Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.

Clustering composite SaaS components in cloud computing using a grouping genetic algorithm

Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.

A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Lateral movements in composite high-rise buildings under seismic action

Daring human nature has already led to the construction of high-rise buildings in naturally challenging geological regions and in worse environments of the world. However; literature review divulges that there is a lag in research of certain generic principles and rules for the prediction of lateral movement in multistorey construction. The present competitive trend orders the best possible used of available construction material and resources. Hence; the mixed used of reinforced concrete with structural steel is gaining prevalence day by day. This paper investigates the effects of Seismic load on composite multistorey building provided with core wall and trusses through FEM modelling. The results showed that increased rigidity corresponds to lower period of vibration and hence higher seismic forces. Since Seismic action is a function of mass and response acceleration, therefore; mass increment generate higher earthquake load and thus cause higher impact base shear and overturning movement. Whereas; wind force depends on building exposed, larger the plan dimension greater is the wind impact. Nonetheless; outriggers trusses noticeably contribute, in improving the serviceability of structure subjected to wind and earthquake forces.

Copper-containing mesoporous bioactive glass scaffolds with multifunctional properties of angiogenesis capacity, osteostimulation and antibacterial activity

It is of great importance to develop multifunctional bioactive scaffolds, which combine angiogenesis capacity, osteostimulation, and antibacterial properties for regenerating lost bone tissues. In order to achieve this aim, we prepared copper (Cu)-containing mesoporous bioactive glass (Cu-MBG) scaffolds with interconnective large pores (several hundred micrometer) and well-ordered mesopore channels (around 5 nm). Both Cu-MBG scaffolds and their ionic extracts could stimulate hypoxia-inducible factor (HIF)-1a and vascular endothelial growth factor(VEGF) expression in human bone marrow stromal cells(hBMSCs). In addition, both Cu-MBG scaffolds and their ionic extracts significantly promoted the osteogenic differentiation of hBMSCs by improving their bone-related gene expression (alkaline phosphatase (ALP), osteopontin(OPN) and osteocalcin (OCN)). Furthermore, Cu-MBG scaffolds could maintain a sustained release of ibuprofen and significantly inhibited the viability of bacteria. This study indicates that the incorporation of Cu2þ ions into MBG scaffolds significantly enhances hypoxia-like tissue reaction leading to the coupling of angiogenesis and osteogenesis. Cu2þ ions play an important role to offer the multifunctional properties of MBG scaffold system. This study has demonstrated that it is possible to develop multifunctional scaffolds by combining enhanced angiogenesis potential, osteostimulation, and antibacterial properties for the treatment of large bone defects.

Hamlet through the looking glass : Rosencrantz and Guildenstern are dead

The film adaptation of "Rosencrantz and Guildenstern Are Dead"'s constant reallocation of actor and audience roles (or subject and object positions) means that the film’s viewers are as deeply implicated in considering issues of identity, agency and determination as Rosencrantz and Guildenstern are. Tellingly, one of The Player’s outbursts reveals the philosophical connections between observing and being observed in ways that are true of the theatre, but which also transcend it: ‘You don’t understand the humiliation of it. To be tricked out of the single assumption that makes our existence bearable; that somebody is watching.’ In this statement is one of the film’s main concerns; that is, the relationship between knowing the self, knowing others, and being known by others.

Characterisation of multi wall carbon nanotube–polymer composites for strain sensing applications

Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.

Exploration and reflection in interactive art : glass pond

Glass Pond is an interactive artwork designed to engender exploration and reflection through an intuitive, tangible interface and a simulation agent. It is being developed using iterative methods. A study has been conducted with the aim of illuminating user experience, interface, design, and performance issues.The paper describes the study methodology and process of data analysis including coding schemes for cognitive states and movements. Analysis reveals that exploration and reflection occurred as well as composing behaviours (unexpected). Results also show that participants interacted to varying degrees. Design discussion includes the artwork's (novel) interface and configuration.

Subliquidus glass-glass immiscibility along the albite-diopside join

A calorimetric study has shown that glasses along the albite-diopside join in the system albiteanorthite-diopside have positive enthalpies of mixing. Thermodynamic calculations based on these data describe a nearly symmetric, metastable, subliquidus irascibility gap along the join with a critical temperature at 910 K. The existence of the miscibility gap was tested experimentally by annealing an Ab50Di50 glass at 748 K and 823 K. Annealed glasses were examined by optical microscopy and by scanning and transmission electron microscopy. The glasses showed morphological and chemical features consistent with unmixing of two glass phases. The apparent mechanism of phase separation involves initial spinodal decomposition followed by coarsening to produce 0.1 μm–0.3 μm spherical glass phases.

Reaction products between Bi-Sr-Ca-Cu-oxide thick films and alumina substrates

The structure and composition of reaction products between Bi-Sr-Ca-Cu-oxide (BSCCO) thick films and alumina substrates have been characterized using a combination of electron diffraction, scanning electron microscopy and energy dispersive X-ray spectrometry (EDX). Sr and Ca are found to be the most reactive cations with alumina. Sr4Al6O12SO4 is formed between the alumina substrates and BSCCO thick films prepared from paste with composition close to Bi-2212 (and Bi-2212 + 10 wt.% Ag). For paste with composition close to Bi(Pb)-2223 + 20 wt.% Ag, a new phase with f.c.c. structure, lattice parameter about a = 24.5 A and approximate composition Al3Sr2CaBi2CuOx has been identified in the interface region. Understanding and control of these reactions is essential for growth of high quality BSCCO thick films on alumina. (C) 1997 Elsevier Science S.A.

Microstructural investigation of Bi-Sr-Ca-Cu-oxide thick films on alumina substrates

The microstructure of Bi-Sr-Ca-Cu-oxide (BSCCO) thick films on alumina substrates has been characterized using a combination of X-ray diffractometry, scanning electron microscopy, transmission electron microscopy of sections across the film/substrate interface and energy-dispersive X-ray spectrometry. A reaction layer formed between the BSCCO films and the alumina substrates. This chemical interaction is largely responsible for off-stoichiometry of the films and is more significant after partial melting of the films. A new phase with fee structure, lattice parameter a = 2.45 nm and approximate composition Al3Sr2CaBi2CuOx has been identified as reaction product between BSCCO and Al2O3.