Geografia e Inovação

Rodríguez, Felipe Forero

doi:10.47749/t/unicamp.2019.1126379

Cited by 4 publications

(3 citation statements)

References 110 publications

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“…Probabilistic forwarding as a broadcast mechanism (see e.g., [4], [5], [6]) has been proposed in the literature as an alternative to flooding. Here, each node, on receiving a packet for the first time, either forwards it to all its onehop neighbours with probability p or takes no action with probability 1 − p. While this mechanism reduces the number of transmissions, reception of a packet by a network node is not guaranteed.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

B.¹,

Kashyap²,

Yogeshwaran

2022

SSRN Journal

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Section: Introductionmentioning

confidence: 99%

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

B.¹,

Kashyap²,

Yogeshwaran

2022

SSRN Journal

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Section: Introductionmentioning

confidence: 99%

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

Kumar

Kashyap

Yogeshwaran

2021

2021 19th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

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We consider the problem of energy-efficient broadcasting on dense ad-hoc networks. Ad-hoc networks are generally modeled using random geometric graphs (RGGs). Here, nodes are deployed uniformly in a square area around the origin, and any two nodes which are within Euclidean distance of 1 are assumed to be able to receive each other's broadcast. A source node at the origin encodes k data packets of information into n (> k) coded packets and transmits them to all its one-hop neighbors. The encoding is such that, any node that receives at least k out of the n coded packets can retrieve the original k data packets. Every other node in the network follows a probabilistic forwarding protocol; upon reception of a previously unreceived packet, the node forwards it with probability p and does nothing with probability 1 − p. We are interested in the minimum forwarding probability which ensures that a large fraction of nodes can decode the information from the source. We deem this a near-broadcast. The performance metric of interest is the expected total number of transmissions at this minimum forwarding probability, where the expectation is over both the forwarding protocol as well as the realization of the RGG. In comparison to probabilistic forwarding with no coding, our treatment of the problem indicates that, with a judicious choice of n, it is possible to reduce the expected total number of transmissions while ensuring a near-broadcast.

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“…Probabilistic forwarding as a broadcast mechanism (see e.g., [7], [8], [9]) has been proposed in the literature as an alternative to flooding. Here, each node, on receiving a packet for the first time, either forwards it to all its onehop neighbours with probability p or takes no action with probability 1 − p. While this mechanism reduces the number of transmissions, reception of a packet by a network node is not guaranteed.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Forwarding of Coded Packets on Networks

Kumar

Kashyap

2019

2019 IEEE International Symposium on Information Theory (ISIT)

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We consider a scenario of broadcasting information over a network of nodes connected by noiseless communication links. A source node in the network has some data packets to broadcast. It encodes these data packets into n coded packets in such a way that any node in the network that receives any k out of the n coded packets will be able to retrieve all the original data packets. The source transmits the n coded packets to its one-hop neighbours. Every other node in the network follows a probabilistic forwarding protocol, in which it forwards a previously unreceived packet to all its neighbours with a certain probability p. We say that the information from the source undergoes a "near-broadcast" if the expected fraction of nodes that receive at least k of the n coded packets is close to 1. The forwarding probability p is chosen so as to minimize the expected total number of transmissions needed for a near-broadcast. We study how, for a given k, this minimum forwarding probability and the associated expected total number of packet transmissions varies with n. We specifically analyze the probabilistic forwarding of coded packets on two network topologies: binary trees and square grids. For trees, our analysis shows that for fixed k, the expected total number of transmissions increases with n. On the other hand, on grids, a judicious choice of n significantly reduces the expected total number of transmissions needed for a near-broadcast. Behaviour similar to that of the grid is also observed in other well-connected network topologies such as random geometric graphs and random regular graphs. I. MOTIVATION AND RELATED WORKAn ad-hoc network is a network of nodes which communicate with each other without relying on any centralized infrastructure. A classical example of ad-hoc networks is wireless sensor networks (WSNs) which have sensors measuring temperature, humidity etc. connected with each other. The Internet of Things (IoT) network, which involves different types of physical devices -sensors, actuators, routers, mobiles etc.communicating with each other over a network can be thought of as an ad-hoc network.Broadcast mechanisms on such distributed networks are crucial in order to disburse key network-related information throughout the network. In the applications mentioned above, updation of sensing parameters in WSNs or over-the-air programming of the IoT nodes are done typically through a broadcast mechanism. These broadcasts are usually initiated from a single node in the network which is easily accessible (a mobile phone, say). In this paper, we will assume that there is a source node, s, which has k s packets of information which need to be broadcast in the network. A natural broadcast This work was presented in part at the 2019 IEEE International Symposium on Information Theory (ISIT 2019) held in Paris, France.The authors are with the algorithm is flooding, wherein a node forwards every newly received packet to all its one-hop neighbours. If there are N nodes in the network, then the total number of transmissi...

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Geografia e Inovação

Cited by 4 publications

References 110 publications

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

Probabilistic Forwarding of Coded Packets on Networks

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