Semantic validation of affinity constrained service function chain requests

Network Function Virtualization (NFV) has been proposed as a paradigm to increase the cost-efficiency, flexibility and innovation in network service provisioning. By leveraging IT virtualization techniques in combination with programmable networks, NFV is able to decouple network functionality from the physical devices on which they are deployed. This opens up new business opportunities for both Infrastructure Providers (InPs) as well as Service Providers (SPs), where the SP can request to deploy a chain of Virtual Network Functions (VNFs) on top of which its service can run. However, current NFV approaches lack the possibility for SPs to define location requirements and constraints on the mapping of virtual functions and paths onto physical hosts and links. Nevertheless, many scenarios can be envisioned in which the SP would like to attach placement constraints for efficiency, resilience, legislative, privacy and economic reasons. Therefore, we propose a set of affinity and anti-affinity constraints, which can be used by SPs to define such placement restrictions. This newfound ability to add constraints to Service Function Chain (SFC) requests also introduces an additional risk that SFCs with conflicting constraints are requested or automatically generated. Therefore, a framework is proposed that allows the InP to check the validity of a set of constraints and provide feedback to the SP. To achieve this, the SFC request and relevant information on the physical topology are modeled as an ontology of which the consistency can be checked using a semantic reasoner. Enabling semantic validation of SFC requests, eliminates inconsistent SFCs requests from being transferred to the embedding algorithm.Peer Reviewe

Optimal Orchestration of Virtual Network Functions

-The emergence of Network Functions Virtualization (NFV) is bringing a set of novel algorithmic challenges in the operation of communication networks. NFV introduces volatility in the management of network functions, which can be dynamically orchestrated, i.e., placed, resized, etc. Virtual Network Functions (VNFs) can belong to VNF chains, where nodes in a chain can serve multiple demands coming from the network edges. In this paper, we formally define the VNF placement and routing (VNF-PR) problem, proposing a versatile linear programming formulation that is able to accommodate specific features and constraints of NFV infrastructures, and that is substantially different from existing virtual network embedding formulations in the state of the art. We also design a math-heuristic able to scale with multiple objectives and large instances. By extensive simulations, we draw conclusions on the trade-off achievable between classical traffic engineering (TE) and NFV infrastructure efficiency goals, evaluating both Internet access and Virtual Private Network (VPN) demands. We do also quantitatively compare the performance of our VNF-PR heuristic with the classical Virtual Network Embedding (VNE) approach proposed for NFV orchestration, showing the computational differences, and how our approach can provide a more stable and closer-to-optimum solution

The United States Marine Corps Data Collaboration Requirements: Retrieving and Integrating Data From Multiple Databases

The goal of this research is to develop an information sharing and database integration model and suggest a framework to fully satisfy the United States Marine Corps collaboration requirements as well as its information sharing and database integration needs. This research is exploratory; it focuses on only one initiative: the IT-21 initiative. The IT-21 initiative dictates The Technology for the United States Navy and Marine Corps, 2000-2035: Becoming a 21st Century Force. The IT-21 initiative states that Navy and Marine Corps information infrastructure will be based largely on commercial systems and services, and the Department of the Navy must ensure that these systems are seamlessly integrated and that information transported over the infrastructure is protected and secure. The Delphi Technique, a qualitative method approach, was used to develop a Holistic Model and to suggest a framework for information sharing and database integration. Data was primarily collected from mid-level to senior information officers, with a focus on Chief Information Officers. In addition, an extensive literature review was conducted to gain insight about known similarities and differences in Strategic Information Management, information sharing strategies, and database integration strategies. It is hoped that the Armed Forces and the Department of Defense will benefit from future development of the information sharing and database integration Holistic Model

Automated Injection of Curated Knowledge Into Real-Time Clinical Systems: CDS Architecture for the 21st Century

abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs. This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKA’s Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards. Towards the goal of interoperable human processes, ARTAKA’s treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment. Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-machine Translations

Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of choosing between different sets of results, and more of a presentation of a single answer, limiting both the availability of, and exposure to, alternate sources of information. Thus, it is essential to understand how that information comes to be structured and how deterministic systems like search based AI come to understand the indeterminate worlds they are tasked with interrogating. The semantic web, one of the technologies underpinning these systems, creates machine-readable data from the existing web of text and formalizes those machine-readable understandings in ontologies. This study investigates the ways that those semantic assemblages structure, and thus define, the world. In accordance with assemblage theory, it is necessary to study the interactions between the components that make up such data assemblages. As yet, the social sciences have been slow to systematically investigate data assemblages, the semantic web, and the components of these important socio-technical systems. This study investigates one major ontology, Schema.org. It uses netnographic methods to study the construction and use of Schema.org to determine how ontological states are declared and how human-machine translations occur in those development and use processes. This study has two main findings that bear on the relevant literature. First, I find that development and use of the ontology is a product of negotiations with technical standards such that ontologists and users must work around, with, and through the affordances and constraints of standards. Second, these groups adopt a pragmatic and generalizable approach to data modeling and semantic markup that determines ontological context in local and global ways. This first finding is significant in that past work has largely focused on how people work around standards’ limitations, whereas this shows that practitioners also strategically engage with standards to achieve their aims. Second, the particular approach that these groups use in translating human knowledge to machines, differs from the formalized and positivistic approaches described in past work. At a larger level, this study fills a lacuna in the collective understanding of how data assemblages are constructed and operate