Deep learning, has delivered a variety of practical uses in the past decade. It has revolutionized customer experience and machine translation. It has made language recognition, autonomous vehicles and computer vision a reality. A multitude of other AI applications are common now. With Deep Learning we gain insights about hidden correlations. We extract features and distinguish categories. But we lack transparency of reasoning behind these conclusions. Most importantly, there is the absence of common sense. Deep learning models might be the best at perceiving patterns. Yet they cannot comprehend what the patterns mean. And they lack the ability to model their behaviors and reason about them.We present a new approach to augment Deep Learning using model based Deep Reasoning and its application to address fraud detection using financial statements. Recent theoretical models of computing structures with cognizing agents go beyond neural networks to provide models of observations, abstractions and generalizations from experience and create time dependent evolution and history to provide reasoning and predictive. We use Knowledge Structures defined therein to represent relevant domain knowledge. In this case, in a company's financial statements. We analyze their history to detect potential fraud based on specific rules and observations. We use information from governance and compliance rules and experience of past violations. We analyze SEC 10-K statements using Deep Learning and model based Deep Reasoning. We use the Knowledge Structures to identify red flags and anomalies.

This track has made signicant contribution to advance the current state of the art in enterprise distributed application management across datacenters, and clouds public or private. A new computing model proposing extensions to the current von Neumann implementation of the Turing machine was contributed by the efforts of several participants in this conference since 2009. Keeping with this tradition, this year a new paper demonstrates theory and practice that pushes the Church-Turing thesis boundaries and demonstrates a novel low-latency and high-performance edge computing solution. In addition, there are nine full papers describing advances in current distributed and cloud computing practices dealing with quality of service, business intelligence, cloud security, Internet of Things, cloud performance and economics.

Advances in our understanding of the nature of cognition in its myriad forms (Embodied, Embedded, Extended, and Enactive) displayed in all living beings (cellular organisms, animals, plants, and humans) and new theories of information, info-computation and knowledge are throwing light on how we should build software systems in the digital universe which mimic and interact with intelligent, sentient and resilient beings in the physical universe. Recent attempts to infuse cognition into computing systems to push the boundaries of Church-Turing thesis have led to new computing models that mimic biological systems in encoding knowledge structures using both algorithms executed in stored program control machines and neural networks. This paper presents a new model and implements an application as hierarchical named network composed of microservices to create a managed process workflow by enabling dynamic configuration and reconfiguration of the microservice network. We demonstrate the resiliency, efficiency and scaling of the named microservice network using a novel edge cloud platform by Platina Systems. The platform eliminates the need for Virtual Machine overlay and provides high performance and low-latency with L3 based 100 GbE network and SSD support with RDMA and NVMeoE. The hierarchical named microservice network using Kubernetes provisioning stack provides all the cloud features such as elasticity, autoscaling, self-repair and live-migration without reboot. The model is derived from a recent theoretical framework for unification of different models of computation using “Structural Machines.” They are shown to simulate Turing machines, inductive Turing machines and also are proved to be more efficient than Turing machines. The structural machine framework with a hierarchy of controllers managing the named service connections provides dynamic reconfiguration of the service network from browsers to database to address rapid fluctuations in the demand for or the availability of resources without having to reconfigure IP address base networks.

Cloud Computing is evolving towards big infrastructures with next generation hardware and services embedding business service intelligence to create complex distributed workflow execution services. Servide providers want to assure service delivery on a massive scale with global interoperability. The scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. In this context, the problem of vendor lock-in is still a very discussed issue and companies are experimenting multi-cloud and various cloud agnostic solutions. In this 2018 edition of CDCGM there are 6 papers describing solutions to improve the current cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures.

This track started in 2009 with opening remarks from the Chair observing that the computing cloud evolution depends on research efforts from the infrastructure providers creating next generation hardware that is service friendly, service developers that embed business service intelligence in the computing infrastructure to create distributed business workflow execution services and service providers who assure service delivery on a massive scale with global interoperability. The state of the art architecture and evolution of the cloud at that time was already increasing datacenter complexity by piling up new layers of management over the many layers that already exist. Since then, the scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. There are many calls to go cloud native and architect applications using the many services provided by the cloud providers such as Amazon Web Services. On the other hand, there are also calls for avoiding vendor lock-in by going multi-cloud and becoming cloud agnostic. In this conference there is a new paper that proposes cloud agnostic approach with globally interoperable cloud network using private or public network while reducing the complexity of Virtual machine image motion across clouds. In addition, there are 7 papers describing advances in current distributed and cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures.

This paper describes the extension of the work started in the first Cloud Computing session in WETICE 2009. A new computing paradigm using distributed intelligent managed elements (DIME) and DIME network architecture introduced in WETICE2010 is used to demonstrate globally interoperable public and private cloud network deploying cloud agnostic workloads. The workloads are cognitive and capable of self-provisioning, self-healing, self-monitoring and self-controlling to adjust their structure and maintain desired quality of service. The agent architecture brings work-load resiliency and tolerance to fluctuations both in demand and available resource pools at scale. A three tier marketing application consisting of an author module, publisher module and a dispatcher module is used to demonstrate workload deployment in an interoperable cloud network using the public Internet. Cloud agnostic inter-cloud and intra-cloud auto-scaling, auto-failover and live migration are demonstrated. This approach goes against the current trend to make workloads cloud-native and provides workload management on any infrastructure be it a bare-metal server, a virtual machine or a container.

Agents and agent systems are becoming more and more important in the development of a variety of fields such as ubiquitous computing, ambient intelligence, autonomous computing, intelligent systems and intelligent robotics. In this paper, we analyze how agent technology is presented in mathematical models of computation demonstrating how these models are used in the novel distributed intelligent managed element (DIME) network architecture (DNA), which extends the conventional computational model of information processing networks, allowing improvement of the efficiency and resiliency of computational processes.

This track has made significant contribution to advance the current state of the art in enterprise distributed application management across data centers, and clouds public or private. The scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. A new computing model proposing extensions to the current von Neumann implementation of the Turing machine was contributed by the efforts of participating in this conference since 2009. The result is a practical demonstration of these concepts, showing infrastructure agnostic auto-fail over, auto-scaling and live-migration of even state-sensitive distributed applications. By eliminating virtual image motion which is the current state of the art, this approach improves efficiency and reduces complexity and tool fatigue prevalent in todays enterprises. In addition, a review of the super recursive algorithms and inductive Turing machines in this track provides the theoretical foundation for new computing. In addition, there are five full papers describing advances in current distributed and cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures. One short paper discusses a new approach for resource allocation in distributed systems. On the eve of the 25th anniversary of WETICE, this track attests to its success where the work started here has contributed to both theoretical and practical application going from ideation to application within a span of 6 years.

This paper describes the result of the work started in the first Cloud Computing session in WETICE 2009. During the last seven years, collaboration from participants in WETICE has resulted in a new computation model and a commercial product that advances the state of the art in infrastructure agnostic distributed application life-cycle quality of service management. In WETICE 2016, celebrating its 25th anniversary, we demonstrate the resulting new technology with extensions to the Turing machine models to include manageability of distributed applications in the face of wild fluctuations in available computing resources or fluctuations introduced by the interactions between the computation and its environment or both.

This track started with the first Cloud Computing session in WETICE2009 with the observation that the cloud computing evolution depends on research efforts from the infrastructure providers creating next generation hardware that is service friendly, service developers that embed business service intelligence in the network to create distributed business workflow execution, assure service delivery on a massive scale with global interoperability while dealing with non-functional requirements such as security, availability, performance, compliance, cost and fluctuations both in resources and workloads. It was pointed out that the architecture and evolution of the cloud is increasing data enter complexity by piling up new layers of management over the many layers that already exist. Current session proves the epigram by Jean-Baptiste (1849) "plus ça change, plus c'est la mêeme chose." Literally "The more it changes, the more it's the same thing". In this conference, one paper presents the result of the discussions started in these sessions in 2009 that led to a policy based dynamic workflow orchestration independent of the infrastructure orchestration which eliminates the need for moving Virtual Machine images and interfaces to myriad infrastructure management systems at runtime. The architecture is derived from the well-understood and time-tested distributed systems such as cellular organisms, human organizational structures and telecommunication networks. In addition, eight full papers and three short papers continue to make progress on current state of the art. Based on the papers presented in these sessions over the last six years, we boldly predict that we are on the verge of a synthesis of the thesis of current state of the art and the anti-thesis of increasing complexity to address scaling and fluctuations in distributed systems.

Distributed systems are dynamic systems where software and hardware together deliver information processing services to allow modelling, interaction, reasoning, analysis and control of the external environment. The intent of the distributed computation is to execute computational workflows using computing resources. The software contains the algorithms that specify the tasks while the hardware provides the required resources to execute the algorithms. The initial structure is defined by the association of software with hardware and the dynamic structure is defined by their temporal evolution. The meta-knowledge of the intent of the algorithm, the association of specific algorithm to a specific device, their temporal evolution and exception handling when the computation deviates from the intent is outside the software and hardware design and is expressed in non-functional requirements. In this paper, we describe an architecture to capture the meta-knowledge in meta-containers and enforce the intent of the computation while the computation is in progress.

Cloud computing deals with accessing services and resources in distributed environments needed to perform functions with dynamically changing needs. The cloud provides a virtualization of resources that maintains and manages itself. The DIME Network Architecture was introduced as a new approach to handle dynamic aspects of cloud computing, i.e., self-repairs, auto-scaling, live-migration, end-to-end service transaction security, and so on. It was hypothesized that for such self-reference features, conventional Turing machines fall short. In this paper, we investigate this claim in more depth.

Current state-of-the-art infrastructure-centric deployment and management of distributed web-scale applications cannot scale and meet the demands of changing workloads and increasing demands on application availability, mobility and security. The DIME network architecture has matured during the last four years to offer an alternative to provide a post-Hyper visor, Hyper-Cloud network of applications spanning across physical or virtual servers with self-management properties. The first paper presented in this conference, addresses a new computing architecture. A second paper describes an implementation showing its usefulness in addressing fault, configuration, accounting, performance, as well security of service transactions spanning across data enters and multiple clouds with or without virtualization. In addition, infrastructure optimization strategies for Cloud computing continue to provide a fertile ground for research and five papers address these topics. Two papers address scheduling and optimization issues in Grid computing while three more papers address various aspects of content management, distributed and parallel computing. The remaining papers embrace interesting topics related to applications of Cloud Computing in different areas of scientific Cloud computing, collaborative platforms, and big data analysis.

The advent of virtualization technologies and cloud computing has improved application provisioning speed, resource utilization, fault-management, availability using auto-failover and performance optimization using auto-scaling in distributed computing environments. However, heterogeneous virtualization technologies offered by different service providers with disparate infrastructure and their orchestration and management systems have also increased the complexity of managing distributed applications and vendor lock-in. In this paper we utilize new computing, management and programming models introduced using the DIME network architecture to provide end to end service visibility and control across distributed physical or virtual infrastructure. Resulting decoupling of application and service transaction management from myriad distributed infrastructure management systems at run-time enables policy based, secure, service mobility across physical servers or virtual machines deployed in data enters or public clouds. Using the new architecture we have implemented service self-repair, auto-scaling, live-migration and end-to-end service transaction security independent of server and network security mechanisms.

By introducing signaling and self-management in a Turing node and a signaling network as an overlay over the computing network, the current von-Neumann computing model is evolved to bring the architectural resiliency of cellular organisms to computing infrastructure. The DIME computing model introduces the genetic transactions of replication, repair, recombination and reconfiguration to program self-resiliency in distributed computing systems executing a managed workflow. The injection of parallelism and network based composition of "Self" identity are the first steps in introducing the elements of homeostasis and self-management in the computing infrastructure. DIMEs inject the architectural resiliency of cellular organisms to create a new class of distributed autonomic computing systems using managed Turing machine networks.

Cloud based services, by their nature, are distributed and traditional operation and management processes that often exert centralized control are not suited for cloud services operation and management. This paper introduces a Policy-based Event-driven Service-oriented Architecture (PESA) that enables the manageability of these loosely coupled services distributed across multiple public or private clouds or a hybrid cloud. PESA allows the implementation of policy driven management of service availability, performance, security and risk management. Using the concept of logical and virtual partitioning of the business service fabric into sub-fabrics - islands of services that may span company, geographical, and technological boundaries, public and private clouds, and corporate data centers, we describe a conceptual management architecture for policy enforcement. An example describes service availability and performance assurance in a business process implementation using a set of loosely coupled service components in a virtual cloud.

The author argues that while object-oriented programming provides a foundation for component-based software construction, the quality of the objects' interfaces (at both system level and component level) is the key to making reuse an effective practice. It is necessary to cultivate an infrastructure that encourages quality interface design and large-scale reuse in order to make object-oriented technologies work for improved quality and productivity. The author proposes the use of standardized objects and services for achieving such an infrastructure in an object-oriented development environment. A business-related object-oriented modeling (BROOM) tool prototype that incorporates the concept of standardized objects and services is described.>

Identifies the confluence of several new technologies that will allow major improvements in the software development process. Future research in this area will encompass advances in database technology, programming languages, expert systems, and distributed workstations. Researchers are working on a new data model that will combine object-oriented language features, database features, inferencing, and distribution. This will allow new software environments that are even more efficient because of the seamless integration of these technologies. This will expedite future software prototyping, production, and maintenance.>