Currently, the data to be explored and exploited by computing systems increases at an exponential rate. The massive amount of data or so-called “Big Data” put pressure on existing technologies for providing scalable, fast and efficient support. Recent applications and the current user support from multi-domain computing, assisted in migrating from data-centric to knowledge-centric computing. However, it remains a challenge to optimally store and place or migrate such huge data sets across data centers (DCs). In particular, due to the frequent change of application and DC behaviour (i.e., resources or latencies), data access or usage patterns need to be analyzed as well. Primarily, the main objective is to find a better data storage location that improves the overall data placement cost as well as the application performance (such as throughput). In this survey paper, we are providing a state of the art overview of Cloud-centric Big Data placement together with the data storage methodologies. It is an attempt to highlight the actual correlation between these two in terms of better supporting Big Data management. Our focus is on management aspects which are seen under the prism of non-functional properties. In the end, the readers can appreciate the deep analysis of respective technologies related to the management of Big Data and be guided towards their selection in the context of satisfying their non-functional application requirements. Furthermore, challenges are supplied highlighting the current gaps in Big Data management marking down the way it needs to evolve in the near future.

Cross-organisation data sharing is challenging because all the involved organisations must agree on ’how’ and ’why’ the data is processed. Due to a lack of transparency, the organisations need to trust that others comply with the agreements and regulations. We propose to exploit blockchain and smart contracts technologies to define an Attribute-Based Access Control System for cross-organisation medical records sharing, coined SmartAccess. SmartAccess offers joint agreement over access policies and dynamic access control besides blockchain transparency and auditability. We leverage the Attribute-Based Access Control model to implement smart contracts.We deploy and test them on a private and permissioned blockchain, transforming the access control process into a distributed smart contract execution. This paper proposes the SmartAccess system and its application in two healthcare use cases. We introduce the threat model and perform a security analysis of the system. To demonstrate the feasibility of our proposal, we implement a proof-of-concept of the smart contracts, written in Solidity language, with a size-efficient policy representation, and analyse the complexity and scalability of the contracts’ functions. Furthermore, we present performance results, measuring the latency and throughput of the transactions to execute the access control functions with different blockchain network consensus setups. We also compare the performance of the SmartAccess system against two open-source Solidity implementations of smart contract-based access control, Role-based Access Control and Access Control List. Finally, we discuss the strengths and drawbacks of our proposal. SmartAccess requires the overhead of a decentralised system, but the trade-off is transparency, regulation compliance and auditability for complex cross-organisation data sharing.

Enterprises increasingly recognize the compelling economic and operational benefits from virtualizing and pooling IT resources in the cloud. Nevertheless, the significant and valuable transformation of organizations that adopt cloud computing is accompanied by a number of security threats that should be considered. In this paper, we outline significant security challenges presented when migrating to a cloud environment and propose PaaSword – a novel holistic framework that aspires to alleviate these challenges. Specifically, the proposed framework involves a context-aware security model, the necessary policies enforcement mechanism along with a physical distribution, encryption and query middleware.

Over the last few years, the vast increase of cloud service offerings that are available from heterogeneous cloud vendors, has made the evaluation and selection of desired cloud services, a cumbersome task for service consumers. In that respect, there is an increasing need for user guidance and intermediation during the service selection process but also during the cloud service consumption that should always refer to the best possible choice based on user preferences. In this paper, we discuss the Preference-based cLoud Service Recommender (PuLSaR) that uses a holistic multi-criteria decision making (MCDM) approach for offering optimisation as a brokerage service. The specification and implementation details of this proposed software mechanism are thoroughly discussed while the background method used is summarised. Both method and brokerage service allow for the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics and dealing with their fuzziness. We cope with the fuzziness of imprecise metrics in the sense that this approach deals with linguistically expressed preferences and cloud service characteristics that lack a fixed or precise value and entail a level of vagueness which can only be captured using the Zadeh’s Fuzzy Set Theory. Furthermore, this paper reports on a number of experiments that were conducted in order to measure PuLSaR’s performance and scalability.