Contemporary analysis and architecture for a generic cloud-based sensor data management platform.

An increasing volume of data is being generated by sensors and smart devices deployed in different areas, often far from computing facilities such as data centres. These data can be difficult to gather and process using local computing infrastructure. This is due to cost and limited resources. Cloud computing provides scalable resources that are capable of addressing such problems. However, platform-independent methods of gathering and transmitting sensor data to Clouds are not widely available. This paper presents a state-of-the-art analysis of Cloud-based sensor monitoring and data gathering platforms. It discusses their strengths and weaknesses and reviews the current trends in this area. Informed by the analysis, the paper further proposes a generic conceptual architecture for achieving a platform-neutral Cloud-based sensor monitoring and data gathering platform. We also discuss the objectives, design decisions and the implementation considerations for the conceptual architecture.IC

Building consumer trust in the cloud: an experimental analysis of the cloud trust label approach

The lack of transparency surrounding cloud service provision makes it difficult for consumers to make knowledge based purchasing decisions. As a result, consumer trust has become a major impediment to cloud computing adoption. Cloud Trust Labels represent a means of communicating relevant service and security information to potential customers on the cloud service provided, thereby facilitating informed decision making. This research investigates the potential of a Cloud Trust Label system to overcome the trust barrier. Specifically, it examines the impact of a Cloud Trust Label on consumer perceptions of a service and cloud service provider trustworthiness and trust in the cloud service and cloud service provider. An experimental study was carried out with a sample of 227 business decision makers with data collected before exposure to the label to examine initial perceptions and after exposure to the label to examine any change in perceptions and attitudes. As hypothesised, the results suggest that Cloud Trust Labels that contain positive information can have a positive impact on trust and trustworthiness while Cloud Trust Labels that contain negative information have a negative impact. The practical implications of this new method of communicating trustworthiness online are discussed and recommendations are made for future research

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.N/

Cost and Benefit of the SLA Mapping Approach for Defining Standardized Goods in Cloud Computing Markets

Due to the large variety in computing resources and, consequently, the large number of different types of Service Level Agreements (SLAs), any market for computing resources faces the potential problem of a low market liquidity. To counteract this problem, offering a set of standardized computing resources is appropriate. Each of these standardized computing resources is defined through an SLA template. An SLA template defines the structure of an SLA, the attributes, the names of the attributes, and the attribute values. Since these SLA templates are currently static, they cannot reflect changes in users' needs. To address this shortcoming, we present the novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings by allowing Cloud users to define mappings between public SLA templates, which are available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates adapt to the demand of users, we also analyze the benefits and costs of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, within this paper, we investigate the cost depending on the use of different public SLA template adaptation methods. The simulation results show that the use of heuristics within adaptation methods helps balancing the cost and benefit of the SLA mapping approach.Cloud economics, computing markets, market liquidity, simulation.

Towards Autonomic Market Management in Cloud Computing Infrastructures

Cloud computing markets face challenges, such as a large variety of different resource types in the market. A large variety of resource types results in a low number of matches of ask and bids. Consequently, the market has a low liquidity, which is economically inefficient and can lead to market failure. To counteract this problem, SLA templates (i.e., templates for electronic contracts) have been introduced. However, until now, SLA templates were static, not able to reflect changes in users’ requirements. In this paper, we apply the adaptive SLA mapping approach for deriving public SLA templates from private SLA templates of users. To achieve the adaptation of SLA templates, we combine clustering algorithms with adaptation methods. The result is a set of new public SLA templates, which reflect the market situation more accurately. This way, we enable marketplaces to automatically adapt to observed changes of market conditions. For the simulation-based evaluation of our approach, we formalize a utility and cost model, calculate the overall net utility, and assess the scalability of the approach. Our results show that the use of clustering algorithms can significantly improve the performance of the adaptive SLA mapping approach.Service Level Agreement, SLA management, electronic markets, autonomic computing.

A survey of cloud monitoring tools: Taxonomy, capabilities and objectives.

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.N/

Achieving flexible SLA and resource management in clouds

One of the key factors driving Cloud computing is flexible and on-demand resource provisioning in a pay-as-you-go manner. This resource provisioning is based on Service Level Agreements (SLAs) negotiated and signed between customers and providers. Efficient management of SLAs and Cloud resources to reduce cost, achieve high utilization, and generate profit is challenging due to the large-scale nature of Cloud environments and complex resource provisioning processes. In order to advance the adoption of this technology, it is necessary to identify and address the issues preventing proper resource and SLA management. The authors purport that monitoring is the first step towards successful management strategies. Thus, this chapter identifies the SLA management and monitoring challenges in Clouds and federated Cloud environments, and proposes a novel resource monitoring architecture as a basis for resource management in Clouds. It presents the design and implementation of this architecture and presents the evaluation of the architecture using heterogeneous application workloads