Abstract not found

Abstract not found

This paper presents a novel routing protocol for wireless ad hoc networks -- Fisheye State Routing (FSR). FSR introduces the notion of multi-level fisheye scope to reduce routing update overhead in large networks. Nodes exchange link state entries with their neighbors with a frequency which depends on distance to destination. From link state entries, nodes construct the topology map of the entire network and compute optimal routes. Simulation experiments show that FSR is a simple, efficient and scalable routing solution in a mobile, ad hoc environment.

Abstract – In this paper, we present a novel routing protocol for wireless

This paper discusses online power-aware routing in large wireless ad-hoc networks for applications where the message sequence is not known. We seek to optimize the lifetime of the network. We show that online power-aware routing does not have a constant competitive ratio to the off-line optimal algorithm. We develop an approximation algorithm called max-min zPmin that has a good empirical competitive ratio. To ensure scalability, we introduce a second online algorithm for power-aware routing. This hierarchical algorithm is called zone-based routing. Our experiments show that its performance is quite good.

Abstract—A new global positioning system (GPS)-based routing protocol for ad hoc networks, called zone-based hierarchical link state (ZHLS) routing protocol, is proposed. In this protocol, the network is divided into nonoverlapping zones. Each node only knows the node connectivity within its zone and the zone connectivity of the whole network. The link state routing is performed on two levels: local node and global zone levels. Unlike other hierarchical protocols, there is no cluster head in this protocol. The zone level topological information is distributed to all nodes. This “peer-to-peer ” manner mitigates traffic bottleneck, avoids single point of failure, and simplifies mobility management. Since only zone ID and node ID of a destination are needed for routing, the route from a source to a destination is adaptable to changing topology. The zone ID of the destination is found by sending one location request to every zone. Simulation results show that our location search scheme generates less overhead than the schemes based on flooding. The results also confirm that the communication overhead for creating and maintaining the topology in the proposed protocol is smaller than that in the flat LSR protocol. This new routing protocol provides a flexible, efficient, and effective approach to accommodate the changing topology in a wireless network environment. Index Terms — Ad hoc networks, global positioning system (GPS), hierarchical routing, link state, packet radio, routing, zone routing. I.

Unlike in a wired network, a packet transmitted by a node in an ad hoc wireless network can reach all neighbors. Therefore, the total number of transmissions (forward nodes) is generally used as the cost criterion for broadcasting. The problem of finding the minimum number of forward nodes is NPcomplete. Among various approximation approaches, dominant pruning [7] utilizes 2-hop neighborhood information to reduce redundant transmissions. In this paper, we analyze some deficiencies of the dominant pruning algorithm and propose two better approximation algorithms: total dominant pruning and partial dominant pruning. Both algorithms utilize 2-hop neighborhood information more effectively to reduce redundant transmissions. Simulation results of applying these two algorithms show performance improvements compared with the original dominant pruning. In addition, two termination criteria are discussed and compared through simulation.

Wireless networks allow a more flexible model of communication than traditional networks since the user is not limited to a fixed physical location. Unlike cellular wireless networks, an ad hoc wireless network does not have any fixed communication infrastructure. For an active connection, the end host as well as the intermediate nodes can be mobile. Therefore routes are subject to frequent disconnections. In such an environment, it is important to minimize disruptions caused by the changing topology for critical application such as voice and video. This presents a difficult challenge for routing protocols, since rapid reconstruction of routes is crucial in the presence of topology changes. By exploiting non-random behaviors for the mobility patterns that mobile users exhibit, we can predict the future state of network topology and perform route reconstruction proactively in a timely manner. Moreover, by using the predicted information on the network topology, we can eliminate transmis...

A mobile ad hoc network (MANET) is a multi-hop wireless network capable of autonomous operation. The mobility of MANET nodes can lead to frequent and unpredictable topology changes. Most MANET literature assumes that network related information of a node (such as its IP address, netmask, etc.) is configured statically, prior to the node joining the MANET. However, not all nodes have IP addresses permanently assigned to them. Such nodes rely on a centralized server and use a dynamic host configuration protocol, like DHCP [1], to acquire an IP address. Such a solution cannot be employed in MANETs due to the unavailability of any centralized DHCP server. In this paper, we first present a survey of possible solutions approaches, and discuss their limitations. Then, we present a distributed dynamic host configuration protocol designed to configure nodes in a MANET. We show that the proposed protocol works correctly and does not have the limitations of earlier approaches. Finally, we evaluate the performance of the solution through simulation experiments, and conclude with a discussion of related security issues.

In the paper, we devise and evaluate a fully decentralized, light-weight, dynamic clustering algorithm for target tracking. Instead of assuming the same role for all the sensors, we envision a hierarchical sensor network that is composed of (a) a static backbone of sparsely placed high-capability sensors which will assume the role of a cluster head (CH) upon triggered by certain signal events; and (b) moderately to densely populated low-end sensors whose function is to provide sensor information to CHs upon request. A cluster is formed and a CH becomes active, when the acoustic signal strength detected by the CH exceeds a pre-determined threshold. The active CH then broadcasts an information solicitation packet, asking sensors in its vicinity to join the cluster and provide their sensing information. We address and devise solution approaches (with the use of Voronoi diagram) to realize dynamic clustering: (I1) how CHs cooperate with one another to ensure that only one CH (preferably the CH that is closest to the target) is active with high probability; (I2) when the active CH solicits for sensor information, instead of having all the sensors in its vicinity reply, only a sufficient number of sensors respond with non-redundant, essential information to determine the target location; and and (I3) both the packets that sensors send to their CHs and packets that CHs report to subscribers do not incur significant collision. Through both probabilistic analysis and ns-2 simulation, we show with the use of Voronoi diagram, the CH that is usually closest to the target is (implicitly) selected as the leader and and that the proposed dynamic clustering algorithm effectively eliminates contention among sensors and renders more accurate estimates of target locations as a result of better quality data collected and less collision incurred.