SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network

In the rapid development of artificial intelligence, solving complex AI tasks is a crucial technology in intelligent mobile networks. Despite the good performance of specialized AI models in intelligent mobile networks, they are unable to handle complicated AI tasks. To address this challenge, we propose Systematic Artificial Intelligence (SAI), which is a framework designed to solve AI tasks by leveraging Large Language Models (LLMs) and JSON-format intent-based input to connect self-designed model library and database. Specifically, we first design a multi-input component, which simultaneously integrates Large Language Models (LLMs) and JSON-format intent-based inputs to fulfill the diverse intent requirements of different users. In addition, we introduce a model library module based on model cards which employ model cards to pairwise match between different modules for model composition. Model cards contain the corresponding model's name and the required performance metrics. Then when receiving user network requirements, we execute each subtask for multiple selected model combinations and provide output based on the execution results and LLM feedback. By leveraging the language capabilities of LLMs and the abundant AI models in the model library, SAI can complete numerous complex AI tasks in the communication network, achieving impressive results in network optimization, resource allocation, and other challenging tasks

Towards 6G: Key technological directions

Sixth-generation mobile networks (6G) are expected to reach extreme communication capabilities to realize emerging applications demanded by the future society. This paper focuses on six technological directions towards 6G, namely, intent-based networking, THz communication, artificial intelligence, distributed ledger technology/blockchain, smart devices and gadget-free communication, and quantum communication. These technologies will enable 6G to be more capable of catering to the demands of future network services and applications. Each of these technologies is discussed highlighting recent developments, applicability in 6G, and deployment challenges. It is envisaged that this work will facilitate 6G related research and developments, especially along the six technological directions discussed in the paper

Survey and Analysis of Production Distributed Computing Infrastructures

This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures

Knowledge-based Intent Modeling for Next Generation Cellular Networks

Intent-based networking (IBN) facilitates the representation of consumer expectations in a declarative and domain-independent form. However, mapping intents to service and resource models remains an open challenge. IBN requires handling existing system data in a structured yet flexible structure way. Knowledge graphs provide an efficient conceptual framework for constructing contexts and organizing known information. We utilize knowledge graphs to construct a knowledge-based for modeling of intents in the networking domain. In addition, this work also proposes a knowledge-based intent modeling and processing methodology, extending the standardized intent common model proposed by TM Forum for next-generation cellular networks and services. The proposed knowledge-based IBN approach is demonstrated for next-generation cellular services, validating its potential.Comment: Accepted at MeditCom 202

Intent-based network slicing for SDN vertical services with assurance: Context, design and preliminary experiments

Network slicing is announced to be one of the key features for 5G infrastructures enabling network operators to provide network services with the flexibility and dynamicity necessary for the vertical services, while relying on Network Function Virtualization (NFV) and Software-defined Networking (SDN). On the other hand, vertical industries are attracted by flexibility and customization offered by operators through network slicing, especially if slices come with in-built SDN capabilities to programmatically connect their application components and if they are relieved of dealing with detailed technicalities of the underlying (virtual) infrastructure. In this paper, we present an Intent-based deployment of a NFV orchestration stack that allows for the setup of Qos-aware and SDN-enabled network slices toward effective service chaining in the vertical domain. The main aim of the work is to simplify and automate the deployment of tenant-managed SDN-enabled network slices through a declarative approach while abstracting the underlying implementation details and unburdening verticals to deal with technology-specific low-level networking directives. In our approach, the intent-based framework we propose is based on an ETSI NFV MANO platform and is assessed through a set of experimental results demonstrating its feasibility and effectiveness

Knowledge Collaboration: Working with Data and Web Specialists

When resources are finite, people strive to manage resources jointly (if they do not rudely take possession of them). Organizing helps achieve—and even amplify—common purpose but often succumbs in time to organizational silos, teaming for the sake of teaming, and the obstacle course of organizational learning. The result is that organizations, be they in the form of hierarchies, markets, or networks (or, gradually more, hybrids of these), fail to create the right value for the right people at the right time. In the 21st century, most organizations are in any event lopsided and should be redesigned to serve a harmonious mix of economic, human, and social functions. In libraries as elsewhere, the three Ss of Strategy—Structure—Systems must give way to the three Ps of Purpose—Processes—People. Thence, with entrepreneurship and knowledge behaviors, data and web specialists can synergize in mutually supportive relationships of shared destiny

Advanced manned space flight simulation and training: An investigation of simulation host computer system concepts

The findings of a preliminary investigation by Southwest Research Institute (SwRI) in simulation host computer concepts is presented. It is designed to aid NASA in evaluating simulation technologies for use in spaceflight training. The focus of the investigation is on the next generation of space simulation systems that will be utilized in training personnel for Space Station Freedom operations. SwRI concludes that NASA should pursue a distributed simulation host computer system architecture for the Space Station Training Facility (SSTF) rather than a centralized mainframe based arrangement. A distributed system offers many advantages and is seen by SwRI as the only architecture that will allow NASA to achieve established functional goals and operational objectives over the life of the Space Station Freedom program. Several distributed, parallel computing systems are available today that offer real-time capabilities for time critical, man-in-the-loop simulation. These systems are flexible in terms of connectivity and configurability, and are easily scaled to meet increasing demands for more computing power

Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results

Fixed and mobile telecom operators, enterprise network operators and cloud providers strive to face the challenging demands coming from the evolution of IP networks (e.g. huge bandwidth requirements, integration of billions of devices and millions of services in the cloud). Proposed in the early 2010s, Segment Routing (SR) architecture helps face these challenging demands, and it is currently being adopted and deployed. SR architecture is based on the concept of source routing and has interesting scalability properties, as it dramatically reduces the amount of state information to be configured in the core nodes to support complex services. SR architecture was first implemented with the MPLS dataplane and then, quite recently, with the IPv6 dataplane (SRv6). IPv6 SR architecture (SRv6) has been extended from the simple steering of packets across nodes to a general network programming approach, making it very suitable for use cases such as Service Function Chaining and Network Function Virtualization. In this paper we present a tutorial and a comprehensive survey on SR technology, analyzing standardization efforts, patents, research activities and implementation results. We start with an introduction on the motivations for Segment Routing and an overview of its evolution and standardization. Then, we provide a tutorial on Segment Routing technology, with a focus on the novel SRv6 solution. We discuss the standardization efforts and the patents providing details on the most important documents and mentioning other ongoing activities. We then thoroughly analyze research activities according to a taxonomy. We have identified 8 main categories during our analysis of the current state of play: Monitoring, Traffic Engineering, Failure Recovery, Centrally Controlled Architectures, Path Encoding, Network Programming, Performance Evaluation and Miscellaneous...Comment: SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIAL

Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030

The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment