34 resultados para Ubiquitous Computing, Pervasive Computing, Internet of Things, Cloud Computing
Resumo:
The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.
Resumo:
Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.
Resumo:
Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers (e.g., MNO, MVNO) move from proprietary and bespoke hardware and software platforms toward an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently created through cloudification by leveraging the existing infrastructure. In this work, we present RANaaS, which is a cloudified radio access network delivered as a service. RANaaS provides the service life-cycle of an ondemand, elastic, and pay as you go 3GPP RAN instantiated on top of the cloud infrastructure. We demonstrate an example of realtime cloudified LTE network deployment using the OpenAirInterface LTE implementation and OpenStack running on commodity hardware as well as the flexibility and performance of the platform developed.
Resumo:
In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.
Resumo:
The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and academia commit to jointly establish the vision of Mobile Cloud Networking, to develop a fully cloud-based mobile communication and application platform.
Resumo:
Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.
Resumo:
Unlike previously explored relationships between the properties of hot Jovian atmospheres, the geometric albedo and the incident stellar flux do not exhibit a clear correlation, as revealed by our re-analysis of Q0-Q14 Kepler data. If the albedo is primarily associated with the presence of clouds in these irradiated atmospheres, a holistic modeling approach needs to relate the following properties: the strength of stellar irradiation (and hence the strength and depth of atmospheric circulation), the geometric albedo (which controls both the fraction of starlight absorbed and the pressure level at which it is predominantly absorbed), and the properties of the embedded cloud particles (which determine the albedo). The anticipated diversity in cloud properties renders any correlation between the geometric albedo and the stellar flux weak and characterized by considerable scatter. In the limit of vertically uniform populations of scatterers and absorbers, we use an analytical model and scaling relations to relate the temperature-pressure profile of an irradiated atmosphere and the photon deposition layer and to estimate whether a cloud particle will be lofted by atmospheric circulation. We derive an analytical formula for computing the albedo spectrum in terms of the cloud properties, which we compare to the measured albedo spectrum of HD 189733b by Evans et al. Furthermore, we show that whether an optical phase curve is flat or sinusoidal depends on whether the particles are small or large as defined by the Knudsen number. This may be an explanation for why Kepler-7b exhibits evidence for the longitudinal variation in abundance of condensates, while Kepler-12b shows no evidence for the presence of condensates despite the incident stellar flux being similar for both exoplanets. We include an "observer's cookbook" for deciphering various scenarios associated with the optical phase curve, the peak offset of the infrared phase curve, and the geometric albedo.
Resumo:
Increased levels of NO in exhaled air in association with increased NO synthetase (NOS)2 expression in bronchial epithelial are hallmark features of asthma. It has been suggested that NO contributes to asthma pathogenesis by selective down-regulation of TH1 responses. We demonstrate, however, that NO can reversibly limit in vitro expansion of both human TH1 and TH2 CD4+ T cells. Mechanistically, NO induces cGMP-mediated reversible STAT5 dephosphorylation and therefore interferes with the IL-2R activation cascade. Human bronchial epithelial cells (HBEC) up-regulate NOS2 after stimulation with IFN-gamma secreted by TH1 CD4+ T cells and release NO, which inhibits both TH1 and TH2 cell proliferation. This reversible T cell growth arrest depends on NO because T cell proliferation is completely restored after in vitro blocking of NOS2 on HBEC. HBEC thus drive the effector end of a TH1-controlled feedback loop, which protects airway mucosal tissues at the potential lesional site in asthma from overwhelming CD4+ TH2 (and potentially TH1) responses following allergen exposure. Variations in the efficiency of this feedback loop provides a plausible mechanism to explain why only a subset of atopics sensitized to ubiquitous aeroallergens progress to expression of clinically relevant levels of airways inflammation.
Resumo:
Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.
Resumo:
Directly imaged exoplanets are unexplored laboratories for the application of the spectral and temperature retrieval method, where the chemistry and composition of their atmospheres are inferred from inverse modeling of the available data. As a pilot study, we focus on the extrasolar gas giant HR 8799b, for which more than 50 data points are available. We upgrade our non-linear optimal estimation retrieval method to include a phenomenological model of clouds that requires the cloud optical depth and monodisperse particle size to be specified. Previous studies have focused on forward models with assumed values of the exoplanetary properties; there is no consensus on the best-fit values of the radius, mass, surface gravity, and effective temperature of HR 8799b. We show that cloud-free models produce reasonable fits to the data if the atmosphere is of super-solar metallicity and non-solar elemental abundances. Intermediate cloudy models with moderate values of the cloud optical depth and micron-sized particles provide an equally reasonable fit to the data and require a lower mean molecular weight. We report our best-fit values for the radius, mass, surface gravity, and effective temperature of HR 8799b. The mean molecular weight is about 3.8, while the carbon-to-oxygen ratio is about unity due to the prevalence of carbon monoxide. Our study emphasizes the need for robust claims about the nature of an exoplanetary atmosphere to be based on analyses involving both photometry and spectroscopy and inferred from beyond a few photometric data points, such as are typically reported for hot Jupiters.
Resumo:
The Toledoth Yeshu, the “Generation,” or “Life of Jesus,” have been described as an anti-Gospel, or a parody of the Gospel. This protean tradition, witnessed in more than hundred manuscripts and printed editions, offers a “counter-history” of the life of Jesus and the origins of Christianity. According to this mischievous narrative Jesus was an illegitimate child turned charlatan, and his disciples a bunch of violent and senseless rogues who continued to stir up trouble in Israel even following their leader’s shameful hanging. The Toledoth Yeshu is the story of an anomaly (Jesus and the birth of Christianity). It is also a story about confusion: marital confusion, social confusion, and religious confusion. As an exercise in “historical imagination,” the Toledoth Yeshu offers a narrative of religions compared, and a reflection on social and religious borders, on their instability and fragility, and ultimately on their necessity. The present paper will explore the normative dimension of the Toledoth Yeshu tradition: the way the “disorder of things” the narrative relates also conveys a powerful discourse on social and religious norms. We will also seek to map this tradition in the broader context of medieval Jewish discussions on Jesus (particularly Maimonides) as a “case” in the religious history of mankind, addressing issues of false prophecy, religious deviation, transgression, and heresy.
Resumo:
Cloudification of the Centralized-Radio Access Network (C-RAN) in which signal processing runs on general purpose processors inside virtual machines has lately received significant attention. Due to short deadlines in the LTE Frequency Division Duplex access method, processing time fluctuations introduced by the virtualization process have a deep impact on C-RAN performance. This paper evaluates bottlenecks of the OpenAirInterface (OAI is an open-source software-based implementation of LTE) cloud performance, provides feasibility studies on C-RAN execution, and introduces a cloud architecture that significantly reduces the encountered execution problems. In typical cloud environments, the OAI processing time deadlines cannot be guaranteed. Our proposed cloud architecture shows good characteristics for the OAI cloud execution. As an example, in our setup more than 99.5% processed LTE subframes reach reasonable processing deadlines close to performance of a dedicated machine.
Resumo:
Senescent higher plants degrade their chlorophylls (Chls) to polar colorless tetrapyrrolic Chl catabolites, which accumulate in the vacuoles. In extracts from degreened leaves of the tree Cercidiphyllum japonicum an unpolar catabolite of this type was discovered. This tetrapyrrole was named Cj-NCC-2 and was found to be identical with the product of a stereoselective nonenzymatic isomerization of a “fluorescent” Chl catabolite. This (bio-mimetic) formation of the “nonfluorescent” catabolite Cj-NCC-2 took place readily at ambient temperature and at pH 4.9 in aqueous solution. The indicated nonenzymatic process is able to account for a crucial step during Chl breakdown in senescent higher plants. Once delivered to the acidic vacuoles, the fluorescent Chl catabolites are due to undergo a rapid, stereoselective isomerization to the ubiquitous nonfluorescent catabolites. The degradation of the Chl macrocycle is thus indicated to rely on just two known enzymes, one of which is senescence specific and cuts open the chlorin macroring. The two enzymes supply the fluorescent Chl catabolites, which are “programmed” to isomerize further rapidly in an acidic medium, as shown here. Indeed, only small amounts of the latter are temporarily observable during senescence in higher plants.