Efficient Distributed Communication in Ad-Hoc Radio Networks

Principles of Distributed Systems, 2004

A radio network is a collection of transmitter-receiver devices (referred to as nodes). ARB (Acknowledged Radio Broadcasting) means transmitting a message from one special node called source to all the nodes and informing the source about its completion. In our model each node takes a synchronization per round and performs transmission or reception at one round. Each node does not have a collision detection capability and knows only own ID. In [1], it is proved that no ARB algorithm exists in the model without collision detection. In this paper, we show that if n ≥ 2, where n is the number of nodes in the network, we can construct algorithms which solve ARB in O(n) rounds for bidirectional graphs and in O(n 3/2) rounds for strongly connected graphs and solve ARG (Acknowledged Radio Gossiping) in O(n log 3 n) rounds for bidirectional graphs and in O(n 3/2) rounds for strongly connected graphs without collision detection.

2002

We consider the problem of distributed deterministic broadcasting in radio networks of unknown topology and size. The network is synchronous. If a node u can be reached from two nodes which send messages in the same round, none of the messages is received by u. Such messages block each other and node u either hears the noise of interference of messages, enabling it to detect a collision, or does not hear anything at all, depending on the model. We assume that nodes know neither the topology nor the size of the network, nor even their immediate neighborhood. The initial knowledge of every node is limited to its own label. Such networks are called ad hoc multi-hop networks. We study the time of deterministic broadcasting under this scenario.

Distributed Computing, 2005

We consider distributed broadcasting in radio networks, modeled as undirected graphs, whose nodes have no information on the topology of the network, nor even on their immediate neighborhood. For randomized broadcasting, we give an algorithm working in expected time O(D log(n/D)+log 2 n) in n-node radio networks of diameter D, which is optimal, as it matches the lower bounds of Alon et al. and Kushilevitz and Mansour . Our algorithm improves the best previously known randomized broadcasting algorithm of Bar-Yehuda, Goldreich and Itai [3], running in expected time O(D log n+log 2 n). For deterministic broadcasting, we show the lower bound Ω(n log n log(n/D) ) on broadcasting time in nnode radio networks of diameter D. This implies previously known lower bounds of Goldreich and Itai [3] and Bruschi and Del Pinto [5], and is sharper than any of them in many cases. We also give an algorithm working in time O(n log n), thus shrinking -for the first time -the gap between the upper and the lower bound on deterministic broadcasting time to a logarithmic factor.

Algorithmica, 2007

We study deterministic gossiping in ad hoc radio networks with large node labels. The labels (identifiers) of the nodes come from a domain of size N which may be much larger than the size n of the network (the number of nodes). Most of the work on deterministic communication has been done for the model with small labels which assumes N = O(n). A notable exception is Peleg's paper , where the problem of deterministic communication in ad hoc radio networks with large labels is raised and a deterministic broadcasting algorithm is proposed, which runs in O(n 2 log n) time for N polynomially large in n. The O(n log 2 n)-time deterministic broadcasting algorithm for networks with small labels given by Chrobak et al.

ee.ucl.ac.uk

Broadcasting is at the heart of many routing algorithms in mobile ad hoc networks (MANETs), and provides a simple yet effective method for one-to-many information dissemination in these networks. In this paper we describe a new algorithm for broadcasting in MANETs which is inspired, by the way rumours spread in social networks. We examine aspects of our algorithm through simulations.

2011

Abstract We investigate the randomness requirements of the classical rumor spreading problem on fully connected graphs with n vertices. In the standard random protocol, where each node that knows the rumor sends it to a randomly chosen neighbor in every round, each node needs O ((log n) 2) random bits in order to spread the rumor in O (log n) rounds with high probability (whp). For the simple quasirandom rumor spreading protocol proposed by Doerr, Friedrich, and Sauerwald (2008),��� log n��� random bits per node are sufficient.

Lecture Notes in Computer Science

We study oblivious deterministic gossip algorithms for multi-channel radio networks with a malicious adversary. In a multi-channel network, each of the n processes in the system must choose, in each round, one of the c channels of the system on which to participate. Assuming the adversary can disrupt one channel per round, preventing communication on that channel, we establish a tight bound of max " Θ " "" on the number of rounds needed to solve the -gossip problem, a parameterized generalization of the all-to-all gossip problem that requires (1 -)n of the "rumors" to be successfully disseminated. Underlying our lower bound proof lies an interesting connection between -gossip and extremal graph theory. Specifically, we make use of Turán's theorem, a seminal result in extremal combinatorics, to reason about an adversary's optimal strategy for disrupting an algorithm of a given duration. We then show how to generalize our upper bound to cope with an adversary that can simultaneously disrupt t < c channels. Our generalization makes use of selectors: a combinatorial tool that guarantees that any subset of processes will be "selected" by some set in the selector. We prove this generalized algorithm optimal if a maximum number of values is to be gossiped. We conclude by extending our algorithm to tolerate traditional Byzantine corruption faults.

2012

Gossiping is a well-studied problem in Radio Networks. However, due to the strong resource limitations of sensor nodes, previous solutions are frequently not feasible in Sensor Networks. In this paper, we study the Gossiping problem in the restrictive context of Sensor Networks. We present a distributed algorithm that completes Gossiping with high probability in a Sensor Network of unknown topology and adversarial start-up.

Proceedings 41st Annual Symposium on Foundations of Computer Science

We investigate the class of so-called epidemic algorithms that are commonly used for the lazy transmission of updates to distributed copies of a database. These algorithms use a simple randomized communication mechanism to ensure robustness. Suppose players communicate in parallel rounds in each of which every player calls a randomly selected communication partner. In every round, players can generate rumors (updates) that are to be distributed among all players. Whenever communication is established between two players, each one must decide which of the rumors to transmit. The major problem (arising due to the randomization) is that players might not know which rumors their partners have already received. For example, a standard algorithm forwarding each rumor from the calling to the called players for rounds needs to transmit the rumor times in order to ensure that every player finally receives the rumor with high probability. We investigate whether such a large communication overhead is inherent to epidemic algorithms. On the positive side, we show that the communication overhead can be reduced significantly. We give an algorithm using only transmissions and rounds. In addition, we prove the robustness of this algorithm, e.g., against adversarial failures. On the negative side, we show that any address-oblivious algorithm (i.e., an algorithm that does not use the addresses of communication partners) needs to send messages for each rumor regardless of the number of rounds. Furthermore, we give a general lower bound showing that time-and communicationoptimality cannot be achieved simultaneously using random phone calls

Random Structures and Algorithms, 1990

In this paper we study the rate at which a rumor spreads through an undirected graph. This study has two important applications in distributed computation: (1) in simple, robust and efficient broadcast protocols; (2) in the maintenance of replicated databases.