Fuzzy-Logic Based Call Admission Control in 5G Cloud Radio Access Networks with Pre-emption

YesFifth generation (5G) cellular networks will be comprised of millions of connected devices like wearable devices, Androids, iPhones, tablets and the Internet of Things (IoT) with a plethora of applications generating requests to the network. The 5G cellular networks need to cope with such sky-rocketing tra c requests from these devices to avoid network congestion. As such, cloud radio access networks (C-RAN) has been considered as a paradigm shift for 5G in which requests from mobile devices are processed in the cloud with shared baseband processing. Despite call admission control (CAC) being one of radio resource management techniques to avoid the network congestion, it has recently been overlooked by the community. The CAC technique in 5G C-RAN has a direct impact on the quality of service (QoS) for individual connections and overall system e ciency. In this paper, a novel Fuzzy-Logic based CAC scheme with pre-emption in C-RAN is proposed. In this scheme, cloud bursting technique is proposed to be used during congestion, where some delay tolerant low-priority connections are pre-empted and outsourced to a public cloud with a penalty charge. Simulation results show that the proposed scheme has low blocking probability below 5%, high throughput, low energy consumption and up to 95% of return on revenue

Analysis of Cloud Bursting on Openstack Infrastructure to AWS

Cloud computing is the development of distributed and parallel computing that seeks to provide a new model of business computing by automating services and efficiently storing proprietary data. Cloud bursting is one of the cloud computing techniques that adopts the hybrid cloud model which seeks to expand the resources of a private cloud through the integration with a public cloud infrastructure. In this paper, the viability of cloud bursting is experimented and an attempt to integrate AWS EC2 onto an Openstack cloud environment using the Openstack OMNI driver is conducted

Influence of transport and ocean ice extent on biogenic aerosol sulfur in the Arctic atmosphere

The recent decline in sea ice cover in the Arctic Ocean could affect the regional radiative forcing via changes in sea ice-atmosphere exchange of dimethyl sulfide (DMS) and biogenic aerosols formed from its atmospheric oxidation, such as methanesulfonic acid (MSA). This study examines relationships between changes in total sea ice extent north of 70 degrees N and atmospheric MSA measurement at Alert, Nunavut, during 1980-2009; at Barrow, Alaska, during 1997-2008; and at Ny-Alesund, Svalbard, for 1991-2004. During the 1980-1989 and 1990-1997 periods, summer (July-August) and June MSA concentrations at Alert decreased. In general, MSA concentrations increased at all locations since 2000 with respect to 1990 values, specifically during June and summer at Alert and in summer at Barrow and Ny-Alesund. Our results show variability in MSA at all sites is related to changes in the source strengths of DMS, possibly linked to changes in sea ice extent as well as to changes in atmospheric transport patterns. Since 2000, a late spring increase in atmospheric MSA at the three sites coincides with the northward migration of the marginal ice edge zone where high DMS emissions from ocean to atmosphere have previously been reported. Significant negative correlations are found between sea ice extent and MSA concentrations at the three sites during the spring and June. These results suggest that a decrease in seasonal ice cover influencing other mechanisms of DMS production could lead to higher atmospheric MSA concentrations

Quenching or Bursting: Star Formation Acceleration--A New Methodology for Tracing Galaxy Evolution

We introduce a new methodology for the direct extraction of galaxy physical parameters from multi-wavelength photometry and spectroscopy. We use semi-analytic models that describe galaxy evolution in the context of large scale cosmological simulation to provide a catalog of galaxies, star formation histories, and physical parameters. We then apply stellar population synthesis models and a simple extinction model to calculate the observable broad-band fluxes and spectral indices for these galaxies. We use a linear regression analysis to relate physical parameters to observed colors and spectral indices. The result is a set of coefficients that can be used to translate observed colors and indices into stellar mass, star formation rate, and many other parameters, including the instantaneous time derivative of the star formation rate which we denote the {\it Star Formation Acceleration (SFA)}, We apply the method to a test sample of galaxies with GALEX photometry and SDSS spectroscopy, deriving relationships between stellar mass, specific star formation rate, and star formation acceleration. We find evidence for a mass-dependent SFA in the green valley, with low mass galaxies showing greater quenching and higher mass galaxies greater bursting. We also find evidence for an increase in average quenching in galaxies hosting AGN. A simple scenario in which lower mass galaxies accrete and become satellite galaxies, having their star forming gas tidally and/or ram-pressure stripped, while higher mass galaxies receive this gas and react with new star formation can qualitatively explain our results.Comment: 33 pages, 31 figures, ApJ accepte

Polarized light scattering by aerosols in the marine atmospheric boundary layer

The intensity and polarization of light scattered from marine aerosols affect visibility and contrast in the marine atmospheric boundary layer (MABL). The polarization properties of scattered light in the MABL vary with size, refractive index, number distributions, and environmental conditions. Laboratory measurements were used to determine the characteristics and variability of the polarization of light scattered by aerosols similar to those in the MABL. Scattering from laboratory-generated sea-salt-containing (SSC) [NaCl, (NH4)2SO4, and seawater] components of marine aerosols was measured with a scanning polarization-modulated nephelometer. Mie theory with Gaussian and log normal size distributions of spheres was used to calculate the polarized light scattering from various aerosol composition models and from experimentally determined distributions of aerosols in the marine boundary layer. The modeling was verified by comparison with scattering from distilled water aerosols. The study suggests that polarimetric techniques can be used to enhance techniques for improving visibility and remote imaging for various aerosol types, Sun angles, and viewing conditions

Interoperability in the Heterogeneous Cloud Environment: A Survey of Recent User-centric Approaches

© 2016 Copyright held by the owner/author(s). Cloud computing provides users the ability to access shared, online computing resources. However, providers often offer their own proprietary applications, interfaces, APIs and infrastructures, resulting in a heterogeneous cloud environment. This heterogeneous environment makes it difficult for users to change cloud service providers; exploring capabilities to support the automated migration from one provider to another is an active, open research area. Many standards bodies (IEEE, NIST, DMTF and SNIA), industry (middleware) and academia have been pursuing approaches to reduce the impact of vendor lock-in by investigating the cloud migration problem at the level of the VM. However, the migration downtime, decoupling VM from underlying systems and security of live channels remain open issues. This paper focuses on analysing recently proposed live, cloud migration approaches for VMs at the infrastructure level in the cloud architecture. The analysis reveals issues with flexibility, performance, and security of the approaches, including additional loads to the CPU and disk I/O drivers of the physical machine where the VM initially resides. The next steps of this research are to develop and evaluate a new approach LibZam (Libya Zamzem) that will work towards addressing the identified limitations

A Framework for Approximate Optimization of BoT Application Deployment in Hybrid Cloud Environment

We adopt a systematic approach to investigate the efficiency of near-optimal deployment of large-scale CPU-intensive Bag-of-Task applications running on cloud resources with the non-proportional cost to performance ratios. Our analytical solutions perform in both known and unknown running time of the given application. It tries to optimize users' utility by choosing the most desirable tradeoff between the make-span and the total incurred expense. We propose a schema to provide a near-optimal deployment of BoT application regarding users' preferences. Our approach is to provide user with a set of Pareto-optimal solutions, and then she may select one of the possible scheduling points based on her internal utility function. Our framework can cope with uncertainty in the tasks' execution time using two methods, too. First, an estimation method based on a Monte Carlo sampling called AA algorithm is presented. It uses the minimum possible number of sampling to predict the average task running time. Second, assuming that we have access to some code analyzer, code profiling or estimation tools, a hybrid method to evaluate the accuracy of each estimation tool in certain interval times for improving resource allocation decision has been presented. We propose approximate deployment strategies that run on hybrid cloud. In essence, proposed strategies first determine either an estimated or an exact optimal schema based on the information provided from users' side and environmental parameters. Then, we exploit dynamic methods to assign tasks to resources to reach an optimal schema as close as possible by using two methods. A fast yet simple method based on First Fit Decreasing algorithm, and a more complex approach based on the approximation solution of the transformed problem into a subset sum problem. Extensive experiment results conducted on a hybrid cloud platform confirm that our framework can deliver a near optimal solution respecting user's utility function

Surface ocean-lower atmosphere study: Scientific synthesis and contribution to Earth system science

The domain of the surface ocean and lower atmosphere is a complex, highly dynamic component of the Earth system. Better understanding of the physics and biogeochemistry of the air-sea interface and the processes that control the exchange of mass and energy across that boundary define the scope of the Surface Ocean-Lower Atmosphere Study (SOLAS) project. The scientific questions driving SOLAS research, as laid out in the SOLAS Science Plan and Implementation Strategy for the period 2004-2014, are highly challenging, inherently multidisciplinary and broad. During that decade, SOLAS has significantly advanced our knowledge. Discoveries related to the physics of exchange, global trace gas budgets and atmospheric chemistry, the CLAW hypothesis (named after its authors, Charlson, Lovelock, Andreae and Warren), and the influence of nutrients and ocean productivity on important biogeochemical cycles, have substantially changed our views of how the Earth system works and revealed knowledge gaps in our understanding. As such SOLAS has been instrumental in contributing to the International Geosphere Biosphere Programme (IGBP) mission of identification and assessment of risks posed to society and ecosystems by major changes in the Earth́s biological, chemical and physical cycles and processes during the Anthropocene epoch. SOLAS is a bottom-up organization, whose scientific priorities evolve in response to scientific developments and community needs, which has led to the launch of a new 10-year phase. SOLAS (2015–2025) will focus on five core science themes that will provide a scientific basis for understanding and projecting future environmental change and for developing tools to inform societal decision-making