Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi

QoS-aware and semantic-based service coordination for multi-Cloud environments

© 2013 Dr. Amir Vahid DastjerdiThe advantages of Cloud computing, such as cost effectiveness and ease of management, encourage companies to adapt its services. However, In a Multi-Cloud environment, the wide range of Cloud services and user specific requirements make it difficult to select the best composition of services. An automated approach is required to deal with all phases of service coordination including discovery, negotiation, selection, composition, and monitoring. To simplify the process of Cloud migration, this thesis proposes an effective architecture to provide automated QoS-aware deployment of virtual appliances on Cloud service providers. The architecture takes advantage of ontology-based discovery to semantically match user requirements to Cloud services. Then, it applies a set of negotiation, selection, and optimization strategies to pick up the best available services from the list of discovered services. Finally, this thesis shows how monitoring services have to be described, deployed (discovered and ranked), and executed to enforce accurate penalties. The key contributions of this thesis are: 1. An ontology-based Cloud service discovery is proposed that works based on modelling virtual units into Semantic Web services. This helps users to deploy their appliances on the fittest providers when providers and users are not using the same notation to describe their services and requirements. 2. A scalable methodology to create an aggregated repository of services in Web Service Modeling Ontology (WSMO) from service advertisements available in XML. 3. A negotiation strategy that acquires user preferences and provider’s resource utilization status and utilizes time-dependent tactic along with statistical methods to maximize the profit of Cloud providers while adhering to deadline constraints of users and verifying reliability of providers’ offers. The proposed negotiation strategy is tested to show how our approach helps Cloud providers to increase their profits. 4. A QoS criteria model for selection of virtual appliances and units in Cloud computing. In addition, two different selection approaches, genetic-based and Forward-checking-based backtracking (FCBB), are proposed to help users deploying net-work of appliances on Clouds based on their preferences. 5. A ranking system for Cloud service composition that let users express their preferences conveniently using high-level linguistic terms. The system utilizes evolutionary multi-objective optimization, and a fuzzy inference system to precisely capture the preferences for the ranking purpose. 6. An approach to help non-expert users with limited or no knowledge on legal and virtual appliance image format compatibility to deploy their services flawlessly. For this purpose, Cloud services are enriched with experts knowledge (from lawyers, software engineers, system administrators, etc). The knowledgebase then is used in a scalable algorithm for reasoning that identifies whether a set of Cloud service consisting of virtual appliance and units are compatible or not. 7. A semantic SLA template that can be used as a goal for discovery of necessary monitoring services. In addition, SLA dependencies are modeled using WSMO to build a knowledgebase that is exploited to eliminate the effects of SLA failure cascading on violation detection

Internet of things: principles and paradigms

xxiii, 354 p. ; 25 cm

Big data: principles and paradigms

xxv, 468 p. : ill. ; 23 cm