Scalable routing strategies for ad hoc wireless networks

Abstract

In this paper, we consider a large population of mobile stations that are interconnected by a multihop wireless network. The applications of this wireless infrastructure range from ad hoc networking (e.g., collaborative, distributed computing) to disaster recovery (e.g., fire, flood, earthquake), law enforcement (e.g., crowd control, search-and-rescue), and military (automated battlefield). Key characteristics of this system are the large number of users, their mobility, and the need to operate without the support of a fixed (wired or wireless) infrastructure. The last feature sets this system apart from existing cellular systems and in fact makes its design much more challenging. In this environment, we investigate routing strategies that scale well to large populations and can handle mobility. In addition, we address the need to support multimedia communications, with low latency requirements for interactive traffic and qualityof-service (QoS) support for real-time streams (voice/video). In the wireless routing area, several schemes have already been proposed and implemented (e.g., hierarchical routing, on-demand routing, etc.). We introduce two new schemes-fisheye state routing (FSR) and hierarchical state routing (HSR)-which offer some competitive advantages over the existing schemes. We compare the performance of existing and proposed schemes via simulation.

Routing Transient Traffic in Mobile Ad Hoc Networks

“…Protocols such as HSR [6] and HierLS [7], for example, build multi-level, multi-hop clusters and then proactively maintain global routes among the clusters. Other hierarchical approaches such as DSRCEDAR [8] and CBRP [9] proactively maintain a spanning backbone and then use the backbone to perform route-discovery broadcasts reactively and more efficiently.…”

“…These include reactive protocols such as DSR [1] and AODV [2], proactive non-hierarchical protocols such as DSDV [3], hybrid non-hierarchical protocols such as ZRP [4] and SHARP [5], and hierarchical backbone protocols such as such as HSR [6], HierLS [7], DSRCEDAR [8] and CBRP [9].…”

“…Hierarchical link-state protocols such as HSR [6] and HierLS [7] follow the more integrated approach. They build multi-level and multi-hop clusters, and then proactively maintain routes to all the other nodes in the network.…”

An Energy Aware, Cluster-Based Routing Algorithm for Wireless Sensor Networks

“…Nevertheless, the chief disadvantage of multi-path routing schemes [8,9] is that the sensor nodes only keep a local view of energy usage and the nodes in the network can not have an even traffic dispatch. In addition, many studies have focused on cluster-based energy-efficient routing protocol for wireless sensor networks [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. Power-Efficient Gathering in Sensor Information Systems (PEGASIS) [11] prolongs the network lifetime with a chain topology.…”

“…Thus, network clustering can increase system lifetime and energy efficiency. Cluster-based routing protocols have special advantages: they can enhance the scalability and efficiency of the routing protocol to reduce the routing complexity [25], reduce the complexity of location management [26], and improve the power control procedure [27]. However, LEACH may also have several problems: First, if the coverage of the cluster-heads is too small, then some cluster-heads may not have any members in their clusters.…”