Mohammed J.F. Alenazi

Multilevel resilience analysis of transportation and communication networks

For many years the research community has attempted to model the Internet in order to better understand its behaviour and improve its performance. Since much of the structural complexity of the Internet is due to its multilevel operation, the Internet’s multilevel nature is an important and non-trivial feature that researchers must consider when developing appropriate models. In this paper, we compare the normalised Laplacian spectra of physical- and logical-level topologies of four commercial ISPs and two research networks against the US freeway topology, and show analytically that physical level communication networks are structurally similar to the US freeway topology. We also generate synthetic Gabriel graphs of physical topologies and show that while these synthetic topologies capture the grid-like structure of actual topologies, they are more expensive than the actual physical level topologies based on a network cost model. Moreover, we introduce a distinction between geographic graphs that include degree-2 nodes needed to capture the geographic paths along which physical links follow, and structural graphs that eliminate these degree-2 nodes and capture only the interconnection properties of the physical graph and its multilevel relationship to logical graph overlays. Furthermore, we develop a multilevel graph evaluation framework and analyse the resilience of single and multilevel graphs using the flow robustness metric. We then confirm that dynamic routing performed over the lower levels helps to improve the performance of a higher level service, and that adaptive challenges more severely impact the performance of the higher levels than non-adaptive challenges.

Topology connectivity analysis of internet infrastructure using graph spectra

Understanding and modelling the Internet has been a major research challenge in part due to the complexity of the interaction among its protocols and in part due to multilevel, multidomain topological structure. It is therefore crucial to properly analyse each structural level of the Internet to gain a better understanding, as well as to improve its resilience properties. In this paper, first we present the physical and logical topologies of two ISPs and compare these topologies with the US interstate highway topology by using graph metrics and then using the normalised Laplacian spectrum. Our results indicate that physical network topologies are closely correlated with the motorway transportation topology. Finally, we study the spectral properties of various communication networks and observe that the spectral radius of the normalised Laplacian matrix is a good indicator of graph connectivity when comparing different size and order graphs.

On the fitness of geographic graph generators for modelling physical level topologies

The Internet topology has been studied extensively for decades. However, the emphasis of Internet topology research has been on logical level topologies. On the other hand, physical level topologies are necessary to study the resilience of networks realistically. In this paper, we analyse the structure of synthetic geographic topologies whose node locations are given by those of actual physical level graphs. Our results indicate that the synthetic Gabriel graphs capture the grid-like structure of physical level networks. Moreover, given that the cost of physical level topologies is an important aspect from a design perspective, we also compare the cost of several synthetically generated geographic graphs and find that the synthetic Gabriel graphs achieve the smallest cost among all of the graph models that we consider.

Network design and optimisation based on cost and algebraic connectivity

Network design and optimisation has been one of the major focuses of the research community over the past decades. Connectivity of topologies can be improved by simply adding links; however, this incurs cost for addition of links for increased resilience. Therefore, topological design and optimisation requires developing algorithms so that a designer can select optimum parameters to achieve resilience in the least costly manner. In this paper, we develop a heuristic algorithm that optimises a topology based on algebraic connectivity metric that is defined as the second smallest eigenvalue of the Laplacian matrix. Furthermore, the connectivity of a topology is improved based on the available budget, for which we capture network cost in terms of euclidian distance between two connected nodes. We apply our algorithm on three realistic sets of backbone service provider graphs and compare the utility of our algorithm. The heuristic algorithm we introduce in this paper optimises topologies and is computationally less costly than an exhaustive optimisation.

A comparative analysis of geometric graph models for modelling backbone networks

Many researchers have studied Internet topology, and the analysis of complex and multilevel Internet structure is nontrivial. The emphasis of these studies has been on logical level topologies, however physical level topologies are necessary to study resilience realistically, given the geography and multilevel nature of the Internet. In this paper, we investigate the representativeness of the synthetic Gabriel, geometric, population-weighted geographical threshold, and location-constrained Waxman graph models to the actual fibre backbone networks of six providers. We quantitatively analyse the structure of the synthetic geographic topologies whose node locations are given by those of actual physical level graphs using well-known graph metrics, graph spectra, and the visualisation tool we have developed. Our results indicate that the synthetic Gabriel graphs capture the grid-like structure of physical level networks best. Furthermore, given that the cost of physical level topologies is an important aspect from a design perspective, we also compare the cost of synthetically generated geographic graphs and find that the synthetic Gabriel graphs achieve the smallest cost among all the graph models that we consider. Finally, based on our findings we propose a graph generation method to model physical level topologies, and show that it captures both grid and star structures ideally.

Cost-efficient algebraic connectivity optimisation of backbone networks

Backbone networks are prone to failures due to targeted attacks or large-scale disasters. Network resilience can be improved by adding new links to increase network connectivity and robustness. However, random link additions without an optimisation objective function can have insignificant connectivity improvement. In this paper, we develop a heuristic algorithm that optimises a network by adding links to achieve a higher network resilience by maximising algebraic connectivity and decreasing total cost via selecting cost-efficient links. We apply our algorithm to five different backbone topologies and measure algebraic connectivity improvement and the cost incurred while adding new links. For evaluation, we apply three centrality node attacks to the non- and optimised networks and show the network flow robustness while nodes are removed. Our results show that optimised graphs with higher algebraic connectivity values are mostly more resilient to centrality-based node attacks.

Comprehensive comparison and accuracy of graph metrics in predicting network resilience

Graph robustness metrics have been used largely to study the behavior of communication networks in the presence of targeted attacks and random failures. Several researchers have proposed new graph metrics to better predict network resilience and survivability against such attacks. Most of these metrics have been compared to a few established graph metrics for evaluating the effectiveness of measuring network resilience. In this paper, we perform a comprehensive comparison of the most commonly used graph robustness metrics. First, we show how each metric is determined and calculate its values for baseline graphs. Using several types of random graphs, we study the accuracy of each robustness metric in predicting network resilience against centrality-based attacks. The results show three conclusions. First, our path diversity metric has the highest accuracy in predicting network resilience for structured baseline graphs. Second, the variance of node-betweenness centrality has mostly the best accuracy in predicting network resilience for Waxman random graphs. Third, path diversity, network criticality, and effective graph resistance have high accuracy in measuring network resilience for Gabriel graphs.

Cost-constrained and centrality-balanced network design improvement

Improving resilience against failures and targeted attacks is an important aspect of network design. The resilience and cost of networks are two opposing objectives in which a designer should consider when building networks. We develop a heuristic algorithm that balances the centrality of networks by adding a set of links that minimizes the variance of graph centrality measures in a least costly fashion. Moreover, our algorithm limits the addition of links by a budget constraint. We apply our algorithm to three different realistic topologies and measure the performance of the improved graphs in terms of flow robustness when subjected to targeted attacks. Our results indicate that degree-balanced networks are more resilient than both betweenness-balanced and closeness-balanced networks.

Protocols for highly-dynamic airborne networks

End-to-end communication in highly-dynamic airborne networks is challenging due to the presence of highly mobile nodes and the inherent nature of wireless communication channels. Domain-specific protocols are required that can address these challenges and enable reliable transmission of data in this environment. We develop the ANTP (airborne network and transport protocols) suite that operates in this highly-dynamic environment while utilising cross-layer optimisations between the physical, MAC, network, and transport layers. We show how each component in the ANTP suite outperforms the traditional TCP/IP and MANET protocols through simulation using ns-3. Having verified these protocols through simulation and analysis, the next step towards deployment of the ANTP suite is developing a cross-platform implementation of the protocols. Towards this end we present an architecture for the protocol stack to be implemented in the Python programming language.

Epidemic routing protocol implementation in ns-3

Routing protocols play a significant role in the overall performance of ad-hoc wireless networks. Several routing protocols have been proposed for ad hoc environments. Any new proposed protocol should be compared with other routing protocols to show its performance under several scenarios. Epidemic routing was one of the first routing schemes proposed for DTNs (delay-tolerant networks). In this paper, we present our implementation of the epidemic routing protocol in the ns-3 simulator. We analyse its performance and compare with the previous ns-2 implementation. Our analysis conforms the results of the previous ns-2 implementation. Moreover, we compare our epidemic implementation to other MANET routing protocols in a delay tolerant environment and we show that epidemic routing outperforms other MANET routing protocols in terms of packet delivery at the expense of overhead and delay.