliferation of mobile devices has stimulated the development of opportunistic encounter-based networking and has spurred a myriad of proximity-based mobile applications. A primary cornerstone of such applications is to discover neighboring devices effectively and efficiently ..."
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Abstract—The continual proliferation of mobile devices has stimulated the development of opportunistic encounter-based networking and has spurred a myriad of proximity-based mobile applications. A primary cornerstone of such applications is to discover neighboring devices effectively and efficiently. De-spite extensive protocol optimization, current neighbor discovery modalities mainly rely on radio interfaces, whose energy and wake up delay required to initiate, configure and operate these protocols hamper practical applicability. Unlike conventional schemes that actively emit radio tones, we exploit ubiquitous audio events to discover neighbors passively. The rationale is that spatially adjacent neighbors tend to share similar ambient acoustic environments. We propose AIR, an effective and efficient neighbor discovery protocol via low power acoustic sensing to reduce discovery latency. Especially, AIR substantially increases the discovery probability of the first time they turn the radio on. Compared with the state-of-the-art neighbor discovery protocol, AIR significantly decreases the average discovery latency by around 70%, which is promising for supporting vast proximity-based mobile applications. I.
