Smart Ontology Framework for Multi-Tenant Cloud Architecture

The exponential growth of data complexity in an era marked by the rapid expansion of the computer environment has led to an increase in the demand for scalable and effective systems. The crucial stage of data management, which acts as a vital conduit for accelerating the processing of enormous amounts of data, is at the centre of this paradigm. Scientific workflows must be coordinated in order to orchestrate the management of large datasets within this complex ecosystem. These workflows differ from generic workflows in that they involve a complex interplay of scheduling, algorithms, data flow, processes, operational protocols, and a focused attention on data-intensive systems. Software as a Service's (SaaS) distinctive feature of multi-tenancy is inextricably related to the growth of the industry. In this complex fabric, the investigation of scientific processes reveals a mutually beneficial relationship with the multi-tenant cloud orchestration environment, revealing a realm that goes beyond simple control and data propagation. It opens a fresh path for system development and makes service delivery's previously hidden facets visible. This study pioneers an exploration into a thorough framework for scientific operations within the context of multi-tenant cloud orchestration. Semantics-based workflows, which leverage semantics to help users manage the complexities of data orchestration, form the basis of this paradigm. In addition, policy-based processes provide another level of intricacy, giving users a flexible way to manoeuvre the complex environment of multi-tenancy, orchestration, and service identification. The study focuses on the fundamentals of orchestrating scientific workflows in a multi-tenant cloud environment, where the creative, scalable, and effective composition results from the harmonious integration of data and semantics under the guidance of rules

Orchestrating Intelligent Network Operations in Programmable Networks

Peer reviewe

Orchestration in the Cloud-to-Things Compute Continuum: Taxonomy, Survey and Future Directions

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems has been increasing rapidly. These IoT use cases often require simultaneous access to geographically distributed arrays of sensors, and heterogeneous remote, local as well as multi-cloud computational resources. This gives birth to the extended Cloud-to-Things computing paradigm. The emergence of this new paradigm raised the quintessential need to extend the orchestration requirements i.e., the automated deployment and run-time management) of applications from the centralised cloud-only environment to the entire spectrum of resources in the Cloud-to-Things continuum. In order to cope with this requirement, in the last few years, there has been a lot of attention to the development of orchestration systems in both industry and academic environments. This paper is an attempt to gather the research conducted in the orchestration for the Cloud-to-Things continuum landscape and to propose a detailed taxonomy, which is then used to critically review the landscape of existing research work. We finally discuss the key challenges that require further attention and also present a conceptual framework based on the conducted analysis.Comment: Journal of Cloud Computing Pages: 2

Dynamic collaboration and secure access of services in multi-cloud environments

The cloud computing services have gained popularity in both public and enterprise domains and they process a large amount of user data with varying privacy levels. The increasing demand for cloud services including storage and computation requires new functional elements and provisioning schemes to meet user requirements. Multi-clouds can optimise the user requirements by allowing them to choose best services from a large number of services offered by various cloud providers as they are massively scalable, can be dynamically configured, and delivered on demand with large-scale infrastructure resources. A major concern related to multi-cloud adoption is the lack of models for them and their associated security issues which become more unpredictable in a multi-cloud environment. Moreover, in order to trust the services in a foreign cloud users depend on their assurances given by the cloud provider but cloud providers give very limited evidence or accountability to users which offers them the ability to hide some behaviour of the service. In this thesis, we propose a model for multi-cloud collaboration that can securely establish dynamic collaboration between heterogeneous clouds using the cloud on-demand model in a secure way. Initially, threat modelling for cloud services has been done that leads to the identification of various threats to service interfaces along with the possible attackers and the mechanisms to exploit those threats. Based on these threats the cloud provider can apply suitable mechanisms to protect services and user data from these threats. In the next phase, we present a lightweight and novel authentication mechanism which provides a single sign-on (SSO) to users for authentication at runtime between multi-clouds before granting them service access and it is formally verified. Next, we provide a service scheduling mechanism to select the best services from multiple cloud providers that closely match user quality of service requirements (QoS). The scheduling mechanism achieves high accuracy by providing distance correlation weighting mechanism among a large number of services QoS parameters. In the next stage, novel service level agreement (SLA) management mechanisms are proposed to ensure secure service execution in the foreign cloud. The usage of SLA mechanisms ensures that user QoS parameters including the functional (CPU, RAM, memory etc.) and non-functional requirements (bandwidth, latency, availability, reliability etc.) of users for a particular service are negotiated before secure collaboration between multi-clouds is setup. The multi-cloud handling user requests will be responsible to enforce mechanisms that fulfil the QoS requirements agreed in the SLA. While the monitoring phase in SLA involves monitoring the service execution in the foreign cloud to check its compliance with the SLA and report it back to the user. Finally, we present the use cases of applying the proposed model in scenarios such as Internet of Things (IoT) and E-Healthcare in multi-clouds. Moreover, the designed protocols are empirically implemented on two different clouds including OpenStack and Amazon AWS. Experiments indicate that the proposed model is scalable, authentication protocols result only in a limited overhead compared to standard authentication protocols, service scheduling achieves high efficiency and any SLA violations by a cloud provider can be recorded and reported back to the user.My research for first 3 years of PhD was funded by the College of Engineering and Technology

A Design Theory for Digital Platforms Supporting Online Communities: A Multiple Case Study

This research proposes and validates a design theory for digital platforms that support online communities (DPsOC). It addresses ways in which digital platforms can effectively support social interactions in online communities. Drawing upon prior literature on IS design theory, online communities, and platforms, we derive an initial set of propositions for designing effective DPsOC. Our overarching proposition is that three components of digital platform architecture (core, interface, and complements) should collectively support the mix of the three distinct types of social interaction structures of online community (information sharing, collaboration, and collective action). We validate the initial propositions and generate additional insights by conducting an in-depth analysis of an European digital platform for elderly care assistance. We further validate the propositions by analyzing three widely used digital platforms, including Twitter, Wikipedia, and Liquidfeedback, and we derive additional propositions and insights that can guide DPsOC design. We discuss the implications of this research for research and practice

Big Ideas paper: Policy-driven middleware for a legally-compliant Internet of Things.

Internet of Things (IoT) applications, systems and services are subject to law. We argue that for the IoT to develop lawfully, there must be technical mechanisms that allow the enforcement of speci ed policy, such that systems align with legal realities. The audit of policy enforcement must assist the apportionment of liability, demonstrate compliance with regulation, and indicate whether policy correctly captures le- gal responsibilities. As both systems and obligations evolve dynamically, this cycle must be continuously maintained. This poses a huge challenge given the global scale of the IoT vision. The IoT entails dynamically creating new ser- vices through managed and exible data exchange . Data management is complex in this dynamic environment, given the need to both control and share information, often across federated domains of administration. We see middleware playing a key role in managing the IoT. Our vision is for a middleware-enforced, uni ed policy model that applies end-to-end, throughout the IoT. This is because policy cannot be bound to things, applications, or administrative domains, since functionality is the result of composition, with dynamically formed chains of data ows. We have investigated the use of Information Flow Control (IFC) to manage and audit data ows in cloud computing; a domain where trust can be well-founded, regulations are more mature and associated responsibilities clearer. We feel that IFC has great potential in the broader IoT context. However, the sheer scale and the dynamic, federated nature of the IoT pose a number of signi cant research challenges

Zero Trust for Cyber Resilience

The increased connectivity and potential insider threats make traditional network defense vulnerable. Instead of assuming that everything behind the security perimeter is safe, the zero-trust security model verifies every incoming request before granting access. This chapter draws attention to the cyber resilience within the zero-trust model. We introduce the evolution from traditional perimeter-based security to zero trust and discuss their difference. Two key elements of the zero-trust engine are trust evaluation (TE) and policy engine (PE). We introduce the design of the two components and discuss how their interplay would contribute to cyber resilience. Dynamic game theory and learning are applied as quantitative approaches to achieve automated zero-trust cyber resilience. Several case studies and implementations are introduced to illustrate the benefits of such a security model

Governance of Autonomous Agents on the Web: Challenges and Opportunities

International audienceThe study of autonomous agents has a long tradition in the Multiagent System and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an extension of the Internet of Things (IoT) with metadata expressed in Web standards, and its community provide further motivation for pushing the autonomous agents research agenda forward. Although representing and reasoning about norms, policies and preferences is crucial to ensuring that autonomous agents act in a manner that satisfies stakeholder requirements, normative concepts, policies and preferences have yet to be considered as first-class abstractions in Web-based multiagent systems. Towards this end, this paper motivates the need for alignment and joint research across the Multiagent Systems, Semantic Web, and WoT communities, introduces a conceptual framework for governance of autonomous agents on the Web, and identifies several research challenges and opportunities