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forwarding node set, the latency of the NWB is increased, because a node must wait for a series of HELLO messages to be sent.
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3.5 CHARACTERIZING NWB UNRELIABILITY In this section, the effect of the MAC broadcast unreliability on the performance of NWB algorithms is characterized to demonstrate their lack of robustness. NWB coverage is affected primarily by two factors: the redundancy of the NWB operation and the probability of MAC transmission loss. A dense network allows some NWB algorithms to use redundant paths providing loss-tolerance without losing coverage. This available redundancy is lower in sparse networks, or for algorithms that control redundancy to improve overhead, making NWBs less robust under such conditions. 3.5.1 Preliminaries and Experimental Setup The primary performance metrics of interest are: (1) node coverage: percentage of nodes that receive the NWB; and (2) overhead: number of retransmissions. Raw overhead is dif cult to interpret independently of the network size and the coverage success. Therefore, normalized overhead, de ned as the number of retransmissions per receiving node, was tracked. For ooding, normalized overhead is always of interest regardless of the topology or the coverage success: every receiving node retransmits the packet once. Optimized NWBs target lowering the overhead while maintaining coverage that should result in a normalized overhead smaller than 1. To simulate losses in the network, two approaches are used. First, packets are probabilistically dropped at receiving nodes; a similar approach to modeling losses was used in other works [26]. While this approach is somewhat unrepresentative (transmission errors are typically not uniform across all links), it provides a controllable approach to varying the loss rate. The second approach involves introducing fading to the network. Fading models allow for more realistic transmission behavior, but vary depending on the distance between nodes. As a result, the best way to judge the effect of fading is by comparing NWB behavior in networks of different densities. Previous work has been done using constant bit rate (CBR) traf c ows in order to increase the level of contention present in the network. These ows often interfere with each other, preventing a consistent level of contention in the network. As a result, data gathered from these studies are not as controlled the data presented below. We evaluated the algorithms described in Section 3.43 . All experiments in this paper use the Network Simulator NS-2 [27]. NS-2 is a discrete event simulator with detailed models for the network protocol stack, including the IEEE 802.11 MAC protocol. NS-2 includes simpli ed models for wireless propagation. In all scenarios, nodes are randomly deployed with a uniform distribution in a xed area of 1000 by
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authors wish to thank Tracy Camp s group at Colorado Mines for the supplying the code for LBA, SBA, and AHBP. We also wish to thank W. Lou for the NS-2 implementation of DCB.
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1000 m. The 802.11 MAC implementation in NS-2 was used for experimentation with the default parameters (range of 250 m). In each experiment, one NWB is generated per node. The NWBs are timed to ensure that successive operations do not interfere. Each data point represents an average of 20 scenarios with different random seeds. While the con dence intervals are not presented in the graphs to avoid clutter, they were tracked; the average is narrowly bound (95% con dence intervals within 1% of the mean). 3.5.2 Grid Topologies Grid topologies consist of nodes that are evenly deployed in a two-dimensional grid throughout the simulation area. This con guration may be representative of static preplanned networks such as mesh network [28]. Grids also provide a level of control to experiments, due to the uniform density present throughout the network. The coverage of ooding for different density grids inside of a 1000-m by 1000-m area were studied. Figure 3.4 plots the coverage achieved by ooding in different densities, using the controlled drop mechanism described earlier. As expected, grids that are more dense achieve a higher level of coverage. This is because denser grids provide more redundancy for the ood. In a sparse grid, the loss of a few packets can result in loss of coverage to signi cant portions of the network. 3.5.3 Random Topologies This section describes studies done with nodes that are randomly deployed in a 1000-m by 1000-m area.
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