A Service Level Agreement Aware Online Algorithm for Virtual Machine Migration

The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be designed. One specific area where energy efficient algorithms are required is virtual machine consolidation. With virtual machine consolidation, the objective is to utilize the minimum possible number of hosts to accommodate the required virtual machines, keeping in mind the service level agreement requirements. This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host. The online algorithm is analyzed using a competitive analysis approach. In addition, an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms. Our proposed online algorithm consumed 25% less energy and performed 43% fewer migrations than the benchmark algorithms.     

Development of the knowledge‐based learning system for distance education

This article addresses difficulties in developing a knowledge base for application to educational environments. To solve this problem, fundamental principles used for building similar systems are proposed. A mathematical model is chosen to propose a mathematical design of educational materials based on linguistic variables. A membership function of knowledge evaluation and an architecture of fuzzy knowledge were created, on the basis of a set of two types of fuzzy rules that cover all possible situations in the educational environment, with a demonstration of its application based on the original method of selection questions for procedure evaluation of student knowledge. In the end, the studies analyzing the utility of the experiment clearly showed an increase in the efficiency of the educational process, with the advantage of applied models and technologies in the long term. © 2012 Wiley Periodicals, Inc.     

Nanosilica Supported Dual Acidic Ionic Liquid as a Recyclable Catalyst for the Rapid and Green Synthesis of Polycyclic Phenolic Compounds

Generally ionic liquids have gained increasing attention in organic synthesis as catalyst and solvent. However, there are some drawbacks, including the difficulties in the product purification, ionic liquid recycling, and use of excess amounts of the expensive ionic liquid when the ionic liquid is used in the organic reactions. In addition, the high viscosity of ionic liquids can lead to mass transfer limitations in fast chemical reactions. These problems can be overcome by the use of supported ionic liquid phases. In this article, a simple, efficient and green method has been developed for the synthesis of bisphenolic antioxidants by the reaction of 2-tert-butyl-4-methylphenol and aldehydes in the presence of nanosilica supported dual acidic ionic liquid (NSSDAIL) as robust and reusable catalyst under solvent-free conditions. Three different NSSDAILs were synthesized and characterized using SEM, BET, IR, and XRD techniques. High yields of the products, short reaction times, use of a non corrosive, non toxic and reusable catalyst, and use of solvent-free condition are the worthwhile advantages of the current method.     

Comparison of constituents, antioxidant potency, and acetylcholinesterase inhibition in Lentinus edodes, Sparassis crispa, and Mycoleptodonoides aitchisonii

This study evaluates three edible mushrooms: Lentinus edodes, Sparassis crispa, and Mycoleptodonoides aitchisonii, in terms of acetylcholinesterase (AChE) inhibition, antioxidant potency and constituents free amino acids and mineral. The concentration of essential amino acids was found to be 34.10 mg/g in M. aitchisonii, 26.25 mg/g in S. crispa, 25.99 mg/g in L. edodes. S. crispa displayed the highest DPPH scavenging activity and phenolic contents. The best results for AChE inhibition were obtained from M. aitchisonii. These results suggest that M. aitchisonii has high potential for cognitive improvement by AChE inhibition and antioxidant potency.     

Stochastic collocation-based nonlinear analysis of concrete bridges with uncertain parameters

This paper focuses on the stochastic response of concrete bridges considering uncertainty in bearing and abutment stiffness. A multi-span simply supported bridge with concrete girders is selected. A 3D-dimensional model is prepared, and nonlinear response history analyses are performed. For the numerical dynamic simulation, the non-sampling stochastic method based on generalized polynomial chaos (gPC) expansion is utilised. The uncertain parameters include the vertical and shear stiffness of bearings and the lateral stiffness of abutments are presented by the truncated gPC expansions. Furthermore, the system response such as base shear, acceleration, velocity and displacement in different columns is presented by gPC expansion with unknown deterministic coefficients. The stochastic Galerkin projection is employed to calculate a set of deterministic equations. A non-intrusive solution, as a set of collocation points, determines the unknown gPC coefficients of the system response and the results are compared with Monte Carlo simulations. The key advantage of spectral discretization is the combination of the mentioned method with the spatial discretization, e.g. finite element model. This study also emphasises the accuracy in results and time efficiency of the proposed non-sampling method for uncertainty quantification of stochastic systems comparing to sampling procedure (e.g. Monte Carlo simulation).     

Physical and chemical modification of distillery sludge for Pb(II) biosorption

The waste distillery sludge from sugar-cane industry was pretreated physically (boiled, heated and autoclaved) as well as chemically (HCl, H(2)SO(4), H(3)PO(4), NaOH, Ca(OH)(2), Al(OH)(3), C(6)H(6), HCHO, CH(3)OH and C1(2)H(25)OSO(3)Na (sodium dodecyl sulphate (SDS)) for assessing the comparative sorption capacity of untreated and modified distillery sludge for Pb(II) biosorption from aqueous solutions. Experiments were conducted in shake flasks on a batch basis to access the effect of different experimental parameters such as pH, biosorbent dosage, biosorbent size, initial Pb(II) concentration and contact time. The uptake capacity 'q' (mg/g) of untreated and pretreated distillery sludge was in following order: NaOH (51.29+/-1.21)>HCl (49.82+/-1.22)>HCHO (49.56+/-1.14)>H(2)SO(4) (47.71+/-1.20)>HgCl(2) (45.32+/-1.06)>Ca(OH)(2) (44.01+/-1.18)>MeOH (43.73+/-1.23)>C(6)H(6) (42.72+/-1.19)>H(3)PO(4) (42.01+/-1.17)>SDS (40.87+/-1.27)>autoclaved (40.23+/-1.24)>Boiled (39.95+/-1.19)>heated (38.87+/-1.32)>Al (OH)(3) (38.30+/-1.14)>untreated (37.76+/-1.21). In further parameter studies, the optimized biosorbent size was 0.250 mm at pH 5 and best dose was 0.05 g of biosorbent. The applicability of the Langmuir and Freundlich models for sorption process was tested and best fitted model was Langmuir with the coefficient of determination (R(2)) value, 0.97, the process followed second order kinetic mechanism.     

Nanoparticles rapidly assess specific IgE in plasma

Allergy is the sixth leading cause of chronic disease in the world. This study demonstrates the feasibility of detecting allergy indicators in human plasma, noninvasively, at the point of care and with a comparable efficiency and reduced turnaround time compared with the gold standard. Peanut allergy was utilized as a model due to its widespread occurrence among the US population and fatality if not treated. The detection procedure utilized magnetic nanoparticles that were coated with an allergen layer (peanut protein extract). Peanut immunoglobulin E (IgE) was detected in concentrations close to the minimum detection range of CAP assay. The results were obtained in minutes compared with the CAP assay which requires more than 3 h.     

Image compression in signal-dependent noise

The performance of an image compression scheme is affected by the presence of noise, and the achievable compression may be reduced significantly. We investigated the effects of specific signal-dependent-noise (SDN) sources, such as film-grain and speckle noise, on image compression, using JPEG (Joint Photographic Experts Group) standard image compression. For the improvement of compression ratios noisy images are preprocessed for noise suppression before compression is applied. Two approaches are employed for noise suppression. In one approach an estimator designed specifically for the SDN model is used. In an alternate approach, the noise is first transformed into signal-independent noise (SIN) and then an estimator designed for SIN is employed. The performances of these two schemes are compared. The compression results achieved for noiseless, noisy, and restored images are also presented.