Browsing by Subject "Network condition"

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Open Access
A performance comparison of zone-based multicast protocols for mobile ad hoc networks
(IEEE, 2003) Zhang, Y.; Rangnekar, A.; Selçuk, Ali A.; Bicak, A.; Sidhu, D.
With the current trend toward ubiquitous computing come wireless devices capable of forming the nodes of mobile ad hoc networks. Such networks typically rely on routing protocols in order to communicate messages from a source node to a destination node through a set of intermediary nodes. In a typical ad hoc environment, mobile nodes mostly work as a group and are involved in collaborative computing. Multicast communication is more effective in these scenarios. This paper presents the comparison of the performance of two zone-based multicast routing protocols. Shared-tree MZR is a shared tree variant of the Multicast Routing Protocol based on Zone Routing (MZR). We compare the two variants and analyze their performance under various network conditions. The test results show that Shared-tree MZR protocol performs well and has significantly low overhead in scenarios with multiple sources. ©2003 IEEE.
Open Access
Shifting network tomography toward a practical goal
(ACM, 2011) Ghita, D.; Karakuş, Can; Argyraki, K.; Thiran, P.
Boolean Inference makes it possible to observe the congestion status of end-to-end paths and infer, from that, the congestion status of individual network links. In principle, this can be a powerful monitoring tool, in scenarios where we want to monitor a network without having direct access to its links. We consider one such real scenario: a Tier-1 ISP operator wants to monitor the congestion status of its peers. We show that, in this scenario, Boolean Inference cannot be solved with enough accuracy to be useful; we do not attribute this to the limitations of particular algorithms, but to the fundamental difficulty of the Inference problem. Instead, we argue that the "right" problem to solve, in this context, is compute the probability that each set of links is congested (as opposed to try to infer which particular links were congested when). Even though solving this problem yields less information than provided by Boolean Inference, we show that this information is more useful in practice, because it can be obtained accurately under weaker assumptions than typically required by Inference algorithms and more challenging network conditions (link correlations, non-stationary network dynamics, sparse topologies).