Juan Carlos González García

Effects of Mobility on Membership Estimation and Routing Services in Ad Hoc Networks

The use of MANETs (or Mobile Ad hoc NETworks) is becoming very popular. Power efficiency is a key issue in this type of network, as mobile devices usually rely on limited power supplies. One essential service, the routing protocol, employed to discover routes between nodes in the network, can greatly affect power consumption. Furthermore, many distributed applications require an additional membership service to keep track of the nodes that make up the system at any moment. In general, this information is not provided by routing services with the exception of the Optimised Link State Routing protocol (OLSR). The two services, routing and membership estimation, form a basic support to build other higher---level distributed services on ad hoc networks. To decrease the over-all power consumption these services should be optimized for the intended use of the network. In particular the degree of mobility can have an impact on the power consumption and performance of different approaches to routing and membership estimation. In this paper we present a study of two different approaches that combine a routing service with membership estimation. We compare the proactive OLSR with our own approach. Our approach consists of integrating a gossip-style failure detector with the reactive Dynamic Source Routing protocol (DSR). We present an analysis of the effects of mobility on the global performance and power consumption of the two approaches. We identify scenarios for which each approach is best suited.

A Stability Criteria Membership Protocol for Ad Hoc Networks

Consensus is one of the most common problems in distributed systems. An important example of this in the field of dependability is group membership . However, consensus presents certain impossibilities which are not solvable on asynchronous systems. Therefore, in the case of group membership, systems must rely on additional services to solve the constraints imposed on them by the impossibility of consensus. Such additional services exist in the form of failure detectors and membership estimators . The contribution of this paper is the upper-level algorithm of a protocol stack that provides group membership for dynamic, mobile and partitionable systems, mainly aimed at mobile ad hoc networks. Stability criteria are established to select a subset of nodes with low failure probability to form stable groups of nodes. We provide a description of the algorithm and the results of performance experiments on the NS2 network simulator.

Cross-layer cooperation between membership estimation and routing

Mobile Ad hoc networks are characterised by the absence of a centralised infrastructure and node heterogeneity. Due to size and mobility requirements of the nodes that make up such a network the protocols employed often must deal with limited bandwith and avoid high power consumption. In classical layered protocol stacks, services are run in isolation. We argue, that in order to save band-with, reduce power and improve performance, various services that are running on a node may co-operate. We have identified two services in particular that can benefit greatly from such a co-operation: The routing protocol, which is responsible for discovering routes between nodes in the system and the membership estimation service, which is responsible for providing an estimation of the current composition of the system. The two services are the fundamental building blocks for distributed algorithms and applications at a higher level. In this paper we show how these two basic protocols can cooperate. The membership estimation service can provide useful information to the routing protocol, whereas routing may aid to maintain the membership estimation updated. We describe an implementation of a cross layer architecture, in which the Dynamic Source Routing protocol (DSR) and our Gossip-based membership estimation service share information. We show results of performacne experiments reflecting how this cooperation improves the performance of both services. Finally, we identify scenarios in which the interaction is of most benefit.