Artificial intelligence empowered virtual network function deployment and service function chaining for next-generation networks

The entire Internet of Things (IoT) ecosystem is directing towards a high volume of diverse applications. From smart healthcare to smart cities, every ubiquitous digital sector provisions automation for an immersive experience. Augmented/Virtual reality, remote surgery, and autonomous driving expect high data rates and ultra-low latency. The Network Function Virtualization (NFV) based IoT infrastructure of decoupling software services from proprietary devices has been extremely popular due to cutting back significant deployment and maintenance expenditure in the telecommunication industry. Another substantially highlighted technological trend for delaysensitive IoT applications has emerged as multi-access edge computing (MEC). MEC brings NFV to the network edge (in closer proximity to users) for faster computation. Among the massive pool of IoT services in NFV context, the urgency for efficient edge service orchestration is constantly growing. The emerging challenges are addressed as collaborative optimization of resource utilities and ensuring Quality-ofService (QoS) with prompt orchestration in dynamic, congested, and resource-hungry IoT networks. Traditional mathematical programming models are NP-hard, hence inappropriate for time-sensitive IoT environments. In this thesis, we promote the need to go beyond the realms and leverage artificial intelligence (AI) based decision-makers for “smart” service management. We offer different methods of integrating supervised and reinforcement learning techniques to support future-generation wireless network optimization problems. Due to the combinatorial explosion of some service orchestration problems, supervised learning is more superior to reinforcement learning performance-wise. Unfortunately, open access and standardized datasets for this research area are still in their infancy. Thus, we utilize the optimal results retrieved by Integer Linear Programming (ILP) for building labeled datasets to train supervised models (e.g., artificial neural networks, convolutional neural networks). Furthermore, we find that ensemble models are better than complex single networks for control layer intelligent service orchestration. Contrarily, we employ Deep Q-learning (DQL) for heavily constrained service function chaining optimization. We carefully address key performance indicators (e.g., optimality gap, service time, relocation and communication costs, resource utilization, scalability intelligence) to evaluate the viability of prospective orchestration schemes. We envision that AI-enabled network management can be regarded as a pioneering tread to scale down massive IoT resource fabrication costs, upgrade profit margin for providers, and sustain QoS mutuall

"Marijuana Moms" : the collective work of negotiating individual and group identity in the age of cannabis legalization

This research is the result of a qualitative study that explored the ways in which marijuana using mothers come to identify as such and how they structure their relationships and parenting as a result. The experiences of 57 self-identified marijuana using mothers (aged 20-48 years-old) from across the United States participated in semi-structured interviews and shared their everyday experiences with both marijuana use and motherhood. Participants were all mothers with children between 3 months and 19 years at the time of the interviews. A thematic narrative analysis uncovered common experiences among these women in constructing both individual and group identity: Participants varied in how each of these themes identified were reflected in their lives, depending upon each participant's interpretation of her local social context. Both motherhood and self-identifying as a marijuana user were valuable and meaningful parts of their identity.Includes bibliographical reference

A Japanese fishing joint venture: worker experience and national development in the Solomon Islands

Tuna fisheries, Joint ventures, Fishery development, Sociological aspects, Solomon Islands, Japan,

Organizational Culture in Wisconsin Large Law Firms

Culture can be defined as the collective programming of the mind which distinguishes one group or category of people from another. Organizational culture is an idea in the field of organizational studies and management which describes the psychology, attitudes, experiences, beliefs and values (personal and cultural values) of an organization. There are many studies on Organizational Culture applied to corporations. There are very few studies of Organizational Culture applied to law firms. This is a study of Organizational Culture in Wisconsin Large Law Firms. This study does not attempt to define specific cultural knowledge of large Wisconsin law firms but instead assesses whether an organizational culture is positive or negative. The hypothesis of this study is as follows. The practice of law is now the business of law. Corporate clients are more sophisticated and in today’s economy have more leverage when hiring large law firms. At the same time technology has flattened the playing field making law firms more similar than different. There is a convergence between large law firms and the output has been commoditized. Law firms with identifiable positive cultures will thrive, while those firms that have a negative culture are less likely to survive. As law firms adapt to the new normal they are undergoing change. Studies show that organizations with a positive culture adapt to change better than organizations with a negative culture. The Organizational Culture Inventory® (OCI®) is the most widely used and thorough researched tool for measuring organizational culture in the world. The inventory presents a list of 120 statements which describe some of the behaviors that might be expected or implicitly required of members of organizations. This quantitative survey was deployed to the 20 largest law firms in Wisconsin. Survey participants included law firm administrators, managing partners and practice group leaders. The results of the survey showed that the overall law firm culture in Wisconsin is positive. Further study is suggested to understand organizational culture within individual law firms as well as law firms outside Wisconsin

Management And Security Of Multi-Cloud Applications

Single cloud management platform technology has reached maturity and is quite successful in information technology applications. Enterprises and application service providers are increasingly adopting a multi-cloud strategy to reduce the risk of cloud service provider lock-in and cloud blackouts and, at the same time, get the benefits like competitive pricing, the flexibility of resource provisioning and better points of presence. Another class of applications that are getting cloud service providers increasingly interested in is the carriers\u27 virtualized network services. However, virtualized carrier services require high levels of availability and performance and impose stringent requirements on cloud services. They necessitate the use of multi-cloud management and innovative techniques for placement and performance management. We consider two classes of distributed applications – the virtual network services and the next generation of healthcare – that would benefit immensely from deployment over multiple clouds. This thesis deals with the design and development of new processes and algorithms to enable these classes of applications. We have evolved a method for optimization of multi-cloud platforms that will pave the way for obtaining optimized placement for both classes of services. The approach that we have followed for placement itself is predictive cost optimized latency controlled virtual resource placement for both types of applications. To improve the availability of virtual network services, we have made innovative use of the machine and deep learning for developing a framework for fault detection and localization. Finally, to secure patient data flowing through the wide expanse of sensors, cloud hierarchy, virtualized network, and visualization domain, we have evolved hierarchical autoencoder models for data in motion between the IoT domain and the multi-cloud domain and within the multi-cloud hierarchy

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

Quality of Service in Distributed Stream Processing for large scale Smart Pervasive Environments

The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs

Food System and Food Security Study for the City of Cape Town

Food insecurity is a critical, but poorly understood, challenge for the health and development of Capetonians. Food insecurity is often imagined as hunger, but it is far broader than that. Households are considered food secure when they have “physical and economic access to sufficient and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (WHO/FAO 1996). Health is not merely the absence of disease, but also encompasses good nutrition and healthy lifestyles. Individuals in a food insecure household and/or community are at greater risk due to diets of poor nutritional value, which lowers immunity against diseases. In children, food insecurity is known to stunt growth and development and this places the child in a disadvantaged position from early on in life. Any improvement in the nutritional profile of an individual is beneficial and as the family and community become more food secure, the greater the benefit. It further reduces the demand on health services. In the Cape Town context, food insecurity manifests not just as hunger, but as long term consumption of a limited variety of foods, reduction in meal sizes and choices to eat calorie dense, nutritionally poor foods in an effort to get enough food to get by. Associated with this food insecurity are chronic malnutrition and micronutrient deficiency, particularly among young children, and an increase in obesity, diabetes and other diet related illnesses. Food insecurity is therefore not about food not being available, it is about households not having the economic or physical resources to access enough of the right kind of food. The latest study of food insecurity in Cape Town found that 75 percent of households in sampled low-income areas were food insecure, with 58 percent falling into the severely food insecurity category. Food insecurity is caused by household scale characteristics, such as income poverty, but also by wider structural issues, such as the local food retail environment and the price and availability of healthy relative to less healthy foods. The City of Cape Town therefore commissioned a study based on the following understanding of the food security challenge facing the City. “Food security or the lack thereof is the outcome of complex and multi-dimensional factors comprising a food system. Therefore, food insecurity is the result of failures or inefficiencies in one or more dimensions of the food system. This necessitates a holistic analysis of the food system that than can provide insights into the various components of the system, especially in our context as a developing world city.” The call for a food system study sees the City of Cape Town taking the lead nationally, being the first metropolitan area to seek to engage in the food system in a holistic manner and attempting to understand what role the city needs to play in the food system. The City must work towards a food system that is reliable, sustainable and transparent. Such a system will generate household food security that is less dependent on welfarist responses to the challenge. In this context, reliability is taken to mean stable and consistent prices, the nutritional quality of available and accessible food, and food safety. Sustainability means that the food system does not degrade the environmental, economic and social environment. Finally, transparency refers to the legibility of the system and its control by the state and citizens

Reinforcement Learning-Based Test Case Generation with Test Suite Prioritization for Android Application Testing

This dissertation introduces a hybrid strategy for automated testing of Android applications that combines reinforcement learning and test suite prioritization. These approaches aim to improve the effectiveness of the testing process by employing reinforcement learning algorithms, namely Q-learning and SARSA (State-Action-Reward-State-Action), for automated test case generation. The studies provide compelling evidence that reinforcement learning techniques hold great potential in generating test cases that consistently achieve high code coverage; however, the generated test cases may not always be in the optimal order. In this study, novel test case prioritization methods are developed, leveraging pairwise event interactions coverage, application state coverage, and application activity coverage, so as to optimize the rates of code coverage specifically for SARSA-generated test cases. Additionally, test suite prioritization techniques are introduced based on UI element coverage, test case cost, and test case complexity to further enhance the ordering of SARSA-generated test cases. Empirical investigations demonstrate that applying the proposed test suite prioritization techniques to the test suites generated by the reinforcement learning algorithm SARSA improved the rates of code coverage over original orderings and random orderings of test cases