Conference Proceeding

A Near Optimal Localized Heuristic for Voice Multicasting over Ad Hoc Wireless Networks

Yahoo! Software Dev. India Pvt. Ltd., Bangalore
07/2007; DOI:10.1109/ICC.2007.276 In proceeding of: Communications, 2007. ICC '07. IEEE International Conference on
Source: IEEE Xplore

ABSTRACT Providing real-time voice multicasting over multi-hop ad hoc wireless networks is a challenging task. The unique characteristics of voice traffic (viz. small packet size, high packet rate, and soft real-time nature) make conventional multicasting protocols perform quite poorly, hence warranting application centric approaches in order to provide robustness against packet losses and lower the overhead due to high packet rate. In this paper, we first show that the optimal voice multicasting tree (OVMT) problem is NP-complete and then propose a localized distributed heuristic for minimum number of transmissions (LDMT). By incorporating LDMT in ADMR protocol, extensive simulations are done in NS-2 framework to measure the performance of LDMT for voice applications. We observed that LDMT reduces the redundant transmissions in transmitting voice packets from the source to all multicast receivers (thus reducing the overall voice traffic considerably), thereby making it suitable for voice multicasting in AWNs.

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    ABSTRACT: This paper presents a wireless multicast tree construction algorithm, SWIM (Source-initiated WIreless Multicast). SWIM forms one shared tree from source(s) to the multicast destinations; yet, as a side product it creates a multicast mesh structure by maintaining alternative branches at every tree node, thus providing robustness to link failures. This makes it suitable for both ad-hoc networks and access networks with multiple gateways. It is proved that SWIM is fully distributed, with a worst case complexity (for multicast) upper-bounded by O(N<sup>3</sup>), and average complexity of only O(N<sup>2</sup>). SWIM constructs a tree on which each multicast destination has the minimum possible depth (number of hops from the nearest source). In terms of minimizing the number of forwarding nodes (NFN), SWIM is optimal for unicast. Its average NFN in the broadcast and multicast cases is compared with practical algorithms targeting low NFN reported in the literature. In both multicast and unicast, SWIM performs competitively in terms of NFN with the previous solutions, while having smaller maximum depth, and consequently low delay.


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