Rafael Tolosana-Calasanz

University of Zaragoza | UNIZAR · Department of Computing and Systems Engineering

Performance interference can occur when various services are executed over the same physical infrastructure in a cloud system. This can lead to performance degradation compared to the execution of services in isolation. This work proposes a Confirmatory Factor Analysis (CFA)-based model to estimate performance interference across containers, caused...

The serverless computing model extends potential deployment options for cloud applications, by allowing users to focus on building and deploying their code without needing to configure or manage the underlying computational resources. Cost and latency constraints in stream processing user applications often push computations closer to the sources o...

Welcome to the 8th International Workshop on Cloud and Edge Computing, and Applications Management - CloudAM2019, which will be held in conjunction with the 12th IEEE/ACM Utility and Cloud Computing Conference (UCC) in Auckland, New Zealand, from 2-5 December 2019. CloudAM is a successful series of workshops that bring together practitioners and re...

The simplification of resource management for container is one of the most important services of Kubernetes. However, the simplification of distributed provisioning and scheduling decisions can impact significantly in cost outcomes. From an economic point of view, the most important factor to consider in container management is performance interfer...

Scientific workflows enable scientists to undertake analysis on large datasets and perform complex scientific simulations. These workflows are often mapped onto distributed and parallel computational infrastructures to speed up their executions. Prior to its execution, a workflow structure may suffer transformations to accommodate the computing inf...

A key challenge for supporting elastic behaviour in cloud systems is to achieve a good performance in automated (de-)provisioning and scheduling of computing resources. One of the key aspects that can be significant is the overheads associated with deploying, terminating and maintaining resources. Therefore, due to their lower start up and terminat...

The proliferation of sensors over the last years has generated large amounts of raw data, forming data streams that need to be processed. In many cases, cloud resources are used for such processing, exploiting their flexibility, but these sensor streaming applications often need to support operational and control actions that have real-time and low...

In container management systems, such as Kubernetes, the scheduler has to place containers in physical machines and it should be aware of the degradation in performance caused by placing together containers that are barely isolated. We propose that clients provide a characterization of their applications to allow a scheduler to evaluate what is the...

Scientific workflows emerged as a technology that enables scientists to undertake computational scientific experiments. Workflow enactors map workflow tasks onto distributed resources, hiding the inherent complexity of distributed infrastructures to the users. In the past, while the emphasis has been focused in adapting the workflow structure onto...

Recent advances in sensor technologies and instrumentation have led to an extraordinary growth of data sources and streaming applications. A wide variety of devices, from smart phones to dedicated sensors, have the capability of collecting and streaming data at unprecedented rates. Typical applications include smart cities & built environments for...

Recent advances in the type and variety of sensing technologies have led to an extraordinary growth in the volume of data being produced and led to a number of streaming applications that make use of this data. Sensors typically monitor environmental or physical phenomenon at predefined time intervals or triggered by user-defined events. Understand...

With the maturation of the Cloud Computing, the eyes of the scientific community and specialized commercial institutions have turned to research related to the use of multiple clouds. The main reason for this interest is the limitations that many cloud providers individually face to meet all the inherent characteristics of this paradigm. Therefore,...

Recent advances in sensor technologies and instrumentation have led to an extraordinary growth of data sources and streaming applications. A wide variety of devices, from smart phones to dedicated sensors, have the capability of collecting and streaming large amounts of data at unprecedented rates. A number of distinct streaming data models have be...

Requirements of Energy Management Services include short and long term processing of data in a massively interconnected scenario. The complexity and variety of short term applications needs methodologies that allow designers to reason about the models taking into account functional and non-functional requirements. In this paper we present a compone...

In this position paper, we envision a Platform-as-a-Service conceptual and architectural solution for large-scale and data intensive applications. Our architectural approach is based on autonomic principles, therefore, its ultimate goal is to reduce human intervention, the cost, and the perceived complexity by enabling the autonomic platform to man...

The number of applications that need to process data continuously over long periods of time has increased significantly over recent years. The emerging Internet of Things and Smart Cities scenarios also confirm the requirement for real time, large scale data processing. When data from multiple sources are processed over a shared distributed computi...

The ever-increasing density in cloud computing users, services, and data centres has led to significant increases in network traffic and the associated energy consumed by its huge infrastructure, e.g. extra servers, switches, routers, which is required to respond quickly and effectively to users requests. Transferring data, via a high bandwidth con...

Coordination of multiple concurrent data stream processing, carried out through a distributed Cloud infrastructure, is described. The coordination (control) is carried out through the use of a Reference net (a particular type of Petri net) based interpreter, implemented alongside the Comet Cloud system. One of the benefits of this approach is that...

This position paper brings to discussion a next step in the evolution of Cloud Computing as the organisation of multiple clouds. We summarise concepts related to the set of clouds called Inter-Cloud and its main elements (hybrid clouds, multi-clouds, etc.). We explore in more detail the Cloud Federation, which has stood as a well-behaved and volunt...

Streaming Applications are complex systems where the existence of concurrency, transmission of data and sharing of resources are essential characteristics. When these applications are run over Cloud infrastructures, the execution may incur an economical cost, and it can be therefore important to conduct an analysis prior to any execution. Such an a...

COSMOS, Computer Science for Complex System Modeling, is a research team that has the mission of bridging the gap between formal methods and real problems. The goal is twofold: (1) a better management of the growing complexity of current systems; (2) a high quality of the implementation reducing the time to market. The COSMOS vision is to prove thi...

With an increase in the number of monitoring sensors deployed on physical infrastructures, there is a corresponding increase in data volumes that need to be processed. Data measured or collected by sensors is typically processed at destination or "in-transit" (i.e. from data capture to delivery to a user). When such data are processed in-transit ov...

The Fish4Knowledge (F4K) project involves analysing video generated from multiple camera feeds to support environmental and ecological assessment. A workflow engine is utilised in the project which deals with on-demand user queries and batch queries, selection of a suitable computing platform on which to enact the workflow along with a selection of...

With the increasing availability of streaming applications from mobile devices to dedicated sensors, understanding how such streaming content can be processed within some time threshold remains an important requirement. We investigate how a computational infrastructure responds to such streaming content based on the revenue per stream – taking acco...

In recent years, the rise and rapid adoption of cloud computing has acted as a catalyst for research in related fields: virtualization, distributed and service-oriented computing to name but a few. Whilst cloud computing technology is rapidly maturing, many of the associated long-standing socio-technical challenges including the dependability of cl...

With an increasing interest in Electric Vehicles (EVs), it is essential to understand how EV charging could impact demand on the Electricity Grid. Existing approaches used to achieve this make use of a centralised data collection mechanism - which often is agnostic of demand variation in a given geographical area. We present an in-transit data proc...

When data from multiple sources (sensors) are processed over a shared distributed computing infrastructure, it is necessary to often provide some Quality of Service (QoS) guarantees to each data stream. Service Level Agreements (SLAs) identify the cost that a user must pay to achieve the required QoS, and a penalty that must be paid to the user in...

The ability to support Quality of Service (QoS) constraints is an important requirement in some scientific applications. With the increasing use of Cloud computing infrastructures, where access to resources is shared, dynamic and provisioned on-demand, identifying how QoS constraints can be supported becomes an important challenge. However, access...

When multiple users execute their streaming applications over a shared Cloud infrastructure, the provider typically captures the Quality of Service (QoS) for each application at a Service Level Agreement (SLA). Such an SLA identifies the cost that a user must pay to achieve the required QoS, and a penalty that must be paid to the user in case the Q...

In data intensive workflows, which often involve files, transfer between tasks is typically accomplished as fast as the network links allow, and once transferred, the files are buffered/stored at their destination. Where a task requires multiple files to execute (from different previous tasks), it must remain idle until all files are available. Hen...

The increasing deployment of sensor network infrastructures has led to large volumes of data becoming available, leading to new challenges in storing, processing and transmitting such data. This is especially true when data from multiple sensors is pre-processed prior to delivery to users. Where such data is processed in-transit (i.e. from data cap...

Data movement between tasks in scientific workflows has received limited attention compared to task execution. Often the staging of data between tasks is either assumed or the time delay in data transfer is considered to be negligible (compared to task execution). Where data consists of files, such file transfers are accomplished as fast as the net...

The enactment of scientific workflows involves the distribution of tasks to distributed resources that exist in different administrative domains. Such resources can range in granularity from a single machine to one or more clusters and file systems. The use of such distributed resources during workflow enactment can be an error prone process and ma...

Interest in data streaming within scientific workflow has increased significantly over the recent years—mainly due to the emergence of data-driven applications. Such applications can include data streaming from sensors and data coupling between scientific simulations. To support resource management to enact such streaming-based workflow, autonomic...

Scientific workflows generally involve the distribution of tasks to distributed resources, which may exist in different administrative domains. The use of distributed resources in this way may lead to faults, and detecting them, identifying them and subsequently correcting them remains an important research challenge. We introduce a fault taxonomy...

There is emerging interest in many scientific disciplines to deal with "dynamic" data, arising from sensors and scientific instruments, which require workflow graphs that can be dynamically adapted - as new data becomes available. Additionally, the elastic nature of many Cloud environments subsequently enable such dynamic workflow graphs to be enac...

Scientific workflow systems often operate in unreliable environments, and have accordingly incorporated different fault tolerance techniques. One of them is the checkpointing technique combined with its corresponding rollback recovery process. Different checkpointing schemes have been developed and at various levels: task- (or activity-) level and...

Scientific workflow systems often operate in highly unreliable, heterogeneous and dynamic environments, and have accordingly incorporated different fault tolerance techniques. We propose an exception-handling mechanism, based on techniques adopted in programming languages, for modifying at run-time the structure of a workflow. In contrast to other...

ABSTRACT Scientific workflows generally involve the distribution of tasks to distributed resources, which may exist in different admin- istrative domains. Such a distribution may,lead to faults that may arise at different levels: application level, enact- ment level, and resource management level, for instance. Detecting these faults, and subsequen...

Workflow systems provide support for combining components to achieve a particular outcome. Various approaches from software engineering have been utilized within such systems, such as the use of design patterns to support composition, and the use of a software engineering lifecycle to support workflow construction and execution. As components used...

There is growing interest in promoting interoperability among the many different existent grid initiatives. The requirements for interlinking of grids have already been studied from a general point of view. In this paper, we analyse current practice in grid interactions and show evidence of how grid interactions may represent a barrier for interlin...

Because of the nature of the Grid, Grid application systems built on traditional software development techniques can only interoperate with Grid services in an ad hoc manner that requires substantial human intervention. In this paper, we introduce Vega, a pure service-oriented Grid workflow system which consists of a set of loosely coupled services...

Geographic metadata quality is one of the most important aspects on the performance of Geographic Digital Libraries. After re- viewing previous attempts outside the geographic domain, this paper presents early results from a series of experiments for the development of a quantitative method for quality assessment. The methodology is de- veloped thr...

The tendency of current cataloguing systems is to interchange metadata in XML according to the specific standard required by each user on demand. Furthermore, metadata schemas from different domains are not usually semantically distinct but overlap and relate to each other in complex ways. As a consequence, the semantic interoperability has to deal...

Geographic metadata quality is one of the most important aspects on the performance of Geographic Digital Libraries. After reviewing previous attempts outside the geographic domain, this paper presents early results from a series of experiments for the development of a quantitative method for quality assessment. The methodology is developed through...

The importance of interoperability among computer systems has been progressively increasing over the last years. The tendency of current cataloguing systems is to interchange metadata in XML according to the specific standard required by each user on demand. According to the research literature, it seems that there exist two main approaches in orde...

SUMMARY This paper will present CatServer: a server of GATOS (the Spanish word GATOS means cats) a functional kernel which provides catalogue services for any XML-coded metadata. CatServer has been used for the creation of geographical dataset catalogues, catalogues of services, geocoders, Web Feature Servers and gazetteers. Nonetheless, in order t...