SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions

Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated services to users and meet their quality expectations. Existing resource management systems in data centers are yet to support Service Level Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to realize cloud computing and utility computing. In addition, no work has been done to collectively incorporate customer-driven service management, computational risk management, and autonomic resource management into a market-based resource management system to target the rapidly changing enterprise requirements of Cloud computing. This paper presents vision, challenges, and architectural elements of SLA-oriented resource management. The proposed architecture supports integration of marketbased provisioning policies and virtualisation technologies for flexible allocation of resources to applications. The performance results obtained from our working prototype system shows the feasibility and effectiveness of SLA-based resource provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011, IEEE Press, USA), Hong Kong, China, December 12-14, 201

Multiple Linear Regression-Based Energy-Aware Resource Allocation in the Fog Computing Environment

Fog computing is a promising computing paradigm for time-sensitive Internet of Things (IoT) applications. It helps to process data close to the users, in order to deliver faster processing outcomes than the Cloud; it also helps to reduce network traffic. The computation environment in the Fog computing is highly dynamic and most of the Fog devices are battery powered hence the chances of application failure is high which leads to delaying the application outcome. On the other hand, if we rerun the application in other devices after the failure it will not comply with time-sensitiveness. To solve this problem, we need to run applications in an energy-efficient manner which is a challenging task due to the dynamic nature of Fog computing environment. It is required to schedule application in such a way that the application should not fail due to the unavailability of energy. In this paper, we propose a multiple linear, regression-based resource allocation mechanism to run applications in an energy-aware manner in the Fog computing environment to minimise failures due to energy constraint. Prior works lack of energy-aware application execution considering dynamism of Fog environment. Hence, we propose A multiple linear regression-based approach which can achieve such objectives. We present a sustainable energy-aware framework and algorithm which execute applications in Fog environment in an energy-aware manner. The trade-off between energy-efficient allocation and application execution time has been investigated and shown to have a minimum negative impact on the system for energy-aware allocation. We compared our proposed method with existing approaches. Our proposed approach minimises the delay and processing by 20%, and 17% compared with the existing one. Furthermore, SLA violation decrease by 57% for the proposed energy-aware allocation.Comment: 8 Pages, 9 Figure

Future Path Toward TB Vaccine Development: Boosting BCG or Re-educating by a New Subunit Vaccine

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb), kills 5,000 people per day globally. Rapid development and spread of various multi drug-resistant strains of Mtb emphasize that an effective vaccine is still the most cost-effectives and efficient way of controlling and eradicating TB. Bacillus Calmette-Guerin (BCG), the only licensed TB vaccine, still remains the most widely administered human vaccine, but is inefficient in protecting from pulmonary TB in adults. The protective immunity afforded by BCG is thought to wane with time and considered to last only through adolescent years. Heterologous boosting of BCG-primed immune responses using a subunit vaccine represents a promising vaccination approach to promote strong cellular responses against Mtb. In our earlier studies, we discovered lipopeptides of ESAT-6 antigen with strong potential as a subunit vaccine candidate. Here, we have investigated that potential as a booster to BCG vaccine in both a pre-exposure preventive vaccine and a post-exposure therapeutic vaccine setting. Surprisingly, our results demonstrated that boosting BCG with subunit vaccine shortly before Mtb challenge did not improve the BCG-primed immunity, whereas the subunit vaccine boost after Mtb challenge markedly improved the quantity and quality of effector T cell responses and significantly reduced Mtb load in lungs, liver and spleen in mice. These studies suggest that ESAT-6 lipopeptide-based subunit vaccine was ineffective in overcoming the apparent immunomodulation induced by BCG vaccine in Mtb uninfected mice, but upon infection, the subunit vaccine is effective in re-educating the protective immunity against Mtb infection. These important results have significant implications in the design and investigation of effective vaccine strategies and immunotherapeutic approaches for individuals who have been pre-immunized with BCG vaccine but still get infected with Mtb

Convalescent Plasma: An Evidence-Based Old Therapy to Treat Novel Coronavirus Patients

Novel Coronavirus (nCoV-2019) is a highly infectious viral outbreak that has so far infected more than 110 million people worldwide. Fast viral transmission and high infection rates have severely affected the entire population, especially the old aged and comorbid individuals leaving significantly less time to find some effective treatment strategy. In these challenging times, convalescent plasma (CP) therapy came as a ray of hope to save humankind. It is a form of passive immunization that has been used to treat various infectious diseases since 1890, including the 1918 Spanish flu, 2002/03 SARS-CoV, 2009 H1N1, 2012 MERS-CoV, and 2014 Ebola outbreak. The transfusion includes administration of CP containing a high value of neutralizing antibodies against the virus in hospitalized patients. This chapter summarizes the potential outcome of CP therapy in the treatment of nCoV-2019 patients

INVESTIGATION AND OPTIMIZATION OF FORMULATION PARAMETERS FOR SELFNANOEMULSIFYING DELIVERY SYSTEM OF TWO LIPOPHILIC AND GASTROINTESTINAL LABILE DRUGS USING BOX-BEHNKEN DESIGN

Objective: Present research work aims toward codelivery of two hydrophobic drugs, curcumin (CRM) and duloxetine hydrochloride (DXH) through self-nanoemulsifying drug delivery systems (SNEDDS).Methods: Initially, binary mixture in the ratio of 1:1 was prepared and then loaded into SNEDDS. Box-Behnken design (BBD) was adopted to develop SNEDDS. As per the optimal design, 13 SNEDDS prototypes were prepared. Castor oil, tween-80 and Transcutol P® were used as oil, surfactant, and cosurfactant, respectively. To 1 mL of SNEDDS, 30 mg each of CRM and DXH was loaded (CRM-DXH- SNEDDS).Results: The design revealed that for mean droplet size, polydispersity index (PDI), as well as percentage drug loading, all the three factors, i.e. ratio of oil (a), surfactant (b), and cosurfactant (c) were found to give significant effect. Factor B showed the most significant effect on mean droplet size (y1). In case of PDI (y2), factors B and C exerted maximum influence, whereas, Factor A has shown non-significant effect. For percentage drug loading of drugs (y3 and y4), all the three factors were found to have the most significant effect. The optimized batch of CRM-DXH- SNEDDS having composition castor oil, tween-80, and Transcutol P® in the ratio: 2.17:5.22:2.61, revealed that the mean drug loading (%) of CRM and DXH in an optimized batch of SNEDDS was found to be 87.22±1.87 and 92.32±0.19%, respectively. The mean droplet size, PDI, and zeta potential of formed SNEDDS were observed as 113.14±1.14 nm, 0.20±0.026, and −13.2 mV, respectively.Conclusion: BBD provided optimal formula composition for SNEDDS for obtaining desirable drug loading, emulsion droplet size, and zeta potential