Graph measures and network robustness

Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to continue to perform well when it is subject to failures or attacks. In this paper we survey a large amount of robustness measures on simple, undirected and unweighted graphs, in order to offer a tool for network administrators to evaluate and improve the robustness of their network. The measures discussed in this paper are based on the concepts of connectivity (including reliability polynomials), distance, betweenness and clustering. Some other measures are notions from spectral graph theory, more precisely, they are functions of the Laplacian eigenvalues. In addition to surveying these graph measures, the paper also contains a discussion of their functionality as a measure for topological network robustness

Routing in a many-to-one communication scenario in a realistic VDTN

In this paper, we evaluate and compare the performance of different routing protocols in a many-to-one communication within a Vehicular Delay Tolerant Network (VDTN). Seven groups with three stationary sensor nodes sense the temperature, humidity and wind speed and send these data to a stationary destination node that collect them for statistical and data analysis purposes. Vehicles moving in Tirana city roads in Albania during the opportunistic contacts will exchange the sensed data to destination node. The simulations are conducted with the Opportunistic Network Environment (ONE) simulator. For the simulations we considered two different scenarios where the distance of the source nodes from the destination is short and long. For both scenarios the effect of node density, ttl and node movement model is evaluated. The performance is analyzed using delivery probability, overhead ratio, average latency, average number of hops and average buffer time metrics. The simulation results show that the increase of node density increases the delivery probability for all protocols and both scenarios, and better results are achieved when shortest-path map-based movement model is used. The increase of ttl slightly affects the performance of all protocols. By increasing the distance between source nodes and destination node, delivery probability is decreased almost 10% for all protocols, the overhead for sprayandwait protocol does not change, but for other protocols is slightly increased and the average number of hops and average latency is increased.Peer ReviewedPostprint (author's final draft

Ant colony system-based applications to electrical distribution system optimization

Chapter 16, February 201

Swarm-based Intelligent Routing (SIR) - a new approach for efficient routing in content centric delay tolerant networks

This paper introduces Swarm-based Intelligent Routing (SIR), a swarm intelligence based approach used for routing content in content centric Pocket Switched Networks. We first formalize the notion of optimal path in DTN, then introduce a swarm intelligence based routing protocol adapted to content centric DTN that use a publish/subscribe communication paradigm. The protocol works in a fully decentralized way in which nodes do not have any knowledge about the global topology. Nodes, via opportunistic contacts, update utility functions which synthesizes their spatio-temporal proximity from the content subscribers. This individual behavior applied by each node leads to the collective formation of gradient fields between content subscribers and content providers. Therefore, content routing simply sums up to follow the steepest slope along these gradient fields to reach subscribers who are located at the minima of the field. Via real traces analysis and simulation, we demonstrate the existence and relevance of such gradient field and show routing performance improvements when compared to classical routing protocols previously defined for information routing in DTN