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In sparse mobile ad hoc networks, placement of services and data is crucial to assure their availability to all nodes because sparse population of nodes can lead to (frequent) network partitions. If these dynamic networks display a fairly stable cluster structure, it is possible to utilize this structure to improve service and data availability. However, clustering in a dynamic network is a very challenging task due to the ever-changing topology and irregular density of such a network. In this paper, we investigate clustering of dynamic networks with the help of community detection mechanisms, using only topology information from the local routing table. The main aim of our approach is to reduce to "zero" the communication overhead needed for cluster management and to dynamically adapt to the size and layout of the network. We have performed extensive experiments to evaluate the consistency, quality, and stability of the clustering returned by our algorithms. The results show that our nonintrusive clustering indeed discovers temporary groups of nodes that form stable clusters in the network. Moreover, even though the local routing tables in general reflect slightly diverging topologies, our results still show only small differences between the communities detected at different nodes.Index Terms-Clustering, community detection algorithm, network topology, rescue operations, sparse mobile ad hoc networks (MANETs), wireless communications.

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No abstract

Information sharing is a mission critical key element in rescue and emergency operations. Mobile ad-hoc networks (MANETs) could provide a useful infrastructure to support information sharing, but appropriate applications are needed. To facilitate efficient application development for this type of infrastructure, middleware support is needed. In the Ad-Hoc Info Ware project, we are currently developing corresponding middleware services. In this paper, we discuss the application requirements that are imposed onto the middleware services, and we outline our technical approach to address the corresponding challenges. The architecture we propose comprises five main building blocks, namely knowledge management, a local and a distributed event notification service, resource management, and security and privacy management. We indicate design alternatives for these building blocks, identify open problems and relate our approach to the state-of-the-art.