Design And Analysis Of Effective Routing And Channel Scheduling For Wavelength Division Multiplexing Optical Networks

Optical networking, employing wavelength division multiplexing (WDM), is seen as the technology of the future for the Internet. This dissertation investigates several important problems affecting optical circuit switching (OCS) and optical burst switching (OBS) networks. Novel algorithms and new approaches to improve the performance of these networks through effective routing and channel scheduling are presented. Extensive simulations and analytical modeling have both been used to evaluate the effectiveness of the proposed algorithms in achieving lower blocking probability, better fairness as well as faster switching. The simulation tests were performed over a variety of optical network topologies including the ring and mesh topologies, the U.S. Long-Haul topology, the Abilene high-speed optical network used in Internet 2, the Toronto Metropolitan topology and the European Optical topology. Optical routing protocols previously published in the literature have largely ignored the noise and timing jitter accumulation caused by cascading several wavelength conversions along the lightpath of the data burst. This dissertation has identified and evaluated a new constraint, called the wavelength conversion cascading constraint. According to this constraint, the deployment of wavelength converters in future optical networks will be constrained by a bound on the number of wavelength conversions that a signal can go through when it is switched all-optically from the source to the destination. Extensive simulation results have conclusively demonstrated that the presence of this constraint causes significant performance deterioration in existing routing and wavelength assignment (RWA) algorithms. Higher blocking probability and/or worse fairness have been observed for existing RWA algorithms when the cascading constraint is not ignored. To counteract the negative side effect of the cascading constraint, two constraint-aware routing algorithms are proposed for OCS networks: the desirable greedy algorithm and the weighted adaptive algorithm. The two algorithms perform source routing using link connectivity and the global state information of each wavelength. Extensive comparative simulation results have illustrated that by limiting the negative cascading impact to the minimum extent practicable, the proposed approaches can dramatically decrease the blocking probability for a variety of optical network topologies. The dissertation has developed a suite of three fairness-improving adaptive routing algorithms in OBS networks. The adaptive routing schemes consider the transient link congestion at the moment when bursts arrive and use this information to reduce the overall burst loss probability. The proposed schemes also resolve the intrinsic unfairness defect of existing popular signaling protocols. The extensive simulation results have shown that the proposed schemes generally outperform the popular shortest path routing algorithm and the improvement could be substantial. A two-dimensional Markov chain analytical model has also been developed and used to analyze the burst loss probabilities for symmetrical ring networks. The accuracy of the model has been validated by simulation. Effective proactive routing and preemptive channel scheduling have also been proposed to address the conversion cascading constraint in OBS environments. The proactive routing adapts the fairness-improving adaptive routing mentioned earlier to the environment of cascaded wavelength conversions. On the other hand, the preemptive channel scheduling approach uses a dynamic priority for each burst based on the constraint threshold and the current number of performed wavelength conversions. Empirical results have proved that when the cascading constraint is present, both approaches would not only decrease the burst loss rates greatly, but also improve the transmission fairness among bursts with different hop counts to a large extent

Effective preemptive scheduling scheme for optical burst-switched networks with cascaded wavelength conversion consideration

We introduce a new preemptive scheduling technique for next-generation optical burst switching (OBS) networks considering the impact of cascaded wavelength conversions. It has been shown that when optical bursts are transmitted all optically from source to destination, each wavelength conversion performed along the lightpath may cause certain signal-to-noise deterioration. If the distortion of the signal quality becomes significant enough, the receiver would not be able to recover the original data. Accordingly, subject to this practical impediment, we improve a recently proposed fair channel scheduling algorithm to deal with the fairness problem and aim at burst loss reduction simultaneously in OBS environments. In our scheme, the dynamic priority associated with each burst is based on a constraint threshold and the number of already conducted wavelength conversions among other factors for this burst. When contention occurs, a new arriving superior burst may preempt another scheduled one according to their priorities. Extensive simulation results have shown that the proposed scheme further improves fairness and achieves burst loss reduction as well

LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce

Livestream e-commerce integrates live streaming and online shopping, allowing viewers to make purchases while watching. However, effective marketing strategies remain a challenge due to limited empirical research and subjective biases from the absence of quantitative data. Current tools fail to capture the interdependence between live performances and feedback. This study identified computational features, formulated design requirements, and developed LiveRetro, an interactive visual analytics system. It enables comprehensive retrospective analysis of livestream e-commerce for streamers, viewers, and merchandise. LiveRetro employs enhanced visualization and time-series forecasting models to align performance features and feedback, identifying influences at channel, merchandise, feature, and segment levels. Through case studies and expert interviews, the system provides deep insights into the relationship between live performance and streaming statistics, enabling efficient strategic analysis from multiple perspectives.Comment: Accepted by IEEE VIS 202

Exploration of High Entropy Ceramics (HECs) with Computational Thermodynamics - A Case Study with LaMnO3±δ

The concept of the new category materials high entropy ceramics (HECs) has been proposed several years ago, which is directly borrowed from high entropy alloys (HEAs). It quickly attracts a lot of interests and displays promising properties. However, there is no clear definition of HECs differentiating it from HEAs, as it is still in its early research stage. In the current work, we are trying to use the classic perovskite LaMnO3±δ (LMO) to demonstrate the fundamental differences between HECs and HEAs. We have adopted the integrated defect chemistry and CALPHAD approach to investigate the mixing behavior and how it is affected by the control parameters, i.e. PO2, T, and composition. We have developed a new way to visualize the mixing behavior of the species including the cations, anions, and defects (vacancies), which linked the mixing behavior to the thermo-chemical properties including enthalpy, entropy, and Gibbs energy. It was found that entropy plays the most important role on the mixing behavior in LMO. The present work paves the way for the HECs investigation and the design of new HECs for the various applications

TPD52L2 as a potential prognostic and immunotherapy biomarker in clear cell renal cell carcinoma

BackgroundTumor Protein D52-Like 2 (TPD52L2) is a tumor-associated protein that participates in B-cell differentiation. However, the role of TPD52L2 in the pathological process of clear cell renal cell carcinoma (ccRCC) is unclear.MethodsMultiple omics data of ccRCC samples were obtained from public databases, and 5 pairs of ccRCC tissue samples were collected from the operating room. Wilcox, chi-square test, Kaplan-Meier method, receiver operating characteristic curve, regression analysis, meta-analysis, and correlation analysis were used to clarify the relationship of TPD52L2 with clinical features, prognosis, and immune microenvironment. Functional enrichment analysis was performed to reveal the potential pathways in which TPD52L2 participates in the progression of ccRCC. The siRNA technique was used to knockdown in the expression level of TPD52L2 in 786-O cells to verify its effect on ccRCC progression.ResultsFirst, TPD52L2 was found to be upregulated in ccRCC at both mRNA and protein levels. Second, TPD52L2 was significantly associated with poor prognosis and served as an independent prognostic factor. Moreover, TPD52L2 expression was regulated by DNA methylation, and some methylation sites were associated with ccRCC prognosis. Third, TPD52L2 overexpression may participate in the pathological process through various signaling pathways such as cytokine-cytokine receptor interactions, PI3K-Akt, IL-17, Wnt, Hippo signaling pathway, and ECM-receptor interactions. Interestingly, TPD52L2 expression level was also closely related to the abundance of various immune cells, immune checkpoint expression, and TMB. Finally, in vitro experiments confirmed that knocking down TPD52L2 can inhibit the proliferation, migration, and invasion abilities of ccRCC cells.ConclusionThis study for the first time revealed the upregulation of TPD52L2 expression in ccRCC, which is closely associated with poor prognosis of patients and is a potentially valuable therapeutic and efficacy assessment target for immunotherapy

Exploring the relationship between abnormally high expression of NUP205 and the clinicopathological characteristics, immune microenvironment, and prognostic value of lower-grade glioma

Nuclear pore complex (NPC) is a major transport pivot for nucleocytoplasmic molecule exchange. Nucleoporin 205 (NUP205)—a main component of NPC—plays a key regulatory role in tumor cell proliferation; however, few reports document its effect on the pathological progression of lower-grade glioma (LGG). Therefore, we conducted an integrated analysis using 906 samples from multiple public databases to explore the effects of NUP205 on the prognosis, clinicopathological characteristics, regulatory mechanism, and tumor immune microenvironment (TIME) formation in LGG. First, multiple methods consistently showed that the mRNA and protein expression levels of NUP205 were higher in LGG tumor tissue than in normal brain tissue. This increased expression was mainly noted in the higher WHO Grade, IDH-wild type, and 1p19q non-codeleted type. Second, various survival analysis methods showed that the highly expressed NUP205 was an independent risk indicator that led to reduced survival time of patients with LGG. Third, GSEA analysis showed that NUP205 regulated the pathological progress of LGG via the cell cycle, notch signaling pathway, and aminoacyl-tRNA biosynthesis. Ultimately, immune correlation analysis suggested that high NUP205 expression was positively correlated with the infiltration of multiple immune cells, particularly M2 macrophages, and was positively correlated with eight immune checkpoints, particularly PD-L1. Collectively, this study documented the pathogenicity of NUP205 in LGG for the first time, expanding our understanding of its molecular function. Furthermore, this study highlighted the potential value of NUP205 as a target of anti-LGG immunotherapy