Ovidiu Valentin Drugan

Detecting communities in sparse MANETs

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.

Building resource aware middleware services over MANET for rescue and emergency applications

In the ad-hoc InfoWare project we investigate middleware solutions for mobile ad-hoc networks (MANETs) used in emergency and rescue situations. One goal in the project is to increase availability of services and information through resource awareness. In this context we regard the ability to predict with a certain confidence the future resource availability as very helpful. The work described in this paper, presents our current progress towards prediction of future connectivity between nodes using information about a nodes neighborhood extracted from the routing protocol. The simple idea is that if two nodes have been close to each other for a certain time, there is a high probability that they will be close also in the immediate future. The advantage with our approach is that the nodes do not need location information. We are using simulation to analyze for how far into the future we can make valid predictions

Middleware Services for Information Sharing in Mobile Ad-Hoc Networks

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 InfoWare 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.

On the importance of composability of ad hoc mobile middleware and trust management

Distributed computing is widely expected to become ubiquitous over the next decade. Distributed services such as those provided by Service Oriented Architectures which will support this ubiquity must meet many requirements at both runtime and over their lifecycle. Composability is one key requirement for such services. In this paper we provide refined definitions of composability as it applies to such distributed services, encompassing both hardware and software. We then analyze these composability issues as they apply to two middleware frameworks which support critical infrastructures. The first examines composability issues for resource management infrastructure for a framework that provides middleware services for ad hoc mobile networks designed to support emergency rescue coordination. The second investigates composability issues involved with trust management for status dissemination for the electric power grid.

Dynamic clustering in Sparse MANETs

In dynamic networks like sparse mobile ad hoc networks used during rescue operations, data and service availability and reachability is crucial. Such dynamic networks can be analysed to identify stable clusters as well as nodes with frequent cluster affiliation changes; these structural and behavioural properties can then be utilised for careful data and service placement and ferry selection. Factors that influence the outcome are the clustering algorithms used and how and when they are applied. In this paper, we identify cluster evolution based on similarities between clusters detected by community detection algorithms on consecutive network snapshots. The community detection algorithms are node agnostic in the sense that they do not elect cluster heads, and are non-intrusive, i.e., they extract topology information from the local routing tables without interfering with the routing algorithm nor creating network traffic. We have performed extensive experiments to evaluate how the choice of clustering algorithm affects the evolution and timeline of clusters and the identification of node-cluster affiliations. Additionally, we compare how well the algorithms perform on selecting nodes for data and service placement and ferrying.

Increasing the Lifetime of Roadside Sensor Networks Using Edge-Betweenness Clustering

Wireless Sensor Networks are proven highly successful in many areas, including military and security monitoring. In this paper, we propose a method to use the edge-betweenness community detection algorithm to determine clusters and to facilitate in-network data aggregation for these applications. To minimize the cost of determining the clusters, the approach is based on exploiting the topology information from the ad hoc routing protocol. Three different schemes are proposed. (1) A distributed clustering scheme using the OLSR routing protocol. (2) A centralized scheme using OLSR. (3) A centralized scheme using an extension to the DYMO-low routing protocol. All schemes support sensor heterogeneity allowing that different data content can use different routing paths. The paper presents simulation results and analysis of the cluster generation for each of the schemes. The results show that our method is a simple and effective method to improve scalability and lifetime of roadside sensor networks.

Resource Aware Middleware Services Over MANETs

In emergency and rescue operations MANETs can help to increase the efficiency of the collaborative work. The goal is to increase the availability of services and information through resource awareness. The work described in this paper, presents our approach towards prediction of current and future resources available on remote devices. Our solution is based on information extracted from the nodes routing protocol. The advantage of our approach is that resource management is not intrusive, does not need location information, and is independent of the routing protocol. We are using simulations to analyze for how far into the future we can make valid predictions.

Predicting Time Intervals forResource Availability in MANETs

In emergency and rescue operations MANETs can help to improve the efficiency of the collaborative work. The goal is to increase the availability of services and information through resource awareness. The work described in this paper, presents our approach towards prediction of current and future resources available on remote devices. Our resource prediction algorithm is based on information extracted from a nodes routing protocol. The advantage of this approach is that resource management is not intrusive, does not need location information, and can work with any given routing protocol. We are using simulations with different node mobility models, roasting protocols and communication patterns, to analyze for how far into the future we can make valid predictions