Philip D. Healy

A survey of Cloud monitoring tools: Taxonomy, capabilities and objectives

a b s t r a c t The efficient management of Cloud infrastructure and deployments is a topic that is currently attracting significant interest. Complex Cloud deployments can result in an intricate layered structure. Understanding the behaviour of these hierarchical systems and how to manage them optimally are challenging tasks that can be facilitated by pervasive monitoring. Monitoring tools and techniques have an important role to play in this area by gathering the information required to make informed decisions. A broad variety of monitoring tools are available, from general-purpose infrastructure monitoring tools that predate Cloud computing, to high-level application monitoring services that are themselves hosted in the Cloud. Surveying the capabilities of monitoring tools can identify the fitness of these tools in serving certain objectives. Monitoring tools are essential components to deal with various objectives of both Cloud providers and consumers in different Cloud operational areas. We have identified the practical capabilities that an ideal monitoring tool should possess to serve the objectives in these operational areas. Based on these identified capabilities, we present a taxonomy and analyse the monitoring tools to determine their strength and weaknesses. In conclusion, we present our reflections on the analysis, discuss challenges and identify future research trends in the area of Cloud monitoring.

Architecture and implementation of a distributed reconfigurable metacomputer

The use of application-specific co-processors created using reconfigurable hardware (FPGAs) has been shown to realize significant speed increases for many computationally intensive applications. The addition of reconfigurable hardware to clusters composed of commodity machines in order to improve the execution times of parallel applications would, therefore, appear to be a logical step. However, the extra complications introduced by this technique may make the real-world application of such technology appear to be prohibitively difficult. In this paper the design and implementation of a metacomputer designed to simplify the development of applications for clusters containing re-configurable hardware are presented. The operation of the metacomputer is also discussed in some detail, including the process of implementing applications for execution on the metacomputer.

Development of a Cloud Trust Label: A Delphi Approach

ABSTRACT The purpose of this research is to identify the potential information components of an online, real-time trust label, which is proposed as a communication mechanism to encourage trust in cloud service providers and cloud computing products. An online Delphi process was used with 28 cloud computing experts (including vendors, software providers, and legal and business representatives). The proposed label contains 81 information components, covering the cloud service provider (e.g. physical location, legal jurisdiction), the cloud service itself (e.g. data location, security, backup, certification), and a historical service-level summary (e.g. uptime data, support response times). The potential benefits of such a label to encourage trustworthiness perceptions and trust behaviors in the cloud computing environment are explored. Limitations of the study are highlighted, and further research studies are suggested to test the concept of the label and to refine the components of the label itself.

Towards a general research framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

Web-based remote monitoring of live EEG

In a critical care setting, delays in the diagnosis of neurological conditions can have a significant impact on patient outcomes. Recording the electrical activity of the brain (EEG) is often used to diagnose and monitor neurological conditions. A trained neurophysiologist is then required to analyse these signals. However, in many cases this expertise is not available on-site. A web-based remote monitoring system for EEG data is presented that reduces the delays that can arise when off-site expert analysis is required. The system allows EEG data to be streamed to a remote location in near-real-time and viewed while acquisition is ongoing. Data streamed earlier may also be reviewed, providing the user with a continually updating view of the entire EEG recording. All communications are performed using web technologies in order to minimise issues with firewalls and to enable analysis on most web-connected PCs. The only tool required for viewing EEG data is a modern web browser with the commonly-available Adobe Flash plugin installed. Since these are ubiquitous, data analysis is not limited by geographic location. Moreover, multiple users can independently view the data simultaneously

A Cloud-Based IoT Data Gathering and Processing Platform

The deployment of Internet of Things (IoT) smart devices, including sensors, is progressing at a rapid pace. However, the volume of data they generate is becoming difficult to store and process on local platforms. The scalability offered by Cloud computing provides a solution to this problem. Cloud computing provides resources at low cost for its users. However, platform-independent methods of gathering and transmitting sensor data to Clouds are not widely available. This paper presents a Cloud-based smart device data monitoring, gathering and processing platform. It first reviews the state-of-the-art embodied by the existing solutions and discusses their strengths and weaknesses. Informed by the survey analysis, a generic architecture is presented that addresses the identified challenges facing data gathering and processing in this area. Based on use case scenarios, we evaluate and demonstrate the novelty of our proposed platform.

Quality Assurance for Open Source Software Configuration Management

Commonly used open source configuration management systems, such as Puppet, Chef and CFEngine, allow for system configurations to be expressed as scripts. A number of quality issues that may arise when executing these scripts are identified. An automated quality assurance service is proposed that identifies the presence of these issues by automatically executing scripts across a range of environments. Test results are automatically published to a format capable of being consumed by script catalogues and social coding sites. This would serve as an independent signal of script trustworthiness and quality to script consumers and would allow developers to be made quickly aware of quality issues. As a result, potential consumers of scripts can be assured that a script is likely to work when applied to their particular environment. Script developers can be notified of compatibility issues and take steps to address them.

Analysis of Data Interchange Formats for Interoperable and Efficient Data Communication in Clouds

Efficient mechanisms for data structuring and formatting are indispensable for managing data traffic between and within federated Cloud environments to avoid excessive bandwidth cost and to ensure portability and interoperability. This facilitates provider-agnostic communication, which is essential for interoperable inter-Cloud deployments and portable integration of service components, both with one another and with the underlying Cloud platform. The existing data interchange formats for structuring and serialising data have not yet been analysed in the context of data communication in Clouds. Thus, to address this issue, the determination of an appropriate data interchange format for Clouds is necessary. In this paper, we present a performance analysis of some selected data interchange formats to assess their efficiency in terms of their usability in realising a common messaging format for communicating data in Clouds. We first describe the characteristics of each data format for clear understanding. As a basis for the analysis, we introduce a Cloud use case scenario comprising the transmission of monitored data as messages. The communication means is achieved with a novel message bus system designed to integrate the data interchange formats. We present some evaluations of the formats and compare their compactness for supporting efficient data transmission in Clouds.

Job Management in WebCom

WebCom is a metacomputer based on the Condensed Graphs model of computing. Within this model, applications are represented as directed acyclic graphs with the nodes representing tasks and arcs their sequencing constraints. This paper presents the job management system used in WebCom. We describe the techniques required to apply common job management concepts, such as suspension, migration and monitoring, to the execution of applications expressed as Condensed Graphs.

A Trust Label System for Communicating Trust in Cloud Services

Cloud computing is rapidly changing the digital service landscape. A proliferation of Cloud providers has emerged, increasing the difficulty of consumer decisions. Trust issues have been identified as a factor holding back Cloud adoption. The risks and challenges inherent in the adoption of Cloud services are well recognised in the computing literature. In conjunction with these risks, the relative novelty of the online environment as a context for the provision of business services can increase consumer perceptions of uncertainty. This uncertainty is worsened in a Cloud context due to the lack of transparency, from the consumer perspective, into the service types, operational conditions and the quality of service offered by the diverse providers. Previous approaches failed to provide an appropriate medium for communicating trust and trustworthiness in Clouds. A new strategy is required to improve consumer confidence and trust in Cloud providers. This paper presents the operationalisation of a trust label system designed to communicate trust and trustworthiness in Cloud services. We describe the technical details and implementation of the trust label components. Based on a use case scenario, an initial evaluation was carried out to test its operations and its usefulness for increasing consumer trust in Cloud services.