Topic

# Flooding algorithm

About: Flooding algorithm is a research topic. Over the lifetime, 244 publications have been published within this topic receiving 2997 citations.

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20 Mar 2003TL;DR: By considering ideal and realistic models, a better understanding is acquired of the factors that determine phase transition, the consequences of the passage to realistic MANET conditions and to what extent the authors may benefit from probabilistic flooding in real MANET networks are acquired.

Abstract: Although far from the optimal, flooding is an indispensable message dissemination technique for network-wide broadcast within mobile ad hoc networks (MANETs). As such, the plain flooding algorithm provokes a high number of unnecessary packet rebroadcasts, causing contention, packet collisions and ultimately wasting precious limited bandwidth. We explore the phase transition phenomenon observed in percolation theory and random graphs as a basis for defining probabilistic flooding algorithm. By considering ideal and realistic models, we acquire a better understanding of the factors that determine phase transition, the consequences of the passage to realistic MANET conditions and to what extent we may benefit from probabilistic flooding in real MANET networks.

524 citations

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TL;DR: Three geocasting protocols for ad hoc networks are proposed, obtained as variations of a multicast flooding algorithm, and three algorithms attempt to utilize physical location information to decrease the overhead of geocast delivery.

Abstract: Geocasting is a variation on the notion of multicasting. A geographical area is associated with each geocast, and the geocast is delivered to the nodes within the specified geographical area. Thus, geocasting may be used for sending a message that is likely to be of interest to everyone in a specified area. In this paper, we propose three geocasting protocols for ad hoc networks, obtained as variations of a multicast flooding algorithm, and then evaluate these approaches by means of simulations. Proposed geocasting algorithms attempt to utilize physical location information to decrease the overhead of geocast delivery.

221 citations

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TL;DR: In this paper, the authors propose a set of alternative algorithms for publish-subscribe systems by using a smaller set of overbroad multicast groups, judiciously chosen to minimize imprecision, issuing multiple multicasts to appropriately chosen clusters, or sending an event over multiple hops each involving a multicast to neighbors.

Abstract: Publish-subscribe systems are evolving toward using content-based subscription rather than subject-based subscription. A key problem in implementing such systems is that a straightforward mapping from matching sets to multicast groups produces a number of groups that rapidly grows beyond practical limits. This paper proposes a set of alternative algorithms for solving this problem, by: (1) using a smaller set of overbroad multicast groups, judiciously chosen to minimize imprecision; (2) issuing multiple multicasts to appropriately chosen clusters; or (3) sending an event over multiple hops each involving a multicast to a set of neighbors. We evaluate these algorithms on a simulated wide-area network. We find that (1) a simple flooding algorithm is viable over an extensive range of conditions; and (2) under conditions of high selectivity and high regionalism of subscriptions, the other approaches mentioned above perform significantly better; however, the specific algorithm to use depends upon the economics of deployment.

196 citations

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Hitachi

^{1}TL;DR: This paper shows the performance improvements obtained by adding more special characteristics to the existing version of MHVB by changing the shape of the backfire region in the algorithm and introducing a new Dynamic Scheduling algorithm which prioritizes the packet transmission based upon "processing" of the received packets from the other vehicles.

Abstract: This paper, focuses on the "enhancement" of multi- hop vehicular broadcast (MHVB). The protocol is fundamentally a flooding algorithm with special characteristics in order to efficiently disseminate information such as the positions and the velocities of the vehicles for the sake of active safety applications. The main purpose of this paper is to show the performance improvements obtained by adding more special characteristics to the existing version of MHVB. The enhancement procedure is carried out in two steps: by changing the shape of the backfire region in the algorithm and by introducing a new Dynamic Scheduling algorithm which prioritizes the packet transmission based upon "processing" of the received packets from the other vehicles. The key point in the proposal made to enhance the broadcast protocol is the balance between the application requirement and the performance of the protocol.

103 citations

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TL;DR: An efficient flooding algorithm is proposed that achieves the local optimality in two senses: 1) the number of forwarding nodes in each step is minimal and 2) the time complexity for computing forwarding nodes is the lowest, which is O(nlogn), where n is thenumber of neighbors of a node.

Abstract: Flooding is one of the most fundamental operations in mobile ad hoc networks. Traditional implementation of flooding suffers from the problems of excessive redundancy of messages, resource contention, and signal collision. This causes high protocol overhead and interference with the existing traffic in the networks. Some efficient flooding algorithms were proposed to avoid these problems. However, these algorithms either perform poorly in reducing redundant transmissions or require each node to maintain 2-hop (or more) neighbors information. In the paper, we study the sufficient and necessary condition of 100 percent deliverability for flooding schemes that are based on only 1-hop neighbors information. We further propose an efficient flooding algorithm that achieves the local optimality in two senses: 1) the number of forwarding nodes in each step is minimal and 2) the time complexity for computing forwarding nodes is the lowest, which is O(nlogn), where n is the number of neighbors of a node. Extensive simulations have been conducted and simulation results have shown the excellent performance of our algorithm

89 citations