Julien Schleich

UAV fleet area coverage with network connectivity constraint

An Unmanned Aerial Vehicle (UAV) is an aircraft without onboard human pilot, which motion can be remotely and / or autonomously controlled. Using multiple UAVs, i.e. a fleet, offers various advantages compared to the single UAV scenario, such as longer mission duration, bigger mission area or the load balancing of the mission payload. For collaboration purposes, it is assumed that the UAVs are equipped with ad hoc communication capabilities and thus form a special case of mobile ad hoc networks. However, the coordination of one or more fleets of UAVs, in order to fulfill collaborative missions, raises multiples issues in particular when UAVs are required to act in an autonomous fashion. Thus, we propose a decentralised and localised algorithm to control the mobility of the UAVs. This algorithm is designed to perform surveillance missions with network connectivity constraints, which are required in most practical use cases for security purposes as any UAV should be able to be contacted at any moment in case of an emergency. The connectivity is maintained via a tree-based overlay network, which root is the base station of the mission, and created by predicting the future positions of one-hop neighbours. This algorithm is compared to the state of the art contributions by introducing new quality metrics to quantify different aspect of the area coverage process (speed, exhaustivity and fairness). Numerical results obtained via simulations show that the maintenance of the connectivity has a slight negative impact on the coverage performances while the connectivity performances are significantly better.

Solving the minimum M-dominating set problem by a continuous optimization approach based on DC programming and DCA

We propose a new optimization approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) to the so-called Minimum M-Dominating Set problem in graphs. This problem is beforehand re-casted as a polyhedral DC program with the help of exact penalty in DC programming. The related DCA is original and computer efficient because it consists of solving a few linear programs and converges after a finite number of iterations to an integer solution while working in a continuous domain. Numerical simulations show the efficiency and robustness of DCA and its superiority with respect to standard methods.

Minimising longest path length in communication satellite payloads via metaheuristics

The size and complexity of communication satellite payloads have been increasing very quickly over the last years and their configuration / reconfiguration have become very difficult problems. In this work, we propose to compare the efficiency of three well-known metaheuristic methods to solve an initial configuration problem, which objective is to minimise the length of the longest channel path. Experiments are conducted on real-world problem instances with realistic operational constraints (e.g., a maximum computation time of 10 minutes) and Wilcoxon test is used to determine with statistical confidence what technique is more suitable and what are its limitations. The results of this work will serve as an initial step in our research to design hybrid approaches to push even further the solving capabilities, i.e., tackling bigger payloads and more channels to activate.

Blackbone2, an efficient deterministic algorithm for creating 2-connected m-dominating set-based backbones in ad hoc networks

This paper introduces Blackbone2, a novel fully decentralized algorithm that aims at creating a robust backbone in ad hoc networks. Backbone robustness is supported by a 2-Connected m-dominating Set, 2,m-CDS, and decentralization relies on the usage of two rules that only require two-hop knowledge in order to reduce the use of bandwidth. Blackbone2 deterministic approach guarantees a density-indpendent valid solution and is proved correct. The algorithm is also characterized by its efficient theoretical computation time, Ο(Δ2) with Δ the average number of neighbors, which outperforms known solutions. The domination parameter, m, can be increased without changing the theoretical computation time. Efficiency of the Blackbone2 algorithm compared to the equivalent literature solutions is illustrated through simulations of a large panel of networks with a wide density range.

An overlay approach for optimising small-world properties in VANETs

Advantages of bringing small-world properties in mobile ad hoc networks (MANETs) in terms of quality of service has been studied and outlined in the past years. In this work, we focus on the specific class of vehicular ad hoc networks (VANETs) and propose to un-partition such networks and improve their small-world properties. To this end, a subset of nodes, called injection points, is chosen to provide backend connectivity and compose a fully-connected overlay network. The optimisation problem we consider is to find the minimal set of injection points to constitute the overlay that will optimise the small-world properties of the resulting network, i.e., (1) maximising the clustering coefficient (CC) so that it approaches the CC of a corresponding regular graph and (2) minimising the difference between the average path length (APL) of the considered graph and the APL of corresponding random graphs. In order to face this new multi-objective optimisation problem, the NSGAII algorithm was used on realistic instances in the city-centre of Luxembourg. The accurate tradeoff solutions found by NSGAII (assuming global knowledge of the network) will permit to better know and understand the problem. This will later ease the design of decentralised solutions to be used in real environments, as well as their future validation.

On quantifying the quality of CDS-based virtual backbones in mobile ad hoc networks

We propose to study the quality of CDS-based virtual backbones generated by fully distributed algorithms in mobile environments. As virtual-backbones may be used for different purposes, the importance of a characteristic may vary accordingly. In order to deal with this variety issue, we provide a set of quality criteria quantifying different suitable aspects for virtual backbones in mobile ad hoc networks. Distributed and localized algorithms are then compared through simulations with respect to these measures and criterion-specific optimizations are proposed for the Blackbone2 algorithm.

Optimising small-world properties in VANETs: Centralised and distributed overlay approaches

Advantages of bringing small-world properties in mobile ad hoc networks (MANETs) in terms of quality of service has been studied and outlined in the past years. In this work, we focus on the specific class of vehicular ad hoc networks (VANETs) and propose to un-partition such networks and improve their small-world properties. To this end, a subset of nodes, called injection points, is chosen to provide backend connectivity and compose a fully-connected overlay network. The optimisation problem we consider is to find the minimal set of injection points to constitute the overlay that will optimise the small-world properties of the resulting network, i.e., (1) maximising the clustering coefficient (CC) so that it approaches the CC of a corresponding regular graph and (2) minimising the difference between the average path length (APL) of the considered graph and the APL of corresponding random graphs. Two accurate evolutionary algorithms (namely, NSGAII and MOCHC) are used to find an upper-bound of high quality solutions to this new multi-objective optimisation problem, on realistic instances in the city-centre of Luxembourg. The obtained sets of solutions are then used to assess the performance of five novel heuristics proposed to solve the problem, i.e., two centralised and three decentralised. The results provided by these heuristics turned out to be extremely accurate with respect to the solutions found by the evolutionary algorithms.

Enhancing the broadcast process in mobile ad hoc networks using community knowledge

Unmanned Aerial Vehicle (UAV) networks can be consid- ered as a kind of mobile ad hoc network. One of the most important goals in UAV networks is to achieve a powerful collaborative fleet. For that, efficient communication pro- tocols are needed. In this paper, we are proposing a new energy efficient broadcasting algorithm, CEDBBT, that is making use of community knowledge to enhance the perfor- mance of the dissemination process. Additionally, a hybrid multi-objective algorithm, CellDE, is used to optimize the configuration parameters of this broadcasting protocol. The optimization is done by maximizing the coverage achieved and minimizing at the same time both, energy consumption and the broadcast time. Results show the improvement ob- tained in the performance of the broadcasting process, as well as, a wide range of solutions for the configuration of CEDBBT that outperforms the original setting.