Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

Modelling mixed autonomy traffic networks with pricing and routing control

Connected and automated vehicles (CAVs) are expected to change the way people travel in cities. Before human-driven vehicles (HVs) are completely phased out, the urban traffic flow will be heterogeneous of HVs, CAVs, and public transport vehicles commonly known as mixed autonomy. Mixed autonomy networks are likely to be made up of different route choice behaviours compared with conventional networks with HVs only. While HVs are expected to continue taking individually and selfishly selected shortest paths following user equilibrium (UE), a set of centrally controlled AVs could potentially follow the system optimal (SO) routing behaviour to reduce the selfish and inefficient behaviour of UE-seeking HVs. In this dissertation, a mixed equilibrium simulation-based dynamic traffic assignment (SBDTA) model is developed in which two classes of vehicles with different routing behaviours (UE-seeking HVs and SO-seeking AVs) are present in the network. The dissertation proposes a joint routing and incentive-based congestion pricing scheme in which SO-seeking CAVs are exempt from the toll while UE-seeking HVs have their usual shortest-path routing decisions are subject to a spatially differentiated congestion charge. This control strategy could potentially boost market penetration rate of CAVs while encouraging them to adopt SO routing behaviour and discouraging UE-seeking users from entering congested areas. The dissertation also proposes a distance-based time-dependent optimal ratio control scheme (TORCS) in which an optimal ratio of CAVs is identified and selected to seek SO routing. The objective of the control scheme is to achieve a reasonable compromise between the system efficiency (i.e., total travel time savings) and the control cost that is proportional to the total distance travelled by SO-seeking AVs. The proposed modelling frameworks are then extended to bi-modal networks considering three competing modes (bus, SO-seeking CAVs, and UE-seeking HVs). A nested logit-based mode choice model is applied to capture travellers’ preferences toward three available modes and elasticity in travel demand. A dynamic transit assignment model is also deployed and integrated into the mixed equilibrium SBDTA model to generate equilibrium traffic flow under different scenarios. The applicability and performance of the proposed models are demonstrated on a real large-scale network of Melbourne, Australia. The research outcomes are expected to improve the performance of mixed autonomy traffic networks with optimal pricing and routing control

Performance and reliability modelling of computing systems using spectral expansion

PhD ThesisThis thesis is concerned with the analytical modelling of computing and other discrete event systems, for steady state performance and dependability. That is carried out using a novel solution technique, known as the spectral expansion method. The type of problems considered, and the systems analysed, are represented by certain two-dimensional Markov-processes on finite or semi-infinite lattice strips. A sub set of these Markov processes are the Quasi-Birth-and-Death processes. These models are important because they have wide ranging applications in the design and analysis of modern communications, advanced computing systems, flexible manufacturing systems and in dependability modelling. Though the matrixgeometric method is the presently most popular method, in this area, it suffers from certain drawbacks, as illustrated in one of the chapters. Spectral expansion clearly rises above those limitations. This also, is shown with the aid of examples. The contributions of this thesis can be divided into two categories. They are, • The theoretical foundation of the spectral expansion method is laid. Stability analysis of these Markov processes is carried out. Efficient numerical solution algorithms are developed. A comparative study is performed to show that the spectral expansion algorithm has an edge over the matrix-geometric method, in computational efficiency, accuracy and ease of use. • The method is applied to several non-trivial and complicated modelling problems, occuring in computer and communication systems. Performance measures are evaluated and optimisation issues are addressed

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform