Hannes Frey

On delivery guarantees of face and combined greedy-face routing in ad hoc and sensor networks

It was recently reported that all known face and combined greedy-face routing variants cannot guarantee message delivery in arbitrary undirected planar graphs. The purpose of this article is to clarify that this is not the truth in general. We show that specifically in relative neighborhood and Gabriel graphs recovery from a greedy routing failure is always possible without changing between any adjacent faces. Guaranteed delivery then follows from guaranteed recovery while traversing the very first face. In arbitrary graphs, however, a proper face selection mechanism is of importance since recovery from a greedy routing failure may require visiting a sequence of faces before greedy routing can be restarted again. A prominent approach is to visit a sequence of faces which are intersected by the line connecting the source and destination node. Whenever encountering an edge which is intersecting with this line, the critical part is to decide if face traversal has to change to the next adjacent one or not. Failures may occur from incorporating face routing procedures that force to change the traversed face at each intersection. Recently observed routing failures which were produced by the GPSR protocol in arbitrary planar graphs result from incorporating such a face routing variant. They cannot be constructed by the well known GFG algorithm which does not force changing the face anytime. Beside methods which visit the faces intersected by the source destination line, we discuss face routing variants which simply restart face routing whenever the next face has to be explored. We give the first complete and formal proofs that several proposed face routing, and combined greedyface routing schemes do guarantee delivery in specific graph classes or even any arbitrary planar graphs. We also discuss the reasons why other methods may fail to deliver a message or even end up in a loop.

Scalable geographic routing algorithms for wireless ad hoc networks

The design of efficient routing protocols for dynamical changing network topologies is a crucial part of building power-efficient and scalable ad hoc wireless networks. If position information is available due to GPS or some kind of relative positioning technique, a promising approach is given by geographic routing algorithms, where each forwarding decision is based on the positions of current, destination, and possible candidate nodes in vicinity only. About 15 years ago heuristic greedy algorithms were proposed, which in order to provide freedom from loops might fail even if there is a path from source to destination. In recent years planar graph traversal has been investigated as one possible strategy to recover from such greedy routing failures. This article provides a tutorial for this class of geographic routing algorithms, and discusses recent improvements to both greedy forwarding and routing in planar graphs.

Strictly Localized Sensor Self-Deployment for Optimal Focused Coverage

We consider sensor self-deployment problem, constructing FOCUSED coverage (F-coverage) around a Point of Interest (POI), with novel evaluation metric, coverage radius. We propose to deploy sensors in polygon layers over a locally computable equilateral triangle tessellation (TT) for optimal F-coverage formation, and introduce two types of deployment polygon, H-polygon and C-polygon. We propose two strictly localized solution algorithms, Greedy Advance (GA), and Greedy-Rotation-Greedy (GRG). The two algorithms drive sensors to move along the TT graph to surround POI. In GA, nodes greedily proceed as close to POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around POI along locally computed H- or C-polygon to a vertex where greedy advance can resume. We prove that they both yield a connected network with maximized hole-free area coverage. To our knowledge, they are the first localized sensor self-deployment algorithms that provide such coverage guarantee. We further analyze their coverage radius property. Our study shows that GRG guarantees optimal or near optimal coverage radius. Through extensive simulation we as well evaluate their performance on convergence time, energy consumption, and node collision.

Routing in Wireless Sensor Networks

Wireless sensor networks are formed by small sensor nodes communicating over wireless links without using a fixed network infrastructure. Sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are also limited. Routing protocols for wireless sensor networks have to ensure reliable multi-hop communication under these conditions. We describe design challenges for routing protocols in sensor networks and illustrate the key techniques to achieve desired characteristics, such as energy efficiency and delivery guarantees. We give a survey of state-of-the-art routing techniques with a focus on geographic routing, a paradigm that enables a reactive message-efficient routing without prior route discovery or knowledge of the network topology. Different geographic routing strategies are described as well as beaconless routing techniques. We also show the physical layer impact on routing and outline further research directions.

Focused-coverage by mobile sensor networks

We pinpoint a new sensor self-deployment problem, constructing focused coverage around a Point of Interest (POI), and introduce an evaluation metric, coverage radius. We propose two solutions, Greedy Advance (GA) and Greedy-Rotation-Greedy (GRG), which are to our knowledge the first sensor self-deployment algorithms that operate in a purely localized manner and yet provide coverage guarantee. The two algorithms drive sensors to move along a locally-computed equilateral triangle tessellation (TT) to surround POI. In GA, nodes greedily proceed as close to POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around POI to a TT vertex where greedy advance can resume. They both yield a connected network of TT layout with hole-free coverage; GRG furthermore assures a hexagon coverage shape centered at POI. We prove their correctness and analyze their coverage radius property. Our study shows that GRG guarantees optimal hexagonal coverage radius and near optimal circular coverage radius. Through extensive simulation we as well evaluate their performance on convergence time, energy consumption, and node collision.

JANE-The Java Ad Hoc Network Development Environment

This work describes a Java based development platform which is intended to support ad hoc network researchers in application and protocol design. Software development within this environment is expected to follow a bottom up approach. Basic functionality is implemented in elementary components which can be combined to more complex ones by using well defined interfaces. With dynamically changing network links being rather the common case than a failure situation, asynchronous communication has been selected as the main communication paradigm within this platform. Reusability of components in different execution contexts by providing an appropriate machine abstraction is a further important design decision which drove the platform development. Code written once can be executed in a pure simulation mode, in a hybrid setting with real devices being attached to a running simulation and, finally, in a setting using real devices only. Software development following this three-tier development process paired with the platforms rich visualization features emerged to significantly ease the burden of debugging and parameterizing in such highly dynamic and inherently distributed environments. In conjunction with a core middleware platform a rich set of generic services has been implemented with the most important ones being described in this work. Several application programs have already been implemented on top of these services. These applications which are described in this work as well serve as a proof of concept for both the platform itself and the utilized set of generic services

On Delivery Guarantees and Worst-Case Forwarding Bounds of Elementary Face Routing Components in Ad Hoc and Sensor Networks

In this paper, we provide a thorough theoretical study on delivery guarantees, loop-free operation, and worst-case behavior of face and combined greedy-face routing. We show that under specific planar topology control schemes, recovery from a greedy routing failure is always possible without changing between any adjacent faces. Guaranteed delivery then follows from guaranteed recovery while traversing the very first face. In arbitrary planar graphs, however, a proper face selection mechanism is of importance since recovery from a greedy routing failure may require visiting a sequence of faces before greedy routing can be restarted again. We provide complete and formal proofs that several proposed face routing and combined greedy-face routing schemes guarantee message delivery in specific planar graph classes or even in arbitrary planar graphs. We also discuss the reasons why other methods fail to deliver a message or even end up in a loop. In addition, we investigate the behavior of face routing in arbitrary not necessarily planar networks and show, while delivery guarantees cannot be supported in such a general case, most face and combined greedy-face routing variants support at least loop-free operation. For those variants, we derive worst-case upper bounds on the number of forwarding steps.

Planar graph routing on geographical clusters

Geographic routing protocols base their forwarding decisions on the location of the current device, its neighbors, and the packets destination. Early proposed heuristic greedy routing algorithms might fail even if there is a path from source to destination. In recent years several recovery strategies have been proposed in order to overcome such greedy routing failures. Planar graph traversal was the first of those strategies that does not require packet duplication and memorizing past routing tasks. This article introduces a novel recovery strategy based on the idea of planar graph traversal but performing routing tasks along geographical clusters instead of individual nodes. The planar graph construction method discovered so far needs one-hop neighbor information only, but may produce disconnection even if there is a path from source to destination. However, simulation results show that the proposed algorithm is a good choice from a practical point of view, since disconnection does only concern sparse networks, while in dense network the proposed algorithm competes with existing solutions and even outperforms planar graph routing methods based on one-hop neighbor information. This paper finally gives an outline of further research directions which show that geographical clusters may be the key to solve some problems that come along with planar graph routing in wireless networks.

Localized sensor self-deployment with coverage guarantee

We pinpoint a new sensor self-deployment problem, achieving focused coverage around a Point of Interest (POI), and introduce an evaluation metric, coverage radius. We propose two purely localized solution protocols Greedy Advance (GA) and Greedy-Rotation-Greedy (GRG), both of which are resilient to node failures and work regardless of network partition. The two algorithms drive sensors to move along a locally-computed triangle tessellation (TT) to surround the POI. In GA, nodes greedily proceed as close to the POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around the POI to a TT vertex where greedy advance can resume. They both yield a connected network of TT layout with hole-free coverage. Further, GRG ensures a hexagon coverage shape centered at the POI.

Localized minimum spanning tree based multicast routing with energy-efficient guaranteed delivery in ad hoc and sensor networks

We present a localized geographic multicast scheme, MSTEAM, based on the construction of local minimum spanning trees (MSTs), that requires information only on 1-hop neighbors. A message replication occurs when the MST spanning the current node and the set of destinations has multiple edges originated at the current node. Destinations spanned by these edges are grouped together, and for each of these subsets the best neighbor is selected as the next hop. This selection is based on a cost over progress metric, where the progress is approximated by subtracting the weight of the MST over a given neighbor and the subset of destinations to the weight of the MST over the current node and the subset of destinations. Since such greedy scheme may lead the message to a void area (i.e., no neighbor providing positive progress), we propose a new multicast generalization of the well-known face recovery mechanism. We provide a theoretical analysis proving that MSTEAM is loop-free, and achieves delivery of the multicast message as long as a path to the destinations exists. Our results demonstrate that MSTEAM outperforms the best existing localized multicast scheme, and is almost as efficient as a centralized scheme in high densities.