5th International Conference "Modern Network Technologies" (MoNeTec-2024)
Moscow State University, Oct 29-31, 2024, Moscow, Russian Federation
To the 270th Anniversary
of Lomonosov Moscow State University

Matrix decompositions and learning from big data

Even most powerful supercomputers cannot deal directly with astronomically big data coming as an array of all elements. Any data on that scale can be processed only if it has an agreeable structure reflected by an appropriate representation model.

For instance, if a matrix is known to be well approximated by a matrix of rank r, then the model can be a skeleton decomposition constructed only from some cross of its r columns and r rows. In many cases, the data can be well approximated by some matrix or tensor decompositions to be learned from a small sample of its elements.

How to select these elements? In the talk, we give a sketch of most useful

matrix and tensor decomposition and consider a simple and as well very powerful principle of selections of data on which the model is learned.

Quality of Service Control Challenges in Data Communication Networks

The presentation addresses the challenges of ensuring deterministic Quality of Service (QoS) in data communication networks. The main focus is on methods for optimal channel selection with specified QoS requirements, transport flows balancing and computational tasks distribution in compliance with SLA requirements. The discussed methods are based on a multi-agent approach.

Understanding Computility Net: A Distributed System Perspective

Computility net provides opportunities to transcending state-of-the-art technologiesin AI, computing and network. This talk will delve into the evolution and architectural design of computility net from the perspective of distributed systems, tracing traditional models like grid and cloud computing to modern computility networks. The discussion will then focus on the specific challenges posed by computility net, particularly in terms of managing heterogeneous compute nodes and network connections. Architectural strategies that effectively address these challenges and facilitate optimal resource allocation across multiple computing centers will be explored. Additionally, the talk will indicate the diverse applications of computility networks in areas such as AI, scientific computing, and beyond, demonstrating their wide-reaching impact and potential

AIOT: Industrial Internet of Things

AIOT is a transformative integration of AI with the Industrial Internet of Things (IIoT). This keynote speech will delve into the synergy between advanced data analytics, AI techniques, and the vast network of connected industrial devices. The fusion of AI with IIoT is revolutionizing the way industries operate, offering unprecedented levels of efficiency, predictive maintenance, and so on. The speech will highlight how AIOT is enabling smarter manufacturing through various techniques.

Industrial Intelligence by “Data+Knowledge” & Edge-Cloud Collaboration

The industrial Internet is a new generation of intelligent network formed by the deep integration of industrial production systems, DT, CT, OT, AIOT, and AI. Its core is the integration and application of sensing, analysis, decision-making and control. As the next generation of industrial infrastructure, the industrial Internet will reshape the entire industrial production and manufacturing system, helping to digitalize, network, and intelligentize the industrial production. The core tasks are ubiquitous low-power smart sensing, wireless interconnection of everything, intelligent computing and service. In this report, I will share some of the challenges of industrial intelligence based on industrial knowledge and data, especially in intelligent sensing, edge computing, AI models under knowledge and data fusion, industrial MIP solvers, security and privacy of data and computing. I will then share some preliminary research results and explorations in this area.

Domain Specific language Engineering via Language Lifting

In the "software defines everything" era of information technology, safe and user-friendly domain-specific languages (DSLs) have gained increasing significance. These DSLs facilitate the direct representation of problems and algorithms tailored to specific professional fields, while empowering domain experts to craft code using domain-specific terminology and operations intuitively. However, developing DSLs tailored for domain experts remains a persistent challenge. Traditional embedded DSL design methodologies provide a rapid prototyping technique for DSL implementation. Yet, the close integration between the embedded DSL and the host language poses difficulties for domain experts unfamiliar with the host language. In this talk, I introduce a new approach to support rapid DSL implementation and the development of an IDE for the DSL. This approach incorporates an extensible general-purpose core language, a DSL definition technique leveraging syntactic sugars, and crucially, a language lifting for generating DSL implementations alongside an IDE optimized for DSL programming. We have devised a system, named Osazone, and employed it to create numerous DSLs, thereby demonstrating the flexibility, efficacy, and practicality of our approach in advancing domain-specific language engineering efforts.