A GP Hyper-Heuristic Approach for Generating TSP Heuristics

in 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019) (2019, May 20)

GP hyper-heuristic for the travelling salesman problem

Scientific Conference (2019, January 29)

A Memory-Based Label Propagation Algorithm for Community Detection

in Aiello, Luca Maria; Cherifi, Chantal; Cherifi, Hocine (Eds.) et al Complex Networks and Their Applications VII (2018, December 02)

The objective of a community detection algorithm is to group similar nodes in a network into communities, while increasing the dis- similarity between them. Several methods have been proposed but many of ... [more ▼]

The objective of a community detection algorithm is to group similar nodes in a network into communities, while increasing the dis- similarity between them. Several methods have been proposed but many of them are not suitable for large-scale networks because they have high complexity and use global knowledge. The Label Propagation Algorithm (LPA) assigns a unique label to every node and propagates the labels locally, while applying the majority rule to reach a consensus. Nodes which share the same label are then grouped into communities. Although LPA excels with near linear execution time, it gets easily stuck in local optima and often returns a single giant community. To overcome these problems we propose MemLPA, a novel LPA where each node imple- ments memory and the decision rule takes past states of the network into account. We demonstrate through extensive experiments on the Lancichinetti-Fortunato-Radicchi benchmark and a set of real-world net- works that MemLPA outperforms most of state-of-the-art community detection algorithms. [less ▲]

A Competitive Approach for Bi-Level Co-Evolution

in 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (2018, May 25)

On Standardised UAV Localisation and Tracking Systems in Smart Cities

Poster (2018, May)

In the near future, more than two thirds of the world’s population is expected to be living in cities and hence, with the aim of being proactive and finding innovative and sustainable solutions ... [more ▼]

In the near future, more than two thirds of the world’s population is expected to be living in cities and hence, with the aim of being proactive and finding innovative and sustainable solutions, governments have made smart cities one of their priority areas of research. Smart cities are sustainable, inclusive and prosperous greener cities that foster enabling smart Information and Communication Technologies (smart ICT) like Internet-of-Things (IoT), cloud computing and big data to facilitate services such as mobility, governance, utility and energy management. As these services depend heavily on data collected by sensors, Unmanned Aerial Vehicles (UAVs) have quickly become one of the promising IoT devices for smart cities thanks to their mobility, agility and customizability of onboard sensors. UAVs found use in a wide array of applications expanding beyond military to more commercial ones, ranging from monitoring, surveillance, mapping to parcel delivery and more demanding applications that require UAVs to operate in heterogeneous swarms in a shared low-altitude airspace over populated cities. However, as the number of UAVs continues to grow and as their sensing, actuation, communication and control capabilities become increasingly sophisticated, UAV deployment in smart cities is faced with a set of fundamental challenges in their safe operation and management. These challenges emphasize the need for establishing globally-harmonised regulations and internationally-agreed-upon technical standards to govern the rapid technological advancements, as well as ensure a fair economy by encouraging market competition and lowering barriers to entry for newcomers. As various Standardisation Development Organisations (SDOs) recently recognised the need, importance and potential of such regulations, most have established dedicated working groups addressing UAVs. However, most current SDO committees focus on aspects such as vehicle categorisation, specifications and operational procedures, but one usually overlooked elementary topic is UAV localisation. Due to its importance and close relation to other technical subsystems, the lack of a resilient, scalable and efficient standardised UAV localisation and tracking system is one of the main obstructing barriers hindering the integration and interoperability of UAV swarms in smart cities and hence impeding the realisation of their vast application benefits. In this work, we focus on studying the fundamental technical requirements, specifications and functions of such UAV localisation and tracking system, and explore its relationship to and importance in 1) optimising path planning, flight scheduling and utilising shared airspace, 2) collision avoidance and conflict resolution in highly populated residential areas and 3) addressing privacy and data protection concerns that could arise from UAV monitoring and surveillance applications. Furthermore, for each of the three aspects, we analyse current SDOs efforts such as those put forth by EASA, EUCARE WG73 and ISO TC20/SC16 on UAV systems, ISO JTC1/SC41 on IoT and related technologies and ISO JTC1/SC27, EU Directive 95/46 EC and GDPR on security, privacy and data protection, in order to identify and prioritise future research questions in relation to UAV localisation, aiming to make a contribution towards narrowing the gap between research and existing technical standards by encouraging multimode standardisation. This research was conducted in collaboration with ILNAS - the Institut Luxembourgeois de la Normalisation, de l’Accréditation, de la Sécurité et qualité des produits et services (ILNAS) under the authority of the Minister of Economy, Luxembourg. [less ▲]

Bayesian optimization to enhance coverage performance of a swarm of UAV with chaotic dynamics

Scientific Conference (2018, February 26)

We introduce the optimization of CACOC through Bayesian Optimization. CACOC is based on a chaotic system, i.e. Rossler system whose behavior can be modified by tuning the α parameter. In order to evaluate ... [more ▼]

We introduce the optimization of CACOC through Bayesian Optimization. CACOC is based on a chaotic system, i.e. Rossler system whose behavior can be modified by tuning the α parameter. In order to evaluate the performance of CACOC for different value of α, the coverage metric has to be evaluated after simulation. The latter is time-consuming. Therefore, a surrogate-based optimization, i.e. Bayesian Optimization has been privilegied to tackle this issue. An analysis of the chaotic system with the obtained α value has been performed to compare the periodic orbits and their associated patterns. Numerical results show that the best α value avoid a waste of time in periodic region of the bifurcation diagram. Future works will focus on more complex chaotic system as well as new application domain of the optimized CACOC approach. [less ▲]

Chaos-enhanced mobility models for multilevel swarms of UAVs

in Swarm and Evolutionary Computation (2018)

The number of civilian and military applications using Unmanned Aerial Vehicles (UAVs) has increased during the last years and the forecasts for upcoming years are exponential. One of the current major ... [more ▼]

The number of civilian and military applications using Unmanned Aerial Vehicles (UAVs) has increased during the last years and the forecasts for upcoming years are exponential. One of the current major challenges consist in considering UAVs as autonomous swarms to address some limitations of single UAV usage such as autonomy, range of operation and resilience. In this article we propose novel mobility models for multi-level swarms of collaborating UAVs used for the coverage of a given area. These mobility models generate unpredictable trajectories using a chaotic solution of a dynamical system. We detail how the chaotic properties are used to structure the exploration of an unknown area and enhance the exploration part of an Ant Colony Optimization method. Empirical evidence of the improvement of the coverage efficiency obtained by our mobility models is provided via simulation. It clearly outperforms state-of-the-art approaches. [less ▲]

Visualizing the Template of a Chaotic Attractor

in 26th International Symposium on Graph Drawing and Network Visualization (GD 2018) (2018)

Chaotic Traversal (CHAT): Very Large Graphs Traversal Using Chaotic Dynamics

in International Journal of Bifurcation and Chaos (2017), 27(14), 1750215

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first ... [more ▼]

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first stepping stone into knowledge extraction from the graph which is now a popular topic. Classical solutions such as Breadth First Search (BFS) and Depth First Search (DFS) require huge amounts of memory for exploring very large graphs. In this research, we present a novel memoryless graph traversal algorithm, Chaotic Traversal (CHAT) which integrates chaotic dynamics to traverse large unknown graphs via the Lozi map and the Rössler system. To compare various dynamics effects on our algorithm, we present an original way to perform the exploration of a parameter space using a bifurcation diagram with respect to the topological structure of attractors. The resulting algorithm is an efficient and nonresource demanding algorithm, and is therefore very suitable for partial traversal of very large and/or unknown environment graphs. CHAT performance using Lozi map is proven superior than the, commonly known, Random Walk, in terms of number of nodes visited (coverage percentage) and computation time where the environment is unknown and memory usage is restricted. [less ▲]

Area exploration with a swarm of UAVs combining deterministic Chaotic Ant Colony Mobility with position MPC

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, July 27)

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already ... [more ▼]

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already proposed a new mobility model using Ant Colony Algorithms combined with chaotic dynamics (CACOC) to enhance the coverage of an area by a swarm of UAVs. In this paper we propose to consider this mobility model as waypoints for real UAVs. A control model of the UAVs is deployed to test the efficiency of the coverage of an area by the swarm. We have tested our approach in a realistic robotics simulator (V-Rep) which is connected with ROS. We compare the performance in terms of coverage using several metrics to ensure that this mobility model is efficient for real UAVs. [less ▲]