SNB-index: a SkipNet and B+ tree based auxiliary Cloud index

Distributed data management plays an essential part in internet applications. With benefits of scalability and reliability, the Cloud storage systems have become an attractive choice for large-scale data processing. However, most Cloud storage systems currently adopt a hash-like approach to retrieve data that only support simple keyword-based enquiries, but lack various forms of information search. In this paper, we propose a novel SkipNet and B+ tree based index structure, called SNB-index, for Cloud computing systems. SNB-index adopts a two-layer architecture. In the lower layer, it uses the B+ tree to construct efficient local index. In the upper layer, it adaptively selects among local index nodes to form a SkipNet based global overlay. Our scalable auxiliary Cloud index can efficiently support a variety of types of queries (e.g. point-query, range-query, similarity-query), and provide high availability. Some new routing algorithms and mapping processing algorithms are designed to enhance performance. Experimental results show that SNB-index is valid and can be an alternative approach for constructing an auxiliary index in Cloud computing systems.     

Interconnecting Federated Clouds by Using Publish-Subscribe Service

Cloud Federation is an emerging computing model where multiple resources from independent Cloud providers are leveraged to create large-scale distributed virtual computing clusters, operating as into a single Cloud organization. This model enables the implementation of environmental diversity for Cloud applications, and overcomes the provisioning and scalability limits of a single Cloud, by introducing minimal additional cost for the Cloud consumer. In such a scenario, it is necessary to leverage on specific networking technologies that enable the effective support of inter-Cloud communication services between Cloud providers. This paper proposes an interconnection solution for Cloud federations based on publish/subscribe services. Moreover, we discuss some fundamental concerns needed to satisfy the inter-Cloud communication requirements in terms of reliability and availability. Finally, we present some experimental results that highlight some key reliability and denial of service vulnerability concerns in this domain.     

Software architecture definition for on-demand cloud provisioning

Cloud computing is a promising paradigm for the provisioning of IT services. Cloud computing infrastructures, such as those offered by the RESERVOIR project, aim to facilitate the deployment, management and execution of services across multiple physical locations in a seamless manner. In order for service providers to meet their quality of service objectives, it is important to examine how software architectures can be described to take full advantage of the capabilities introduced by such platforms. When dealing with software systems involving numerous loosely coupled components, architectural constraints need to be made explicit to ensure continuous operation when allocating and migrating services from one host in the Cloud to another. In addition, the need for optimising resources and minimising over-provisioning requires service providers to control the dynamic adjustment of capacity throughout the entire service lifecycle. We discuss the implications for software architecture definitions of distributed applications that are to be deployed on Clouds. In particular, we identify novel primitives to support service elasticity, co-location and other requirements, propose language abstractions for these primitives and define their behavioural semantics precisely by establishing constraints on the relationship between architecture definitions and Cloud management infrastructures using a model denotational approach in order to derive appropriate service management cycles. Using these primitives and semantic definition as a basis, we define a service management framework implementation that supports on demand cloud provisioning and present a novel monitoring framework that meets the demands of Cloud based applications.     

Protection goals in environmental risk assessment: a practical approach

Policy protection goals are set up in most countries to minimise harm to the environment, humans and animals caused by human activities. Decisions on whether to approve new agricultural products, like pesticides or genetically modified (GM) crops, take into account these policy protection goals. To support decision-making, applications for approval of commercial uses of GM crops usually comprise an environmental risk assessment (ERA). These risk assessments are analytical tools, based on science, that follow a conceptual model that includes a problem formulation step where policy protection goals are considered. However, in most countries, risk assessors face major problems in that policy protection goals set in the legislation are stated in very broad terms and are too ambiguous to be directly applicable in ERAs. This means that risk assessors often have to interpret policy protection goals without clear guidance on what effects would be considered harmful. In this paper we propose a practical approach that may help risk assessors to translate policy protection goals into unambiguous (i.e., operational) protection goals and to establish relevant assessment endpoints and risk hypotheses that can be used in ERAs. Examples are provided to show how this approach can be applied to two areas of environmental concern relevant to the ERAs of GM crops.     

Developing a Model Driven Approach for engineering applications based on mOSAIC

In many scientific and engineering areas there are emerging software services available over the Web. The reason for deploying such services in the Cloud is either to reduce the operational costs or to support the peaks in their usage profiles. The algorithms employed in such services are usually result of a long term research and technology development work, so it is beneficial to reuse those critical application parts when developing new Cloud applications. This paper investigates the possibilities to introduce a Model Driven Architecture (MDA) for the Cloud computing domain, which would support composition, customization, flexibility, maintenance and reusability of Cloud application components in the particular case of scientific and engineering applications. The underlying middleware technology of choice is the mOSAIC Platform as a Service (PaaS) solution. This choice is motivated by the fact that in mOSAIC a Cloud application consists of loosely coupled components, which are either generic and provide for key resource types needed by an application (computation, storage, communication) or custom made, e.g. based on existing legacy software. The MDA approach is illustrated through the design and operation of an application for analysis of structures under static loading. It is shown that a relatively simple design can be used to address two application bottlenecks: the varying number of users and the computational complexity of the given problem. The design reduces the necessary application development efforts and the key components can be reused for similar applications.     

Artificial cell-cell communication in yeast Saccharomyces cerevisiae using signaling elements from Arabidopsis thaliana

The construction of synthetic cell-cell communication networks can improve our quantitative understanding of naturally occurring signaling pathways and enhance our capabilities to engineer coordinated cellular behavior in cell populations. Towards accomplishing these goals in eukaryotes, we developed and analyzed two artificial cell-cell communication systems in yeast. We integrated Arabidopsis thaliana signal synthesis and receptor components with yeast endogenous protein phosphorylation elements and new response promoters. In the first system, engineered yeast 'sender' cells synthesize the plant hormone cytokinin, which diffuses into the environment and activates a hybrid exogenous/endogenous phosphorylation signaling pathway in nearby engineered yeast 'receiver' cells. For the second system, the sender network was integrated into the receivers under positive-feedback regulation, resulting in population density-dependent gene expression (that is, quorum sensing). The combined experimental work and mathematical modeling of the systems presented here can benefit various biotechnology applications for yeast and higher level eukaryotes, including fermentation processes, biomaterial fabrication and tissue engineering.     

RALBA: a computation-aware load balancing scheduler for cloud computing

Cloud computing serves as a platform for remote users to utilize the heterogeneous resources in data-centers to compute High-Performance Computing jobs. The physical resources are virtualized in Cloud to entertain user services employing Virtual Machines (VMs). Job scheduling is deemed as a quintessential part of Cloud and efficient utilization of VMs by Cloud Service Providers demands an optimal job scheduling heuristic. An ideal scheduling heuristic should be efficient, fair, and starvation-free to produce a reduced makespan with improved resource utilization. However, static heuristics often lead to inefficient and poor resource utilization in the Cloud. An idle and underutilized host machine in Cloud still consumes up to 70% of the energy required by an active machine (Ray, in Indian J Comput Sci Eng 1(4):333–339, 2012). Consequently, it demands a load-balanced distribution of workload to achieve optimal resource utilization in Cloud. Existing Cloud scheduling heuristics such as Min–Min, Max–Min, and Sufferage distribute workloads among VMs based on minimum job completion time that ultimately causes a load imbalance. In this paper, a novel Resource-Aware Load Balancing Algorithm (RALBA) is presented to ensure a balanced distribution of workload based on computation capabilities of VMs. The RABLA framework comprises of two phases: (1) scheduling based on computing capabilities of VMs, and (2) the VM with earliest finish time is selected for jobs mapping. The outcomes of the RALBA have revealed that it provides substantial improvement against traditional heuristics regarding makespan, resource utilization, and throughput.     

HEALTH,VITAL GOALS,AND CENTRAL HUMAN CAPABILITIES

I argue for a conception of health as a person's ability to achieve or exercise a cluster of basic human activities. These basic activities are in turn specified through free‐standing ethical reasoning about what constitutes a minimal conception of a human life with equal human dignity in the modern world. I arrive at this conception of health by closely following and modifying Lennart Nordenfelt's theory of health which presents health as the ability to achieve vital goals. Despite its strengths I transform Nordenfelt's argument in order to overcome three significant drawbacks. Nordenfelt makes vital goals relative to each community or context and significantly reflective of personal preferences. By doing so, Nordenfelt's conception of health faces problems with both socially relative concepts of health and subjectively defined wellbeing. Moreover, Nordenfelt does not ever explicitly specify a set of vital goals. The theory of health advanced here replaces Nordenfelt's (seemingly) empty set of preferences and society‐relative vital goals with a human species‐wide conception of basic vital goals, or ‘central human capabilities and functionings’. These central human capabilities come out of the capabilities approach (CA) now familiar in political philosophy and economics, and particularly reflect the work of Martha Nussbaum. As a result, the health of an individual should be understood as the ability to achieve a basic cluster of beings and doings—or having the overarching capability, a meta‐capability, to achieve a set of central or vital inter‐related capabilities and functionings.     

Bioremoval of heavy metals by the use of microalgae

Bioremoval, the use of biological systems for the removal of metal ions from polluted waters, has the potential to achieve greater performance at lower cost than conventional wastewater treatment technologies for metal removal. Bioremoval capabilities of microalgae have been extensively studied, and some commercial applications have been initiated. Although microalgae are not unique in their bioremoval capabilities, they offer advantages over other biological materials in some conceptual bioremoval process schemes. Selected microalgae strains, purposefully cultivated and processed for specific bioremoval applications, have the potential to provide significant improvements in dealing with the world-wide problems of metal pollution. In addition to strain selection, significant advances in the technology appear possible by improving biomass containment or immobilization techniques and by developing bioremoval process steps utilizing metabolically active microalgae cultures. The latter approach is especially attractive in applications where extremely low levels of residual metal ions are desired. This review summarizes the current literature, highlighting the potential benefits and problems associated with the development of novel algal-based bioremoval processes for the abatement of heavy metal pollution.     

Monitoring and evaluating large-scale, ‘open-ended’ habitat creation projects: A journey rather than a destination

Ecological restoration frequently involves setting fixed species or habitat targets to be achieved by prescribed restoration activities or through natural processes. Where no reference systems exist for defining outcomes or where restoration is planned on a large spatial scale, a more ‘open-ended’ approach to defining outcomes may be appropriate. Such approaches require changes to the definition of goals and the design of monitoring and evaluation activities. We suggest that in open-ended projects restoration goals should be framed in terms of promoting natural processes, mobile landscape mosaics and improved ecosystem services. Monitoring can then focus on the biophysical processes that underpin the development of habitat mosaics and the provision of ecosystem services, on the way habitat mosaics change through time and on species that can indicate the changing landscape attributes of connectivity and scale. Stakeholder response should be monitored since an open-ended restoration approach is unusual and can encounter institutional and societal constraints. Evaluation should focus on reporting changing restoration impacts and benefits rather than on achieving a pre-defined concept of ecological success.     

Some Remarks on the Socio-Cultural Background of Restoration Ecology

Restoration ecology plays an important role in nature conservation policy in Europe today. It establishes the scientific basis for restoring ecosystems altered or destroyed by man to a more “natural” state. The goals of restoration ecology can generally be described in terms of increased biodiversity, enhanced water retention capacity, avoidance of soil erosion, etc. In practice, however, a discrepancy exists between the high ideals of restoration goals and reality, where one often encounters limiting factors. These limiting factors can include the conflict between different restoration goals, the unpredictability of restoration goals owing to long‐term effects and stochastic events, the insufficient social acceptance of landscape changes during restoration processes, and the use of restoration processes themselves (e.g., undisturbed succession, certain management measures like impoverishment of fertilized areas) as restoration goals in place of a certain resource quality (such as species composition, population sizes, water quality). Two examples from southern Germany show that restoration goals in European cultural landscapes can only be implemented successfully when they are integrated into the respective land use systems.     

Web-based applications for building, managing and analysing kinetic models of biological systems

Mathematical modelling and computational analysis play an essentialrole in improving our capability to elucidate the functionsand characteristics of complex biological systems such as metabolic,regulatory and cell signalling pathways. The modelling and concomitantsimulation render it possible to predict the cellular behaviourof systems under various genetically and/or environmentallyperturbed conditions. This motivates systems biologists/bioengineers/bioinformaticiansto develop new tools and applications, allowing non-expertsto easily conduct such modelling and analysis. However, amonga multitude of systems biology tools developed to date, onlya handful of projects have adopted a web-based approach to kineticmodelling. In this report, we evaluate the capabilities andcharacteristics of current web-based tools in systems biologyand identify desirable features, limitations and bottlenecksfor further improvements in terms of usability and functionality.A short discussion on software architecture issues involvedin web-based applications and the approaches taken by existingtools is included for those interested in developing their ownsimulation applications.      

A coupled discrete/continuum model for describing cancer-therapeutic transport in the lung

We propose a computational simulation framework for describing cancer-therapeutic transport in the lung. A discrete vascular graph model (VGM) is coupled to a double-continuum model (DCM) to determine the amount of administered therapeutic agent that will reach the cancer cells. An alveolar cell carcinoma is considered. The processes in the bigger blood vessels (arteries, arterioles, venules and veins) are described by the VGM. The processes in the alveolar capillaries and the surrounding tissue are represented by a continuum approach for porous media. The system of equations of the coupled discrete/continuum model contains terms that account for degradation processes of the therapeutic agent, the reduction of the number of drug molecules by the lymphatic system and the interaction of the drug with the tissue cells. The functionality of the coupled discrete/continuum model is demonstrated in example simulations using simplified pulmonary vascular networks, which are designed to show-off the capabilities of the model rather than being physiologically accurate.     

Multi-objective workflow scheduling in Amazon EC2

Nowadays, scientists and companies are confronted with multiple competing goals such as makespan in high-performance computing and economic cost in Clouds that have to be simultaneously optimised. Multi-objective scheduling of scientific applications in these systems is therefore receiving increasing research attention. Most existing approaches typically aggregate all objectives in a single function, defined a-priori without any knowledge about the problem being solved, which negatively impacts the quality of the solutions. In contrast, Pareto-based approaches having as outcome a set of (nearly) optimal solutions that represent a tradeoff among the different objectives, have been scarcely studied. In this paper, we analyse MOHEFT, a Pareto-based list scheduling heuristic that provides the user with a set of tradeoff optimal solutions from which the one that better suits the user requirements can be manually selected. We demonstrate the potential of our method for multi-objective workflow scheduling on the commercial Amazon EC2 Cloud. We compare the quality of the MOHEFT tradeoff solutions with two state-of-the-art approaches using different synthetic and real-world workflows: the classical HEFT algorithm for single-objective scheduling and the SPEA2* genetic algorithm used in multi-objective optimisation problems. The results demonstrate that our approach is able to compute solutions of higher quality than SPEA2*. In addition, we show that MOHEFT is more suitable than SPEA2* for workflow scheduling in the context of commercial Clouds, since the genetic-based approach is unable of dealing with some of the constraints imposed by these systems.     

Software quality in the clouds: a cloud-based solution

Cloud computing, an on-demand computation model that consists of large data-centers (Clouds) managed by cloud providers, offers storage and computation needs for cloud users based on service level agreements (SLAs). Services in cloud computing are offered at relatively low cost. The model, therefore, forms a great target for many applications, such as startup businesses and e-commerce applications. The area of cloud computing has grown rapidly in the last few years; yet, it still faces some obstacles. For example, there is a lack of mechanisms that guarantee for cloud users the quality that they are actually getting, compared to the quality of service that is specified in SLAs. Another example is the concern of security, privacy and trust, since users lose control over their data and programs once they are sent to cloud providers. In this paper, we introduce a new architecture that aids the design and implementation of attestation services. The services monitor cloud-based applications to ensure software quality, such as security, privacy, trust and usability of cloud-based applications. Our approach is a user-centric approach through which users have more control on their own data/applications. Further, the proposed approach is a cloud-based approach where the powers of the clouds are utilized. Simulation results show that many services can be designed based on our architecture, with limited performance overhead.     

Nephele streaming: stream processing under QoS constraints at scale

The ability to process large numbers of continuous data streams in a near-real-time fashion has become a crucial prerequisite for many scientific and industrial use cases in recent years. While the individual data streams are usually trivial to process, their aggregated data volumes easily exceed the scalability of traditional stream processing systems. At the same time, massively-parallel data processing systems like MapReduce or Dryad currently enjoy a tremendous popularity for data-intensive applications and have proven to scale to large numbers of nodes. Many of these systems also provide streaming capabilities. However, unlike traditional stream processors, these systems have disregarded QoS requirements of prospective stream processing applications so far. In this paper we address this gap. First, we analyze common design principles of today’s parallel data processing frameworks and identify those principles that provide degrees of freedom in trading off the QoS goals latency and throughput. Second, we propose a highly distributed scheme which allows these frameworks to detect violations of user-defined QoS constraints and optimize the job execution without manual interaction. As a proof of concept, we implemented our approach for our massively-parallel data processing framework Nephele and evaluated its effectiveness through a comparison with Hadoop Online. For an example streaming application from the multimedia domain running on a cluster of 200 nodes, our approach improves the processing latency by a factor of at least 13 while preserving high data throughput when needed.     

Dielectrophoretic platforms for bio-microfluidic systems

Dielectrophoresis, the induced motion of polarisable particles in a nonuniform electric field, has been proven as a versatile mechanism to transport, accumulate, separate and characterise micro/nano scale bioparticles in microfluidic systems. The integration of DEP systems into the microfluidics enables the inexpensive, fast, highly sensitive, highly selective and label-free detection and analysis of target bioparticles. This review provides an in-depth overview of state-of-the-art dielectrophoretic (DEP) platforms integrated into microfluidics aimed towards different biomedical applications. It classifies the current DEP systems in terms of different microelectrode configurations and operating strategies devised to generate and employ DEP forces in such processes, and compares the features of each approach. Finally, it suggests the future trends and potential applications of DEP systems in single cell analysis, stem cell research, establishing novel devices, and realising fully DEP-activated lab-on-a-chip systems.     

RNA structure comparison,motif search and discovery using a reduced representation of RNA conformational space

Given the wealth of new RNA structures and the growing list of RNA functions in biology, it is of great interest to understand the repertoire of RNA folding motifs. The ability to identify new and known motifs within novel RNA structures, to compare tertiary structures with one another and to quantify the characteristics of a given RNA motif are major goals in the field of RNA research; however, there are few systematic ways to address these issues. Using a novel approach for visualizing and mathematically describing macromolecular structures, we have developed a means to quantitatively describe RNA molecules in order to rapidly analyze, compare and explore their features. This approach builds on the alternative eta,theta convention for describing RNA torsion angles and is executed using a new program called PRIMOS. Applying this methodology, we have successfully identified major regions of conformational change in the 50S and 30S ribosomal subunits, we have developed a means to search the database of RNA structures for the prevalence of known motifs and we have classified and identified new motifs. These applications illustrate the powerful capabilities of our new RNA structural convention, and they suggest future adaptations with important implications for bioinformatics and structural genomics.     

Natural selection. IV. The Price equation

The Price equation partitions total evolutionary change into two components. The first component provides an abstract expression of natural selection. The second component subsumes all other evolutionary processes, including changes during transmission. The natural selection component is often used in applications. Those applications attract widespread interest for their simplicity of expression and ease of interpretation. Those same applications attract widespread criticism by dropping the second component of evolutionary change and by leaving unspecified the detailed assumptions needed for a complete study of dynamics. Controversies over approximation and dynamics have nothing to do with the Price equation itself, which is simply a mathematical equivalence relation for total evolutionary change expressed in an alternative form. Disagreements about approach have to do with the tension between the relative valuation of abstract versus concrete analyses. The Price equation's greatest value has been on the abstract side, particularly the invariance relations that illuminate the understanding of natural selection. Those abstract insights lay the foundation for applications in terms of kin selection, information theory interpretations of natural selection and partitions of causes by path analysis. I discuss recent critiques of the Price equation by Nowak and van Veelen.     

Identifying constraints that govern cell behavior: a key to converting conceptual to computational models in biology?

Cells must abide by a number of constraints. The environmental constrains of cellular behavior and physicochemical limitations affect cellular processes. To regulate and adapt their functions, cells impose constraints on themselves. Enumerating, understanding, and applying these constraints leads to a constraints-based modeling formalism that has been helpful in converting conceptual models to computational models in biology. The continued success of the constraints-based approach depends upon identification and incorporation of new constraints to more accurately define cellular capabilities. This review considers constraints in terms of environmental, physicochemical, and self-imposed regulatory and evolutionary constraints with the purpose of refining current constraints-based models of cell phenotype.