Resource allocation and scalability in dynamic wavelength-routed optical networks.

This thesis investigates the potential benefits of dynamic operation of wavelength-routed optical networks (WRONs) compared to the static approach. It is widely believed that dynamic operation of WRONs would overcome the inefficiencies of the static allocation in improving resource use. By rapidly allocating resources only when and where required, dynamic networks could potentially provide the same service that static networks but at decreased cost, very attractive to network operators. This hypothesis, however, has not been verified. It is therefore the focus of this thesis to investigate whether dynamic operation of WRONs can save significant number of wavelengths compared to the static approach whilst maintaining acceptable levels of delay and scalability. Firstly, the wavelength-routed optical-burst-switching (WR-OBS) network architecture is selected as the dynamic architecture to be studied, due to its feasibility of implementation and its improved network performance. Then, the wavelength requirements of dynamic WR-OBS are evaluated by means of novel analysis and simulation and compared to that of static networks for uniform and non-uniform traffic demand. It is shown that dynamic WR-OBS saves wavelengths with respect to the static approach only at low loads and especially for sparsely connected networks and that wavelength conversion is a key capability to significantly increase the benefits of dynamic operation. The mean delay introduced by dynamic operation of WR-OBS is then assessed. The results show that the extra delay is not significant as to violate end-to-end limits of time-sensitive applications. Finally, the limiting scalability of WR-OBS as a function of the lightpath allocation algorithm computational complexity is studied. The trade-off between the request processing time and blocking probability is investigated and a new low-blocking and scalable lightpath allocation algorithm which improves the mentioned trade-off is proposed. The presented algorithms and results can be used in the analysis and design of dynamic WRONs

As Seen on TV: Programming Cinema and Entertainment in Italy in the Long 1980s.

Between 1974 and 1976 the Italian Constitutional Court allowed the development of private television channels in Italy. The progressive emergence of the financial holding company Fininvest’s television channels and the ensuing stiff competition with the state broadcaster RAI from the mid-1970s to the early 1990s, a period I define as “the long 1980s,” was a decisive moment not only for the television market, but also for Italy’s cultural and economic history. The ruling by Italy’s highest court opened up new and unprecedented opportunities for private enterprises, and within a few years profoundly affected Italians’ relationship to the television medium, film viewership, and cultural consumption. The domain of the competition for film programming became an important element in the battle for the acquisition of audiences between RAI and Fininvest’s channels. In my dissertation, I focus on the interdependent relationships between cinema and television in Italy during the long 1980s, from the emergence of private local networks and their transformation to national networks, and the ensuing vertiginous rise in film programming, to the introduction of pay-per-view. At the center of my work is a particular practice of programming, which amounted to what I refer to as habit-forming flow, since programmers successfully juxtaposed films and other programs, together with announcements, trailers, and commercials in order to inform the viewing and material consumption habits of the audience. I contend it is the programming as a whole, and not just individual programs, that had a crucial role in shaping these habits and creating new narrative structures. In particular, during the long 1980s, the implementation of the television habit-forming flow informed, and, at the same time was influenced by, a period of profound political, social, and economic transformations. More individualist lifestyles were emerging throughout Italy also thanks to an innovative television programming and its objective to spread more personalized forms of viewing and material consumption. The substantial rise in television film programming through the advent of private television, along with the creation of a habit-forming flow, brought about significant cultural changes in the long 1980s that inspired new consumption practices and narrative formats in Italy.PhDRomance Languages and Literatures: ItalianUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120671/1/mbeghe_1.pd

Multi-User Entanglement Distribution in Quantum Networks Using Multipath Routing

Quantum networks facilitate numerous applications including secure communication and distributed quantum computation by performing entanglement distribution. For some multi-user quantum applications access to a shared multipartite state is required. We consider the problem of designing protocols for distributing such states, at an increased rate. For this, we propose three protocols that leverage multipath routing to increase the distribution rate for multi-user applications. The protocols are evaluated on quantum networks with NISQ constraints, including limited quantum memories and probabilistic entanglement generation. Simulation results show that the developed protocols achieve an exponential increase in the distribution rate of multipartite states compared to single path routing techniques, with a maximum increase of four orders of magnitude for the cases studied. Further, the relative increase in distribution rate was also found to improve for larger sets of users. When the protocols were tested in scaled-down real-world topologies, it was found that topology had a significant effect on the multipartite state distribution rates achieved by the protocols. Finally, we found that the benefits of multipath routing are maximum for short quantum memory decoherence times and intermediate values of entanglement generation probability. Hence, the protocols developed can benefit NISQ quantum network control and design

Dynamic Optical Networks as Arcade Games: Lessons Learnt and Next Steps

We transformed the dynamic routing and spectrum allocation problem into an Arcade-like game and trained a reinforcement learning agent to play it. Preliminary results show the agent outperforms the K-SP-FF heuristic

Multi-User Entanglement Distribution in Quantum Networks Using Multipath Routing

Quantum networks facilitate numerous applications such as secure communication and distributed quantum computation by performing entanglement distribution. Multi-user quantum applications where quantum information is shared between multiple users require access to a shared multipartite state between the users. We consider the problem of designing protocols for distributing such states, at an increased entanglement rate. We propose three protocols that increase the entanglement rate of multi-user applications by leveraging multipath routing. The protocols are evaluated on quantum networks with NISQ constraints, including limited quantum memories and probabilistic entanglement generation. Monte Carlo simulation results show that the developed protocols achieve an exponential speedup of entanglement rate compared to single-path routing techniques, with a maximum speedup of four orders of magnitude for the cases studied. The speedup was also found to improve for larger sets of users. When the protocols were tested in scaled-down real-world topologies, it was found that topology can have a significant effect on the achievable entanglement rates, with one order of magnitude difference between topologies. Finally, we find that the benefits of multipath routing are a maximum for short quantum memory decoherence times, and intermediate values of entanglement generation probability. Hence the protocols developed can benefit NISQ quantum network control and design.Comment: 13 pages, 14 figure

Masked deep reinforcement learning for virtual network embedding on elastic optical networks

Deep reinforcement learning (DRL) with invalid action masking is applied to the optimization problem of virtual optical network embedding (VONE) over elastic optical networks (EON). Separate DRL agents are trained on the nodemapping task, link-mapping task, and overall VONE task. Their blocking probability performance is compared with a spectral fragmentation-aware VONE heuristic. All three DRL agents achieve lower blocking probability than the heuristic across low and high traffic loads

Multipartite state distribution for quantum networks with probabilistic entanglement generation and swapping

Quantum networks exchange quantum information by distributing entangled states which are used for applications such as secure communication and distributed quantum computation. Applications where quantum information must be shared between multiple users -such as distributed sensing and computing- require the distribution of shared multipartite states. Current shortest-path routing approaches for multipartite state distribution can only achieve an entanglement rate which decreases exponentially with the distance between users, and do not scale efficiently with the number of users. We develop new entanglement distribution protocols which utilise multipath routing to improve the achieved rate for distributing multipartite states. The protocols are evaluated on quantum networks with NISQ era constraints, such as probabilistic entanglement generation and error-prone qubit gate operations during entanglement swapping. Results show that the developed protocols achieve an exponential speedup of entanglement rate compared to single-path routing techniques. Further, it was found that non-ideal qubit gates had only a small effect on the entanglement rate speedup compared to the shortest-path techniques. Finally, the benefits of multipath routing are a maximum for intermediate values of entanglement generation probability. Hence, the protocols developed can benefit NISQ quantum network control and design

Effects of age on chemical composition and tenderness of muscle Longissimus thoracis of Martina Franca donkey breed.

The aim of this study was to determine the effects of age on chemical composition and tenderness of donkey meat. These characteristics were determined on Longissimus thoracis samples taken from 40 entire donkey males of Martina Franca breed slaughtered at 12 (Group 1, n = 20) and at 18 months (Group 2, n = 20) of age. Tenderness was evaluated at two and seven days post slaughter using a Warner-Bratzler shear force device. The chemical composition showed a signifycant increase in protein content (P < 0.05) in the meat of donkeys slaughtered at 18 months of age (22.3 g/100g) compared to the meat of younger animals (21.4 g/100g). Intramuscular fat content was significantly lower (P < 0.05) in Group 1 (2.41 g/100g) compared to Group 2 (3.71 g/100g). Shear force values at seven days post slaughter were significantly (P < 0.01) lower ((5.15 ± 0.31) kg/cm2) in Group 1 compared with the results obtained at two days post slaughter ((6.25 ± 0.53) kg/cm2). In Group 2 shear force values obtained seven days post mortem were higher ((5.88 ± 0.23) kg/cm2) compared with Group 1 after the same ageing period but significantly (P < 0.05) lower if compared with those ((6.53 ± 0.23) kg/cm2) determined in the same animals two days post slaugher