Composite SaaS scaling in cloud computing using a hybrid genetic algorithm

A Software-as-a-Service or SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. Components in a composite SaaS may need to be scaled – replicated or deleted, to accommodate the user’s load. It may not be necessary to replicate all components of the SaaS, as some components can be shared by other instances. On the other hand, when the load is low, some of the instances may need to be deleted to avoid resource underutilisation. Thus, it is important to determine which components are to be scaled such that the performance of the SaaS is still maintained. Extensive research on the SaaS resource management in Cloud has not yet addressed the challenges of scaling process for composite SaaS. Therefore, a hybrid genetic algorithm is proposed in which it utilises the problem’s knowledge and explores the best combination of scaling plan for the components. Experimental results demonstrate that the proposed algorithm outperforms existing heuristic-based solutions.

Recursive pathways to marginal likelihood estimation with prior-sensitivity analysis

We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.

Study on dynamic system optimum assignment to establish marginal time equilibrium

Several analytical methods for Dynamic System Optimum (DSO) assignment have been proposed but they are basically classified into two kinds. This chapter attempts to establish DSO by equilbrating the path dynamic marginal time (DMT). The authors analyze the path DMT for a single path with tandem bottlenecks and showed that the path DMT is not the simple summation of DMT associated with each bottleneck along the path. Next, the authors examined the DMT of several paths passing through a common bottleneck. It is shown that the externality at the bottleneck is shared by the paths in proportion to their demand from the current time until the queue vanishes. This share of the externality is caused by the departure rate shift under first in first out (FIFO) and the externality propagates to the downstream bottlenecks. However, the externalities propagates to the downstream are calculated out if downstream bottlenecks exist. Therefore, the authors concluded that the path DMT can be evaluated without considering the propagation of the externalities, but just as in the evaluation of the path DMT for a single path passing through a series of bottlenecks between the origin and destination. Based on the DMT analysis, the authors finally proposed a heuristic solution algorithm and verified it by comparing the numerical solution with the analytical one.

Theory based production and project management

This paper gives an overview of an ongoing project endeavouring to advance theory-based production and project management, and the rationale for this approach is briefly justified. The status of the theoretical foundation of production management, project management and allied disciplines is discussed, with emphasis on metaphysical grounding of theories, as well as the nature of the heuristic solution method commonly used in these disciplines. Then, on-going work related to different aspects of production and project management is reviewed from both theoretical and practical orientation. Next, information systems agile project management is explored with a view to its re-use in generic project management. In production management, the consequences and implementation of a new, wider theoretical basis are analyzed. The theoretical implications and negative symptoms of the peculiarities of the construction industry for supply chains and supply chain management in construction are observed. Theoretical paths for improvements of inter-organisational relationships in construction which are fundamental for improvement of construction supply chains are described. To conclude, the observations made in this paper vis-à-vis production, project and supply chain management are related again to the theoretical basis of this paper, and finally directions for theory development and future research are given and discussed.

Reconnecting theory and practice in a pluralistic organizing context : issues and Aristotelian considerations

The overall purpose of this paper is to contribute to the theory - practice gap debate in organization studies, especially in pluralistic contexts such as project organizing. We briefly outline some of the current debates, i.e. modernist and postmodernist proposals, and the prevalent dichotomous thinking stance assumptions to better move beyond it, anchoring our contribution in the Aristotelian ethical and practical philosophy. We introduce the current state of the debate, part of the broad question of “science that matters”, and the various discourses between practice and academia within social sciences and more specifically organizational studies. We briefly critically summarize some main features of the two main philosophical stances (modernism, postmodernism), before presenting some key aspects, for the purpose of this paper, of the Aristotelian pre-modern practical and ethical philosophy. Then, we build on the foundations above established, discussing propositions to reconnect theory and practice according the Aristotelian ethical and practical philosophy, and some key implications for research notably in the following areas: roles played by practitioners and scholars, emancipatory praxeological style of reasoning, for closing the “phronetic gap” and reconnecting means and ends, facts and values, relation between collective praxis, development of “good practice” (standards), ethics and politics. We conclude highlighting the role of the suggested shift to an Aristotelian emancipatory style of reasoning for reconciling theory and practice.

Hyperbranched polymer-gold nanoparticle assemblies : role of polymer architecture in hybrid assembly formation and SERS activity

Plasmonic gold nano-assemblies that self-assemble with the aid of linking molecules or polymers have the potential to yield controlled hierarchies of morphologies and consequently result in materials with tailored optical (e.g. localized surface plasmon resonances (LSPR)) and spectroscopic properties (e.g. surface enhanced Raman scattering (SERS)). Molecular linkers that are structurally well-defined are promising for forming hybrid nano-assemblies which are stable in aqueous solution and are increasingly finding application in nanomedicine. Despite much ongoing research in this field, the precise role of molecular linkers in governing the morphology and properties of the hybrid nano-assemblies remains unclear. Previously we have demonstrated that branched linkers, such as hyperbranched polymers, with specific anchoring end groups can be successfully employed to form assemblies of gold NPs demonstrating near-infrared SPRs and intense SERS scattering. We herein introduce a tailored polymer as a versatile molecular linker, capable of manipulating nano-assembly morphologies and hot-spot density. In addition, this report explores the role of the polymeric linker architecture, specifically the degree of branching of the tailored polymer in determining the formation, morphology and properties of the hybrid nano-assemblies. The degree of branching of the linker polymer, in addition to the concentration and number of anchoring groups, is observed to strongly influence the self-assembly process. The assembly morphology shifts primarily from 1D-like chains to 2D plates and finally to 3D-like globular structures, with increase in degree of branching. Insights have been gained into how the morphology influences the SERS performance of these nano-assemblies with respect to hot-spot density. These findings supplement the understanding of the morphology determining nano-assembly formation and pave the way for the possible application of these nano-assemblies as SERS bio-sensors for medical diagnostics.

Self assembly of plasmonic core-satellite nano-assemblies mediated by hyperbranched polymer linkers

The morphology of plasmonic nano-assemblies has a direct influence on optical properties, such as localised surface plasmon resonance (LSPR) and surface enhanced Raman scattering (SERS) intensity. Assemblies with core-satellite morphologies are of particular interest, because this morphology has a high density of hot-spots, while constraining the overall size. Herein, a simple method is reported for the self-assembly of gold NPs nano-assemblies with a core-satellite morphology, which was mediated by hyperbranched polymer (HBP) linkers. The HBP linkers have repeat units that do not interact strongly with gold NPs, but have multiple end-groups that specifically interact with the gold NPs and act as anchoring points resulting in nano-assemblies with a large (~48 nm) core surrounded by smaller (~15 nm) satellites. It was possible to control the number of satellites in an assembly which allowed optical parameters such as SPR maxima and the SERS intensity to be tuned. These results were found to be consistent with finite-difference time domain (FDTD) simulations. Furthermore, the multiplexing of the nano-assemblies with a series of Raman tag molecules was demonstrated, without an observable signal arising from the HBP linker after tagging. Such plasmonic nano-assemblies could potentially serve as efficient SERS based diagnostics or biomedical imaging agents in nanomedicine.

High-voltage insulation organic-inorganic nanocomposites by plasma polymerization

In organic-inorganic nanocomposites, interfacial regions are primarily influenced by the dispersion uniformity of nanoparticles and the strength of interfacial bonds between the nanoparticles and the polymer matrix. The insulating performance of organic-inorganic dielectric nanocomposites is highly influenced by the characteristics of interfacial regions. In this study, we prepare polyethylene oxide (PEO)-like functional layers on silica nanoparticles through plasma polymerization. Epoxy resin/silica nanocomposites are subsequently synthesized with these plasma-polymerized nanoparticles. It is found that plasma at a low power (i.e., 10 W) can significantly increase the concentration of C-O bonds on the surface of silica nanoparticles. This plasma polymerized thin layer can not only improve the dispersion uniformity by increasing the hydrophilicity of the nanoparticles, but also provide anchoring sites to enable the formation of covalent bonds between the organic and inorganic phases. Furthermore, electrical tests reveal improved electrical treeing resistance and decreased dielectric constant of the synthesized nanocomposites, while the dielectric loss of the nanocomposites remains unchanged as compared to the pure epoxy resin.

Structure-mediated thermal transport of monolayer graphene allotropes nanoribbons

We report the study of the thermal transport management of monolayer graphene allotrope nanoribbons (size ∼20 × 4 nm2) by the modulation of their structures via molecular dynamics simulations. The thermal conductivity of graphyne (GY)-like geometries is observed to decrease monotonously with increasing number of acetylenic linkages between adjacent hexagons. Strikingly, by incorporating those GY or GY-like structures, the thermal performance of graphene can be effectively engineered. The resulting hetero-junctions possess a sharp local temperature jump at the interface, and show a much lower effective thermal conductivity due to the enhanced phonon–phonon scattering. More importantly, by controlling the percentage, type and distribution pattern of the GY or GY-like structures, the hetero-junctions are found to exhibit tunable thermal transport properties (including the effective thermal conductivity, interfacial thermal resistance and rectification). This study provides a heuristic guideline to manipulate the thermal properties of 2D carbon networks, ideal for application in thermoelectric devices with strongly suppressed thermal conductivity.

Human errors in computer related abuses

The term “Human error” can simply be defined as an error which made by a human. In fact, Human error is an explanation of malfunctions, unintended consequents from operating a system. There are many factors that cause a person to have an error due to the unwanted error of human. The aim of this paper is to investigate the relationship of human error as one of the factors to computer related abuses. The paper beings by computer-relating to human errors and followed by mechanism mitigate these errors through social and technical perspectives. We present the 25 techniques of computer crime prevention, as a heuristic device that assists. A last section discussing the ways of improving the adoption of security, and conclusion.

Pedestrian dynamics in real and simulated world

The paper examines the knowledge of pedestrian movements, both in real scenarios, and from more recent years, in the virtual 4 simulation realm. Aiming to verify whether it is possible to learn from the study of virtual environments how people will behave in real 5 environments, it is vital to understand what is already known about behavior in real environments. Besides the walking interaction among 6 pedestrians, the interaction between pedestrians and the built environment in which they are walking also have greatest relevance. Force-based 7 models were compared with the other three major microscopic models of pedestrian simulation to demonstrate a more realistic and capable 8 heuristic approach is needed for the study of the dynamics of pedestrians.

Centrobin regulates the assembly of functional mitotic spindles

The proper function of the spindle is crucial to the high fidelity of chromosome segregation and is indispensable for tumor suppression in humans. Centrobin is a recently identified centrosomal protein that has a role in stabilizing the microtubule structure. Here we functionally characterize the defects in centrosome integrity and spindle assembly in Centrobin-depleted cells. Centrobin-depleted cells show a range of spindle abnormalities including unfocused poles that are not associated with centrosomes, S-shaped spindles and mini spindles. These cells undergo mitotic arrest and subsequently often die by apoptosis, as determined by live cell imaging. Co-depletion of Mad2 relieves the mitotic arrest, indicating that cells arrest due to a failure to silence the spindle checkpoint in metaphase. Consistent with this, Centrobin-depleted metaphase cells stained positive for BubR1 and BubR1 S676. Staining with a panel of centrosome markers showed a loss of centrosome anchoring to the mitotic spindle. Furthermore, these cells show less cold-stable microtubules and a shorter distance between kinetochore pairs. These results show a requirement of Centrobin in maintaining centrosome integrity, which in turn promotes anchoring of mitotic spindle to the centrosomes. Furthermore, this anchoring is required for the stability of microtubule–kinetochore attachments and biogenesis of tension-ridden and properly functioning mitotic spindle.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Locality-sensitive hashing for protein classification

Determination of sequence similarity is a central issue in computational biology, a problem addressed primarily through BLAST, an alignment based heuristic which has underpinned much of the analysis and annotation of the genomic era. Despite their success, alignment-based approaches scale poorly with increasing data set size, and are not robust under structural sequence rearrangements. Successive waves of innovation in sequencing technologies – so-called Next Generation Sequencing (NGS) approaches – have led to an explosion in data availability, challenging existing methods and motivating novel approaches to sequence representation and similarity scoring, including adaptation of existing methods from other domains such as information retrieval. In this work, we investigate locality-sensitive hashing of sequences through binary document signatures, applying the method to a bacterial protein classification task. Here, the goal is to predict the gene family to which a given query protein belongs. Experiments carried out on a pair of small but biologically realistic datasets (the full protein repertoires of families of Chlamydia and Staphylococcus aureus genomes respectively) show that a measure of similarity obtained by locality sensitive hashing gives highly accurate results while offering a number of avenues which will lead to substantial performance improvements over BLAST..

A Memetic Algorithm for the location-based continuously operating reference stations placement problem in Network Real-Time Kinematic

Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.