doi:10.1016/j.comnet.2007.09.007
Copyright © 2007 Elsevier B.V. All rights reserved.
Efficient virtual-backbone routing in mobile ad hoc networks
aDepartment of Computer Engineering, The Hashemite University, Zarqa, Jordan
bDepartment of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, United States
Received 29 September 2006;
revised 16 August 2007;
accepted 2 September 2007.
Responsible Editor: V.R. Syrotiuk.
Available online 19 September 2007.
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Abstract
Since the physical topology of mobile ad hoc networks (MANETs) is generally unstable, an appealing approach is the construction of a stable and robust virtual topology or backbone. A virtual backbone can play important roles related to routing and connectivity management. In this paper, the problem of providing such a virtual backbone with low overhead is investigated. In particular, we propose an approach, called virtual grid architecture (VGA), that can be applied to both homogeneous and heterogeneous MANETs. We study the performance tradeoffs between the VGA clustering approach and an optimal clustering based on an integer linear program (ILP) formulation. Many properties of the VGA clustering approach, e.g., VGA size, route length over VGA, and clustering overhead are also studied and quantified. Analytical as well as simulation results show that average route length over VGA and VGA cardinality tend to be close to optimal. The results also show that the overhead of creating and maintaining VGA is greatly reduced, and thus the routing performance is improved significantly. To illustrate, two hierarchical routing techniques that operate on top of VGA are presented and evaluated. Performance evaluation shows that VGA clustering approach, albeit simple, is able to provide more stable (long lifetime) routes, deliver more packets, and accept more calls.
Keywords: Mobile ad hoc networks; Topology management; Virtual topology; Routing; Performance
Fig. 1. Selection of zone side length.
Fig. 2. The Fixed zoning process in both (a) Homogeneous networks and (b) Heterogeneous networks.
Fig. 3. (a) Inter-zone communication and (b) Intra-zone communication in VGA.
Fig. 4. Example of the split and merge processes in heterogeneous MANETs.
Fig. 5. Cluster head election algorithm in a certain zone z.
Fig. 6. The zoning process with corresponding virtual topologies for VGA, D-VGA, and optimal cases.
Fig. 7. (a) Diagonal routing capability option and (b) Probability that D-VGA succeeds given that VGA fails.
Fig. 8. On-demand packet forwarding/routing over VGA: an example.
Fig. 9. The illustration of local path restoration in VGA.
Fig. 10. CHs cardinality; homogeneous MANETs.
Fig. 11. CHs cardinality; heterogeneous MANETs.
Fig. 12. Average path length; VGA and D-VGA.
Fig. 13. Communication Overhead in VGA and D-VGA.
Fig. 14. Packet delivery ratio vs. offered load.
Fig. 15. Network end-to-end delay vs. offered load.
Fig. 16. Percentage of broken routes due to mobility.
Fig. 17. Call acceptance rate in the two routing techniques.
Fig. 18. Network control overhead versus offered load using the TC and OD techniques.
Fig. 19. Packet delivery ratio versus offered load under different CH election strategies.
Fig. 20. Effect of power control scheme of VGA on node lifetime.
Fig. 21. OD-based routing scalability as node density increases.
Fig. 22. Figure used in the proof of Proposition 1.
Table 1.
System model notations

Table 2.
Summary of Intra-zone and Inter-zone communication ranges and RTP values

Table 3.
Comparison of clusterhead cardinality for VGA, D-VGA, and optimal clustering

Table 4.
The ILP variables in heterogeneous MANETs

Table 5.
The ILP formulation for finding MCDS

Table 6.
Performance comparison between different algorithms

Here opt is the size of the optimal MCDS; Δ is the maximum node degree; C is the size of the generated connected dominating set; Z is the number of zones in VGA; V, E: the number of nodes and number of edges in the virtual network graph, respectively.