9 research outputs found

    Chapter 12 Wireless Protocols

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    Wireless communication was one of the major success stories of the last decades. Today, different wireless standards such as wireless local area networks (WLAN) are omnipresent. In some sense, from a distributed computing viewpoint wireless networks are quite simple, as they cannot form arbitrary network topologies. Simplistic models of wireless networks include geometric graph models such as the so-called unit disk graph. Modern models are more robust: The network graph is restricted, e.g., the total number of neighbors of a node which are not adjacent is likely to be small. This observation is hard to capture with purely geometric models, and motivates more advanced network connectivity models such as bounded growth or bounded independence. However, on the other hand, wireless communication is also more difficult than standard message passing, as for instance nodes are not able to transmit a different message to each neighbor at the same time. And if two neighbors are transmitting at the same time, they interfere, and a node may not be able to decipher anything

    Distributed Deterministic Broadcasting in Uniform-Power Ad Hoc Wireless Networks

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    Development of many futuristic technologies, such as MANET, VANET, iThings, nano-devices, depend on efficient distributed communication protocols in multi-hop ad hoc networks. A vast majority of research in this area focus on design heuristic protocols, and analyze their performance by simulations on networks generated randomly or obtained in practical measurements of some (usually small-size) wireless networks. %some library. Moreover, they often assume access to truly random sources, which is often not reasonable in case of wireless devices. In this work we use a formal framework to study the problem of broadcasting and its time complexity in any two dimensional Euclidean wireless network with uniform transmission powers. For the analysis, we consider two popular models of ad hoc networks based on the Signal-to-Interference-and-Noise Ratio (SINR): one with opportunistic links, and the other with randomly disturbed SINR. In the former model, we show that one of our algorithms accomplishes broadcasting in O(Dlog2n)O(D\log^2 n) rounds, where nn is the number of nodes and DD is the diameter of the network. If nodes know a priori the granularity gg of the network, i.e., the inverse of the maximum transmission range over the minimum distance between any two stations, a modification of this algorithm accomplishes broadcasting in O(Dlogg)O(D\log g) rounds. Finally, we modify both algorithms to make them efficient in the latter model with randomly disturbed SINR, with only logarithmic growth of performance. Ours are the first provably efficient and well-scalable, under the two models, distributed deterministic solutions for the broadcast task.Comment: arXiv admin note: substantial text overlap with arXiv:1207.673

    Broadcasting in Noisy Radio Networks

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    The widely-studied radio network model [Chlamtac and Kutten, 1985] is a graph-based description that captures the inherent impact of collisions in wireless communication. In this model, the strong assumption is made that node vv receives a message from a neighbor if and only if exactly one of its neighbors broadcasts. We relax this assumption by introducing a new noisy radio network model in which random faults occur at senders or receivers. Specifically, for a constant noise parameter p[0,1)p \in [0,1), either every sender has probability pp of transmitting noise or every receiver of a single transmission in its neighborhood has probability pp of receiving noise. We first study single-message broadcast algorithms in noisy radio networks and show that the Decay algorithm [Bar-Yehuda et al., 1992] remains robust in the noisy model while the diameter-linear algorithm of Gasieniec et al., 2007 does not. We give a modified version of the algorithm of Gasieniec et al., 2007 that is robust to sender and receiver faults, and extend both this modified algorithm and the Decay algorithm to robust multi-message broadcast algorithms. We next investigate the extent to which (network) coding improves throughput in noisy radio networks. We address the previously perplexing result of Alon et al. 2014 that worst case coding throughput is no better than worst case routing throughput up to constants: we show that the worst case throughput performance of coding is, in fact, superior to that of routing -- by a Θ(log(n))\Theta(\log(n)) gap -- provided receiver faults are introduced. However, we show that any coding or routing scheme for the noiseless setting can be transformed to be robust to sender faults with only a constant throughput overhead. These transformations imply that the results of Alon et al., 2014 carry over to noisy radio networks with sender faults.Comment: Principles of Distributed Computing 201

    An Omega(D log(N/D)) Lower Bound for Broadcast in Radio Networks

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    We show that for any randomized broadcast protocol for radio networks, there exists a network in which the expected time to broadcast a message is \Omega\Gamma D log(N=D)), where D is the diameter of the network and N is the number of nodes. This implies a tight lower bound of \Omega\Gamma D log N) for any D N 1\Gamma" , where " ? 0 is any constant. 1 Introduction Traditionally, radio networks received a considerable attention due to their military significance. The growing interest in cellular telephones and wireless communication networks has reinforced the interest in radio networks. The basic feature of radio networks, that distinguishes them from other networks, is that a processor can receive a message only from a single neighbor at a certain time. If two (or more) neighbors of a processor transmit concurrently, then the processor would not receive either messages. In many applications, the users of the radio network are mobile, and therefore the topology is unstable. For th..

    Consensus and collision detectors in wireless ad hoc networks

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 76-80).In this study, we consider the fault-tolerant consensus problem in wireless ad hoc networks with crashprone nodes. Specifically, we develop lower bounds and matching upper bounds for this problem in single-hop wireless networks, where all nodes are located within broadcast range of each other. In a novel break from existing work, we introduce a highly unpredictable communication model in which each node may lose an arbitrary subset of the messages sent by its neighbors during each round. We argue that this model better matches behavior observed in empirical studies of these networks. To cope with this communication unreliability we augment nodes with receiver-side collision detectors and present a new classification of these detectors in terms of accuracy and completeness. This classification is motivated by practical realities and allows us to determine, roughly speaking, how much collision detection capability is enough to solve the consensus problem efficiently in this setting. We consider ten different combinations of completeness and accuracy properties in total, determining for each whether consensus is solvable, and, if it is, a lower bound on the number of rounds required.(cont.) Furthermore, we distinguish anonymous and non-anonymous protocols-where "anonymous" implies that devices do not have unique identifiers-determining what effect (if any) this extra information has on the complexity of the problem. In all relevant cases, we provide matching upper bounds. Our contention is that the introduction of (possibly weak) receiver-side collision detection is an important approach to reliably solving problems in unreliable networks. Our results, derived in a realistic network model, provide important feedback to ad hoc network practitioners regarding what hardware (and low-layer software) collision detection capability is sufficient to facilitate the construction of reliable and fault-tolerant agreement protocols for use in real-world deployments.by Calvin Newport.S.M
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