E-ODMRP: Enhanced ODMRP with motion adaptive refresh

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Abstract

On-Demand Multicast Routing Protocol (ODMRP) is a multicast routing protocol for mobile ad hoc networks. Its efficiency, simplicity, and robustness to mobility render it one of the most widely used MANET multicast protocols. At the heart of the ODMRP’s robustness is the periodic route refreshing. ODMRP rebuilds the data forwarding “mesh” on a fixed interval and thus the route refresh interval is a key parameter that has critical impact on the network performance. If the route refresh rate is too high, the network will undergo too much routing overhead, wasting valuable resources. If it is too low, ODMRP cannot keep up with network dynamics, resulting in packet losses due to route breakages. In this paper, we present an enhancement of ODMRP with the refresh rate dynamically adapted to the environment. Simulation results show that the Enhanced ODMRP (E-ODMRP) reduces the packet overhead by up to a half yet keeping a packet delivery ratio comparable to that of the original ODMRP. E-ODMRP compares favorably with other published multicast schemes.

Introduction

A mobile ad hoc network (MANET) is a self-organized and dynamically reconfigurable wireless network without central administration and wired infrastructure. Nodes in the MANET can instantly establish a communication structure while each node moves in an arbitrary manner. Thus MANET is useful for people working in groups to achieve the given task where preexisting infrastructure cannot be accessed or no infrastructure is installed. Accordingly, applications in this environment such as group conferencing, data dissemination, disaster relief and battlefield require multicast routing. Developing a multicast routing protocol for MANET, however, is a different challenge than for wired networks due to characteristics of MANET such as usages of wireless broadcast medium, dynamic topology, limited bandwidth, high packet error rate, etc.

Many MANET multicast routing protocols have been proposed in the literature (e.g., [1], [2], [4], [5], [7], [8], [9], [10], [11], [12], [13], [14], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [29]) and several of them operate in an on-demand fashion [1], [2], [8], [9], [10], [11], [12], [13], [19], [27] in which routing information is exchanged only when it is needed. In general, on-demand routing protocols employ two-way handshaking to find a path for a sender/receiver pair. The sender floods the network with a Route Request packet and the receivers respond with Route Replys. To limit the scope (and overhead) of flooding, the local recovery approach is introduced. Namely, an alternative route to the destination is searched locally upon detection of the disconnection. Adaptive Demand-Driven Multicast Routing (ADMR) [9] and Multicast Ad hoc On-demand Distance Vector protocol (MAODV) [19] are two examples of an on-demand multicast protocol following this approach. They first build a multicast tree between a source and receivers and on detection of a broken link try to repair the route locally. Another popular on-demand multicast routing protocol, On-Demand Multicast Routing Protocol (ODMRP) [11] relies instead on periodic network-wide flooding for route discovery and maintenance. This design is intended to ensure robustness against mobility and unreliable wireless link propagation.

ODMRP periodically reconstructs the “Forwarding mesh” on a fixed short interval. Thus the route refresh interval is one of the most important performance parameters since it has critical impact on the protocol overhead and thus efficiency. If the refresh interval is too short, the protocol generates more control packets than needed for mesh construction/maintenance wasting valuable resources such as channel bandwidth and if the interval is too long, ODMRP cannot keep up with network dynamics resulting in packet losses due to link breakages. To find the “right” refresh interval, a mobility prediction scheme [12] was previously proposed trying to adapt the refresh interval to nodes’ mobility. However, it requires additional hardware/software supports: a location service such as GPS (Global Positioning System) from which nodes can get their location information; and all nodes’ clock time to be synchronized using NTP (Network Time Protocol) or the GPS clock. Moreover, it assumes the location service to be error-free and free space radio propagation model [18] in which received signal strength solely depends on its distance to the transmitter. Considering its unrealistic assumptions such as an error-free location service and the free space radio propagation, it is unlikely to work as intended in a real deployment even with the additional hardware/software supports. Another problem of the scheme is that since it chooses the minimum link life-time in the mesh as the route refresh interval, unnecessarily frequent network-wide flooding is inevitable when only a small part in the multicast group has high mobility or unstable connection which may admit more efficient solutions such as the local recovery. In fact, it generates more control packets than ODMRP as Lee et al. [12] showed when nodes’ speed is higher than 50 km/h.

In this paper, we present E-ODMRP an enhanced version of ODMRP with adaptive refresh. Adaptation is driven by receivers’ reports on link breakages rather than mobility prediction. And the adaptive refreshing mechanism is seamlessly integrated with a simple and “unified” (i.e. combined) local recovery and receiver joining scheme. As the time between refresh episodes can be quite long, a new node or a momentarily detached node might lose some data while waiting for the route to it to be refreshed and reconstructed. Upon joining or upon detection of a broken route, a node performs a local route recovery procedure instead of flooding to proactively attach itself to a forwarding mesh or to request a global route refresh from the source. Compared to ODMRP, a slightly lower packet delivery ratio might be expected in E-ODMRP in light load since the new scheme uses packet loss as a indicator of a broken link. The major advantage is reduced overhead (by up to 90%) which translates into a better delivery ratio at high loads.

The rest of the paper is organized as follows: Section 2 overviews existing MANET multicast protocols, Section 3 describes our protocol, Section 4 presents simulation results, and finally Section 5 concludes the paper.

Section snippets

Background and related work

In this section, we introduce ODMRP, the base protocol of E-ODMRP, and ADMR. Also we reivew other MANET multicast routing protocols very briefly.

Enhanced ODMRP with motion adaptive refresh

In this section we describe details of E-ODMRP, an ODMRP enhancement for mobility adaptive refresh.

Simulation results

In this section, we study the performance of E-ODMRP and compare it with ODMRP, PatchODMRP, and ADMR. To this end, we conducted a set of ns-2 [16] simulations.

Conclusion

In this paper, we have presented an enhanced version of ODMRP with motion adaptive refresh, namely E-ODMRP. It performs the periodic refresh at a rate dynamically adapted to the nodes’ mobility. Another feature is the “unification” of local recovery and receiver joining process. On joining or upon detecting a broken route, a node performs a local search to graft to the forwarding mesh proactively. Simulation results show that E-ODMRP reduces the packet overhead by up to 50% yet keeping similar

Acknowledgments

Research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence and was accomplished under Agreement Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to

Soon Y. Oh received his B.S. degree in Information and Computer Sciences from University of California, Irvine in 2003, and his M.S. degree in Computer Science from University of California, Los Angeles in 2005. He is currently working toward his Ph.D. degree in the same university. His research interests include multicast routing in ad hoc wireless networks, delay tolerant multicast routing in ad hoc networks, mobile wireless sensor, and network coding.

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    Soon Y. Oh received his B.S. degree in Information and Computer Sciences from University of California, Irvine in 2003, and his M.S. degree in Computer Science from University of California, Los Angeles in 2005. He is currently working toward his Ph.D. degree in the same university. His research interests include multicast routing in ad hoc wireless networks, delay tolerant multicast routing in ad hoc networks, mobile wireless sensor, and network coding.

    Joon-Sang Park received his Ph.D. in Computer Science from University of California, Los Angeles in 2006, M.S. in Computer Science from the University of Southern California in 2001, and B.S. in Industrial Engineering from Hongik University in 1996. He worked in industry as a software engineer for three years and was a postdoctoral researcher at UCLA. He is now on the faculty of the Computer Engineering Department at Hongik University. His research interests include routing and MAC protocols in mobile ad hoc and sensor networks, smart antennas, and network coding.

    Mario Gerla Dr. Mario Gerla, Professor, UCLA, Computer Science Dept. Dr. Gerla received his Engineering degree from the Politecnico di Milano, Italy, in 1966 and the M.S. and Ph.D. degrees from UCLA in 1970 and 1973. He became IEEE Fellow in 2002. At UCLA, he was part of a small team that developed the early ARPANET protocols under the guidance of Prof. Leonard Kleinrock. He worked at Network Analysis Corporation, New York, from 1973 to 1976, transferring the ARPANET technology to several Government and Commercial Networks. He joined the Faculty of the Computer Science Department at UCLA in 1976, where he is now Professor. At UCLA he has designed and implemented some of the most popular and cited network protocols for ad hoc wireless networks including distributed clustering, multicast (ODMRP and CODECast) and transport (TCP Westwood) under DARPA and NSF grants. He has lead the $12M, 6 year ONR MINUTEMAN project, designing the next generation scalable airborne Internet for tactical and homeland defense scenarios. He is now leading two advanced wireless network projects under ARMY and IBM funding. In the vehicular network scenario, with NSF and Industry sponsorship, he has led the development of peer to peer applications for safe navigation, urban sensing and location aware applications (see www.cs.ucla.edu/NRL for recent publications).

    The material in this paper was presented in part at the 2nd International Symposium on Wireless Communication System (ISWCS 2005).

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