Location based multicasting has been gaining considerable attention due to its stateless operation, potential for scalability and resilience against mobility in mobile ad hoc networks. One of the key requirements for location based multicast is location service, which operates in a distributed manner to provide the current locations of all group members in order to construct a location based multicast tree. While literature describes a few mulitcast location service protocols, there has been no prior study to evaluate these protocols for scalable operation in a large ad hoc network. In this paper, we study four multicast location service protocols, namely-MLS, HRPM, AMDLM and SPBM-for scalability in a uniformly distributed ad hoc network. Our analysis shows that the MLS protocol scales well in both the total location service cost as well as the per node storage requirement to carry out location service.

Geometric routing using source-destination locations has been widely suggested as a scalable alternative to conventional routing approaches in mobile ad hoc networks. Recently, there has been considerable attention on face routing in planar graphs constructed from overlay graphs in wireless networks. Given a plane tiled into an infinite mesh of polygons, an overlay graph is defined as one in which a graph edge is defined between two adjacent polygons if a radio link exists between any two nodes located in these polygons. We consider the problem of constructing a connected planar graph from the overlay graph, and geometric routing in such graphs. We prove a specific property of such graphs known as the redundancy property and propose a distributed routing algorithm called grid traversal algorithm (GTA) based on the redundancy property of overlay graphs. The algorithm is both localized and energy efficient, but may not guarantee connectivity in pathological cases. Simulations show that such disconnections are rare in practise and that GTA performs very well in terms of percentage of data delivered, data delay and overhead compared to GPSR, a geometric routing protocol that routes on a planar graph extracted from the unit disk graph.

In this paper, we introduce a novel concept of integrating ''macro-mobility" information obtained from the sociological movement pattern of mobile MANET users into routing. The extraction of this mobility information is based on our observation that the movement of a mobile user exhibits a partially repetitive "orbital" pattern involving a set of "hubs" in practice. This partially deterministic movement pattern is both practical and useful in locating nodes and routing packets to them without the need for constant tracking or flooding. Leveraging on this hub-based orbital pattern, we propose a sociological orbit aware location approximation and routing (SOLAR) protocol. Through extensive performance analysis we show that SOLAR significantly outperforms conventional routing protocols like dynamic source routing (DSR) and location aided routing (LAR) in terms of higher data throughput, lower control overhead, and lower end-to-end delay.

Location tracking has several applications in mobile (cellular or ad hoc) networks, such as location-based routing algorithms and consumer services. It is often difficult to compute the location of a node precisely because of the infrastructure costs and the errors inherent in most tracking techniques. Furthermore, this accuracy differs amongst nodes based on the scattered availability of equipment such as GPS. We focus on heterogeneous mobile networks, wherein some nodes know their locations more precisely than others and there is a short-range peer-to-peer communication channel such as Bluetooth or 802.11. We consider a generalized notion of location, called vicinity, which is the set of potential locations for a node. We formulate a hierarchy of distance constraints that can be applied in a network and devise efficient distributed techniques for computing the most optimal (smallest) vicinities under various constraint classes. In particular, our algorithms use both proximity and non-proximity relationships between the nodes. We present simulation results establishing the effectiveness of using these different types of constraints.

A major challenge faced in mobile ad hoc networks (MANET) is locating the devices for communication, especially with high node mobility and sparse node density. Present solutions provided by the ad hoc routing protocols range from flooding the entire network with route requests, to deploying a separate location management scheme to maintain a device location database. In this work, we propose a novel scheme called acquaintance based soft location management (ABSLM) in MANET. In ABSLM, nodes make use of the real life concept of making acquaintances and keeping in touch with them regarding each other's current locations. ABSLM has a two-fold aim: to avoid the overhead of flooding: and to use a 'soft' location management setup that does not require a strict location management strategies and is thus computationally less expensive than the standard 'hard' location management schemes. Simulation results show that the ABSLM not only outperforms the existing flooding schemes in terms of throughput, overhead and location discovery latency, but also achieves a performance comparable to 'hard' grid based location management schemes with a much lower control overhead.

Geography based routing in mobile ad hoc networks is an application that uses the location information of nodes in a network to route data packets. Since the amount of network state information that each node needs to maintain in order to route packets is minimal, location based routing is considered scalable compared to existing routing protocols in ad hoc networks. However, geographic routing requires location management, where the locations of destination nodes needs to be found before the actual routing can begin. Many location management schemes have been proposed in the literature, but no prior work has quantitatively compared the scalability of these protocols with respect to the increase in the number of nodes in the network. In this work, we use a theoretical framework to show the asymptotic scalability of three location management protocols. We also carry out extensive simulations to study the performance of these protocols under practical considerations. Our results indicate that all protocols perform well, with a slight performance degradation with the increasing network size. In particular, the hierarchical grid location management protocol (HGRID) performs the best for all practical purposes, and is a candidate for location management in a wireless network architecture.

In this paper, we characterize analytically the multiaccess interference in wireless code-division multiple-access sensor networks with uniformly random distributed nodes and study the tradeoff between interference and connectivity. To provide a guideline for improving system behavior, three competitive deterministic topologies are evaluated along with the random topology in terms of link-level and network-level (routing) performance. The impact of signature code length and receiver design on the network performance for different topologies is also studied.

Recently, a new family of protocols has been introduced for large scale ad hoc networks that makes use of the approximate location of nodes in the network for geography-based routing. Location management plays an important role in such protocols, and previous work in this area has shown that the asymptotic overhead of location management is heavily dependant on the service primitives (location registration, maintenance and discovery) supported by a location management protocol. Currently, SLALoM (C.T. Cheng et al., 2002), which is a grid-based protocol optimized for large node movements, achieves the best known upper bound on the asymptotic worst case overhead of location management. However, the location registration cost in SLALoM dominates other costs for all practical purposes, and thus novel schemes need to be designed to limit this control traffic. In this work, we use the idea of location forwarding to devise a new scheme called ELF that limits the signalling traffic, and thus enhances the scalability of location management in large ad hoc networks. We find that, while the asymptotic overhead cost by such an improvisation matches that of SLALoM, ELF outperforms SLALoM in average case scenarios.

In a mobile wireless ad-hoc network, nodes move about and relay packets destined for other nodes. One of the biggest challenges in this area is the design of scalable routing protocols. A family of routing protocols has emerged that is potentially more scalable than the protocols that discover and/or maintain end-to-end routes. These protocols are location-based-the network maintains nodes' approximate geographic locations and use the information to route packets. An important component of these protocols is the management of the location information at network nodes. We present one such scheme called SLALoM which scales well in large, mobile ad-hoc networks. In particular, we prove that under a specific environment the overhead cost of SLALoM is asymptotically lower than SLURP, the only other location management scheme that has been analyzed theoretically. We also provide simulation results that show our scheme performs well in comparison to SLURP under a variety of scenarios not incorporated into the analysis.