Network-level synchronization in decentralized social ad-hoc networks

Dobson, Matthew; Voulgaris, Spyros; Steen, Maarten van

doi:10.1109/icpca.2010.5704099

Cited by 5 publications

(6 citation statements)

References 11 publications

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“…Each individual wears a simulated device. We simulated the devices in accordance with the devices we used for our real world evaluation [12]. These nodes have an Atmel ATXMega128 CPU with 8k of RAM, 128k of Flash memory, and a Nordic nRF24L01+ wireless radio.…”

Section: A Methodologymentioning

confidence: 98%

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From proximity sensing to spatio-temporal social graphs

Martella

Dobson

Halteren

et al. 2014

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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Understanding the social dynamics of a group of people can give new insights into social behavior. Physical proximity between individuals results from the interactions between them. Hence, measuring physical proximity is an important step towards a better understanding of social behavior. We discuss a novel approach to sense proximity from within the social dynamics. Our primary objective is to construct a spatio-temporal social graph from noisy proximity data. We address the technical and algorithmic challenges of measuring proximity reliably and accurately. Simulations and real world experiments demonstrate the feasibility and scalability of our approach. Our algorithms doubles the sensitivity of proximity detections at the cost of a slight reduction in specificity.

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Section: A Methodologymentioning

confidence: 98%

“…However, our approach is applicable to other devices as well, such as mobile phones. We dealt with the challenges that belong to the technological level in [12], [13]. In this paper we focus mostly on those that belong to the processing level.…”

Section: A Challengesmentioning

confidence: 99%

From proximity sensing to spatio-temporal social graphs

Martella

Dobson

Halteren

et al. 2014

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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“…Conservation of the nodes' fixed energy budget is the chief concern in all design decisions, and necessitates that wireless communication is kept to a minimum. In ad hoc networks dynamic changes to network topology can wreak havoc on many algorithms (e.g., routing and leader election), which assume stable and symmetric connections between nodes [10]. Many important optimization problems can best be analyzed by means of a graphical network representation [29].…”

Section: Random Matrix Theorymentioning

confidence: 99%

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

et al. 2015

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Dynamic Spectrum Access (DSA) is widely seen as a solution to the problem of limited spectrum, because of its ability to adapt the operating frequency of a radio. Mobile Ad Hoc Networks (MANETs) can extend high-capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact, cognitive radio employs spectrum sensing to facilitate the identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, while secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate fair path use of the DSA-discovered links. Utilization of high-resolution geospatial data layers in RF propagation analysis is directly applicable. Random matrix theory (RMT) is useful in simulating network layer usage in nodes by a Wishart adjacency matrix. We use the Dijkstra algorithm for discovering ad hoc network node connection patterns. We present a method for analysts to dynamically allocate node-node path and link resources using fair division. User allocation of limited resources as a function of time must be dynamic and based on system fairness policies. The context of fair means that first available request for an asset is not envied as long as it is not yet allocated or tasked in order to prevent cycling of the system. This solution may also save money by offering a Pareto efficient repeatable process. We use a water fill queue algorithm to include Shapley value marginal contributions for allocation.

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“…In Dobson et al [2010], we showed that the median algorithm (Algorithm 1) is capable of maintaining tight synchronization within connected networks of static grids of nodes. The algorithm is quite simple, yet very efficient.…”

Section: Maintaining Synchronized Groupsmentioning

confidence: 99%

“…We have dealt with the first subproblem in Dobson et al [2010]. We have also partly explored the second problem in Dobson et al [2011], which we extend here to include an exploration of how node mobility affects synchronization while also considering much larger networks.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Network-Level Synchronization in Mobile Ad Hoc Networks

Voulgaris

Dobson

Steen

2016

ACM Trans. Sen. Netw.

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Energy is the scarcest resource in ad hoc wireless networks, particularly in wireless sensor networks requiring a long lifetime. Intermittently switching the radio on and off is widely adopted as the most effective way to keep energy consumption low. This, however, prevents the very goal of communication, unless nodes switch their radios on at synchronized intervals—a rather nontrivial coordination task. In this article, we address the problem of synchronizing node radios to a single universal schedule in wireless mobile ad hoc networks that can potentially consist of thousands of nodes. More specifically, we are interested in operating the network with duty cycles that can be less than 1% of the total cycle time. We identify the fundamental issues that govern cluster merging and provide a detailed comparison of various policies using extensive simulations based on a variety of mobility patterns. We propose a specific scheme that allows a 4,000-node network to stay synchronized with a duty cycle of approximately 0.7%. Our work is based on an existing, experimental MAC protocol that we use for real-world applications and is validated in a real network of around 120 mobile nodes.

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Network-level synchronization in decentralized social ad-hoc networks

Cited by 5 publications

References 11 publications

From proximity sensing to spatio-temporal social graphs

From proximity sensing to spatio-temporal social graphs

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

Decentralized Network-Level Synchronization in Mobile Ad Hoc Networks

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