An Efficient Algorithm for Congestion Control in Highly Loaded DiffServ/MPLS Networks

Optimal QoS path provisioning of coexisted and aggregated traffic in networks is still demanding problem. All traffic flows in a domain are distributed among LSPs (Label Switching Path) related to N service classes, but the congestion problem of concurrent flows can appear. As we know the IGP (Interior Getaway Protocol) uses simple on-line routing algorithms (e.g. OSPFS, IS-IS) based on shortest path methodology. In QoS end-to-end provisioning where some links may be reserved for certain traffic classes (for particular set of users) it becomes insufficient technique. On other hand, constraint-based explicit routing (CR) based on IGP metric ensures traffic engineering (TE) capabilities. But in overloaded and poorly connected MPLS/DiffServ networks the CR becomes insufficient technique. As we need firm correlation with bandwidth management and traffic engineering (TE) the initial (pro-active) routing can be pre-computed in the context of all priority traffic flows (former contracted SLAs) traversing the network simultaneously. It mean that LSP can be pre-computed much earlier, possibly during SLA (Service Level Agreement) negotiation process. In the paper a new load simulation technique for load balancing control purpose is proposed. The algorithm proposed in the paper may find a longer but lightly loaded path, better than the heavily loaded shortest path. It could be a very good solution for congestion avoidance and for better load-balancing purpose where links are running close to capacity. Also, such technique could be useful in inter-domain end-to-end provisioning, where bandwidth reservation has to be negotiated with neighbor ASes (Autonomous System). To be acceptable for real applications such complicated routing algorithm can be significantly improved. Algorithm was tested on the network of M core routers on the path (between edge routers) and results are given for N=3 service classes. Further improvements through heuristic approach are made and results are discussed

Multivariable PID controller synthesis for coupled mechanical systems via linear matrix inequality approach

Završni rad pokušat će prvotno predstaviti matematički pristup regulaciji primjenom linearnih matričnih nejednadžbi (LMN), odnosno optimizacijskim problemima s konveksnim ograničenjima, i to s posebnim naglaskom na H_beskonačno stabilizaciju. Razmatraju se dosadašnje spoznaje LMN-a u teoriji regulacije te se navode i obrađuju optimizacijski alati, posebice metoda unutarnje točke za njihovo rješavanje. Vrhunac takvog teorijskog razmatranja bit će PID regulacija. Sekundarno, iznjedriti će se na isti način sinteza PID regulatora mehaničkog nelinearnog sustava sastavljenog od dva elastično spregnuta mehanička podsustava. Pristupit će se pritom linearnim matričnim nejednadžbama, budući da danas predstavljaju jedan od glavnih smjerova napretka u sličnim primjenama. Štoviše, koristeći dosadašnje spoznaje disipativnih sustava, koncept će se temeljiti na lemi ograničene realnosti (eng. bounded-real lemma), odnosno oslanjanju na H_boskonačno normu prijenosne funkcije.This thesis will attempt firstly to present mathematical approach to the synthesis of controllers based on Linear Matrix Inequalities (LMI), and more so H_infinity stabilization. Current acknowledgements of LMI-s, or generally constrained optimization in control synthesis, as well as modern optimization tools, including interior-point method for finding their solutions shall be discussed. The peak of such theoretical considerations shall be PID control. Secondly, PID controller synthesis of the mechanical nonlinear system incorporated by two elastically interconnected subsystems shall be derived accordingly. LMI approach will be taken as it represents one of the most important niches of modern optimal control theory. Furthermore, taking in to account current knowledge of dissipative systems, concept will be based on bounded-real lemma and H_infinity norm of the transfer function

Software package for optimal data-based control of linear dynamical systems

Rad će prvotno predstaviti bihevioralni pristup teoriji upravljanja, kao polazišnu točku „data-based“ sinteze na temelju tzv. fundamentalne leme. Kao jedan od modernijih primjena bit će naglašeno optimalno prediktivno upravljanje na temelju podataka, kao alternativa klasičnom Modelskom prediktivnom upravljanju (eng. Model Predictive Control - MPC). Na većem broju primjera će se pokazati sažetost identifikacije sustava na temelju fundamentalne leme, te će se na bazi simulacija usporediti s istom temeljenom na modelu. Sekundarno, razvit će se algoritam koji za proizvoljni diskretni linearni vremenski-invarijantni sustav u prostoru stanja, za proizvoljnu referentnu trajektoriju, korak diskretizacije i težinske parametre, na temelju offline podataka generira vektorski prostor svih mogućih trajektorija sustava, te online identificira inicijalno stanja poznavanjem prethodnih izlaza, nakon kojeg slijedi generiranje optimalne trajektorije na pomičnom horizontu - DeePC (eng. Data-enabled predictive control) algoritam. Dodatno, u navedeni algoritam bit će integrirano i robusno djelovanje, na temelju regularizacijskih varijabli u funkciji cilja (robustifikacija), s namjerom da se obuhvate i nesigurnosti u identificiranom modelu, primjerice zbog utjecaja šuma. Pokazat će se i uvjeti na garanciju performansi takvog robusnog djelovanja.The thesis will firstly present behavioural approach to control theory, as a beginning setpoint for data-based synthesis based on fundamental lemma. As one of the more modern approaches, the emphasis will be on predictive optimal control based on data, as an alternative to Model predictive control (MPC). The simplicity of system identification based on fundamental lemma will be shown on more examples, and the comparison with model-based identification will be made. Secondly, the thesis shall develop an algorithm that, for a given arbitrary controllable linear time-invariant (LTI) discrete system in state space, reference trajectory and tuning parameters, generates the span of vector space of all possible system trajectories of a system based on offline data, identifies an initial state based on online measurements, and produces an optimal trajectory on finite horizon – DeePC (Data-enabled predictive control). Additionally, a robust control based on regularization variables in cost function (robustification) will be integrated into the algorithm, with a goal of covering the uncertainty in identified model, for example caused by noise. The performance guarantees for such robust control will be given

Yeast-Derived Nucleotides Enhance Fibroblast Migration and Proliferation and Provide Clinical Benefits in Atopic Dermatitis

Nucleotides, glycosaminoglycans, and omega-3 essential fatty acids (O3s) could be used for improving skin health, although their modes of action, alone or in combination, are not yet fully understood. To gain some insight into these mechanisms, we performed two in vitro tests and one in vivo pilot trial. The effects on human dermal fibroblast proliferation and migration were evaluated with the following compounds and combinations: 0.156 mg/mL O3s, 0.0017 mg/mL hyaluronic acid (HA), 0.0004 mg/mL dermatan sulfate (DS), 0.0818 mg/mL nucleotides, and [O3s + HA + DS] and [O3s + HA + DS + nucleotides] at the same concentrations. In both in vitro assays, adding nucleotides to [O3s + HA + DS] provided significant improvements. The resulting combination [O3s + HA + DS + nucleotides] was then tested in vivo in dogs with atopic dermatitis by oral administration of a supplement providing a daily amount of 40 mg/kg nucleotides, 0.9 mg/kg HA, 0.18 mg/kg DS, 53.4 mg/kg EPA, and 7.6 mg/kg DHA. After 30 days, the pruritus visual analog scale (pVAS) score was significantly reduced, and no adverse effects were observed. In conclusion, the combination of nucleotides plus glycosaminoglycans and O3s could serve as a useful therapeutic alternative in skin health applications