MACS: deep reinforcement learning based SDN controller synchronization policy design

In distributed software-defined networks (SDN), multiple physical SDN controllers, each managing a network domain, are implemented to balance centralised control, scalability, and reliability requirements. In such networking paradigms, controllers synchronize with each other, in attempts to maintain a logically centralised network view. Despite the presence of various design proposals for distributed SDN controller architectures, most existing works only aim at eliminating anomalies arising from the inconsistencies in different controllers' network views. However, the performance aspect of controller synchronization designs with respect to given SDN applications are generally missing. To fill this gap, we formulate the controller synchronization problem as a Markov decision process (MDP) and apply reinforcement learning techniques combined with deep neural networks (DNNs) to train a smart, scalable, and fine-grained controller synchronization policy, called the Multi-Armed Cooperative Synchronization (MACS), whose goal is to maximise the performance enhancements brought by controller synchronizations. Evaluation results confirm the DNN's exceptional ability in abstracting latent patterns in the distributed SDN environment, rendering significant superiority to MACS-based synchronization policy, which are 56% and 30% performance improvements over ONOS and greedy SDN controller synchronization heuristics

Let's share: a game-theoretic framework for resource sharing in mobile edge clouds

Mobile edge computing seeks to provide resources to different delay-sensitive applications. This is a challenging problem as an edge cloud-service provider may not have sufficient resources to satisfy all resource requests. Furthermore, allocating available resources optimally to different applications is also challenging. Resource sharing among different edge cloud-service providers can address the aforementioned limitation as certain service providers may have resources available that can be “rented” by other service providers. However, edge cloud service providers can have different objectives or utilities . Therefore, there is a need for an efficient and effective mechanism to share resources among service providers, while considering the different objectives of various providers. We model resource sharing as a multi-objective optimization problem and present a solution framework based on Cooperative Game Theory (CGT). We consider the strategy where each service provider allocates resources to its native applications first and shares the remaining resources with applications from other service providers. We prove that for a monotonic, non-decreasing utility function, the game is canonical and convex. Hence, the core is not empty and the grand coalition is stable. We propose two algorithms, Game-theoretic Pareto optimal allocation (GPOA) and Polyandrous-Polygamous Matching based Pareto Optimal Allocation (PPMPOA) that provide allocations from the core. Hence the obtained allocations are Pareto optimal and the grand coalition of all the service providers is stable. Experimental results confirm that our proposed resource sharing framework improves utilities of edge cloud-service providers and application request satisfaction

TCF7L2 gene polymorphisms do not predict susceptibility to diabetes in tropical calcific pancreatitis but may interact with SPINK1 and CTSB mutations in predicting diabetes

<p>Abstract</p> <p>Background</p> <p>Tropical calcific pancreatitis (TCP) is a type of chronic pancreatitis unique to developing countries in tropical regions and one of its important features is invariable progression to diabetes, a condition called fibro-calculous pancreatic diabetes (FCPD), but the nature of diabetes in TCP is controversial. We analysed the recently reported type 2 diabetes (T2D) associated polymorphisms in the <it>TCF7L2 </it>gene using a case-control approach, under the hypothesis that <it>TCF7L2 </it>variants should show similar association if diabetes in FCPD is similar to T2D. We also investigated the interaction between the <it>TCF7L2 </it>variants and N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations, since they are strong predictors of risk for TCP.</p> <p>Methods</p> <p>Two polymorphisms rs7903146 and rs12255372 in the <it>TCF7L2 </it>gene were analyzed by direct sequencing in 478 well-characterized TCP patients and 661 healthy controls of Dravidian and Indo-European ethnicities. Their association with TCP with diabetes (FCPD) and without diabetes was tested in both populations independently using chi-square test. Finally, a meta analysis was performed on all the cases and controls for assessing the overall significance irrespective of ethnicity. We dichotomized the whole cohort based on the presence or absence of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations and further subdivided them into TCP and FCPD patients and compared the distribution of <it>TCF7L2 </it>variants between them.</p> <p>Results</p> <p>The allelic and genotypic frequencies for both <it>TCF7L2 </it>polymorphisms, did not differ significantly between TCP patients and controls belonging to either of the ethnic groups or taken together. No statistically significant association of the SNPs was observed with TCP or FCPD or between carriers and non-carriers of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations. The minor allele frequency for rs7903146 was different between TCP and FCPD patients carrying the N34S <it>SPINK1 </it>variant but did not reach statistical significance (OR = 1.59, 95% CI = 0.93–2.70, P = 0.09), while, <it>TCF7L2</it><it/>variant showed a statistically significant association between TCP and FCPD patients carrying the 26V allele (OR = 1.69, 95% CI = 1.11–2.56, P = 0.013).</p> <p>Conclusion</p> <p>Type 2 diabetes associated <it>TCF7L2 </it>variants are not associated with diabetes in TCP. Since, <it>TCF7L2 </it>is a major susceptibility gene for T2D, it may be hypothesized that the diabetes in TCP patients may not be similar to T2D. Our data also suggests that co-existence of <it>TCF7L2 </it>variants and the <it>SPINK1 </it>and <it>CTSB </it>mutations, that predict susceptibility to exocrine damage, may interact to determine the onset of diabetes in TCP patients.</p

Alterations in Vitamin D signalling and metabolic pathways in breast cancer progression: a study of VDR, CYP27B1 and CYP24A1 expression in benign and malignant breast lesions Vitamin D pathways unbalanced in breast lesions

<p>Abstract</p> <p>Background</p> <p>Breast cancer is a heterogeneous disease associated with different patient prognosis and responses to therapy. Vitamin D has been emerging as a potential treatment for cancer, as it has been demonstrated that it modulates proliferation, apoptosis, invasion and metastasis, among others. It acts mostly through the Vitamin D receptor (VDR) and the synthesis and degradation of this hormone are regulated by the enzymes CYP27B1 and CYP24A1, respectively. We aimed to study the expression of these three proteins by immunohistochemistry in a series of breast lesions.</p> <p>Methods</p> <p>We have used a cohort comprising normal breast, benign mammary lesions, carcinomas <it>in situ </it>and invasive carcinomas and assessed the expression of the VDR, CYP27B1 and CYP24A1 by immunohistochemistry.</p> <p>Results</p> <p>The results that we have obtained show that all proteins are expressed in the various breast tissues, although at different amounts. The VDR was frequently expressed in benign lesions (93.5%) and its levels of expression were diminished in invasive tumours (56.2%). Additionally, the VDR was strongly associated with the oestrogen receptor positivity in breast carcinomas. CYP27B1 expression is slightly lower in invasive carcinomas (44.6%) than in benign lesions (55.8%). In contrast, CYP24A1 expression was augmented in carcinomas (56.0% in <it>in situ </it>and 53.7% in invasive carcinomas) when compared with that in benign lesions (19.0%).</p> <p>Conclusions</p> <p>From this study, we conclude that there is a deregulation of the Vitamin D signalling and metabolic pathways in breast cancer, favouring tumour progression. Thus, during mammary malignant transformation, tumour cells lose their ability to synthesize the active form of Vitamin D and respond to VDR-mediated Vitamin D effects, while increasing their ability to degrade this hormone.</p

Pretreatment Serum Concentrations of 25-Hydroxyvitamin D and Breast Cancer Prognostic Characteristics: A Case-Control and a Case-Series Study

Results from epidemiologic studies on the relationship between vitamin D and breast cancer risk are inconclusive. It is possible that vitamin D may be effective in reducing risk only of specific subtypes due to disease heterogeneity.In case-control and case-series analyses, we examined serum concentrations of 25-hydroxyvitamin D (25OHD) in relation to breast cancer prognostic characteristics, including histologic grade, estrogen receptor (ER), and molecular subtypes defined by ER, progesterone receptor (PR) and HER2, among 579 women with incident breast cancer and 574 controls matched on age and time of blood draw enrolled in the Roswell Park Cancer Institute from 2003 to 2008. We found that breast cancer cases had significantly lower 25OHD concentrations than controls (adjusted mean, 22.8 versus 26.2 ng/mL, p<0.001). Among premenopausal women, 25OHD concentrations were lower in those with high- versus low-grade tumors, and ER negative versus ER positive tumors (p≤0.03). Levels were lowest among women with triple-negative cancer (17.5 ng/mL), significantly different from those with luminal A cancer (24.5 ng/mL, p = 0.002). In case-control analyses, premenopausal women with 25OHD concentrations above the median had significantly lower odds of having triple-negative cancer (OR = 0.21, 95% CI = 0.08-0.53) than those with levels below the median; and every 10 ng/mL increase in serum 25OHD concentrations was associated with a 64% lower odds of having triple-negative cancer (OR = 0.36, 95% CI = 0.22-0.56). The differential associations by tumor subtypes among premenopausal women were confirmed in case-series analyses.In our analyses, higher serum levels of 25OHD were associated with reduced risk of breast cancer, with associations strongest for high grade, ER negative or triple negative cancers in premenopausal women. With further confirmation in large prospective studies, these findings could warrant vitamin D supplementation for reducing breast cancer risk, particularly those with poor prognostic characteristics among premenopausal women

Anisotropic nanomaterials: structure, growth, assembly, and functions

Comprehensive knowledge over the shape of nanomaterials is a critical factor in designing devices with desired functions. Due to this reason, systematic efforts have been made to synthesize materials of diverse shape in the nanoscale regime. Anisotropic nanomaterials are a class of materials in which their properties are direction-dependent and more than one structural parameter is needed to describe them. Their unique and fine-tuned physical and chemical properties make them ideal candidates for devising new applications. In addition, the assembly of ordered one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) arrays of anisotropic nanoparticles brings novel properties into the resulting system, which would be entirely different from the properties of individual nanoparticles. This review presents an overview of current research in the area of anisotropic nanomaterials in general and noble metal nanoparticles in particular. We begin with an introduction to the advancements in this area followed by general aspects of the growth of anisotropic nanoparticles. Then we describe several important synthetic protocols for making anisotropic nanomaterials, followed by a summary of their assemblies, and conclude with major applications

Optimization framework with reduced complexity for sensor networks with in-network processing.

We propose a framework for optimizing in-network processing (INP) in wireless sensor networks. INP provides a platform for processing (e.g., fusing, aggregating or compressing) the data along the transmission routes in the sensor network. This can reduce the volume of transmitted data, therefore optimizing the utilization of energy and bandwidth. However, such data processing must ensure that the end result can meet given QoI requirements. We formulate the QoI-aware INP problem as a non-linear optimization problem to identify the optimal degree of data compression at each sensor node subject to satisfying a QoI requirement for the end-user. The formulation arranges all involved sensor nodes in a tree where data is transfered and processed from nodes to their parent nodes toward the root node of the tree. Under the assumption of uniform parameter setting, we show that the processing tree can be collapsed into a linear graph where the number of nodes represents the node levels of the original processing tree. This represents a significant reduction in complexity of the problem. Numerical example are provided to illustrate the performance of the proposed approach

Network capability in localizing node failures via end-to-end path measurements

We investigate the capability of localizing node failures in communication networks from binary states (normal/failed) of end-to-end paths. Given a set of nodes of interest, uniquely localizing failures within this set requires that different observable path states associate with different node failure events. However, this condition is difficult to test on large networks due to the need to enumerate all possible node failures. Our first contribution is a set of sufficient/necessary conditions for identifying a bounded number of failures within an arbitrary node set that can be tested in polynomial time. In addition to network topology and locations of monitors, our conditions also incorporate constraints imposed by the probing mechanism used. We consider three probing mechanisms that differ according to whether measurement paths are: (i) arbitrarily controllable; (ii) controllable but cycle-free; or (iii) uncontrollable (determined by the default routing protocol). Our second contribution is to quantify the capability of failure localization through: 1) the maximum number of failures (anywhere in the network) such that failures within a given node set can be uniquely localized and 2) the largest node set within which failures can be uniquely localized under a given bound on the total number of failures. Both measures in 1) and 2) can be converted into the functions of a per-node property, which can be computed efficiently based on the above sufficient/necessary conditions. We demonstrate how measures 1) and 2) proposed for quantifying failure localization capability can be used to evaluate the impact of various parameters, including topology, number of monitors, and probing mechanisms

Optimal energy consumption for communication, computation, caching and quality guarantee

Energy efficiency is a fundamental requirement of modern data-communication systems, and its importance is reflected in much recent work on performance analysis of system energy consumption. However, most work has only focused on communication and computation costs without accounting for data caching costs. Given the increasing interest in cache networks, this is a serious deficiency. In this paper, we consider the problem of energy consumption in data communication, computation and caching (C3) with a quality-of-information (QoI) guarantee in a communication network. Our goal is to identify the optimal data compression rates and cache placement over the network that minimizes the overall energy consumption in the network. We formulate the problem as a mixed integer nonlinear programming (MINLP) problem with nonconvex functions, which is non-deterministic polynomial-time hard (NP-hard) in general. We propose a variant of the spatial branch-and-bound algorithm (V-SBB) that can provide an ϵ-global optimal solution to the problem. By extensive numerical experiments, we show that the C3 optimization framework improves the energy efficiency by up to 88% compared to any optimization that only considers either communication and caching or communication and computation. Furthermore, the V-SBB technique provides comparatively better solutions than some other MINLP solvers at the cost of additional computation time