[Air-L] Call for Workshop Papers -- IEEE HPSR 2023 -- Deadline: April 5, 2023

Fri Feb 24 08:32:56 PST 2023

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IEEE International Conference on High Performance Switching and Routing

Artificial Intelligent Next Generation (NextG) Integrated Communications and Computing Systems

5-7 June 2023 @ Albuquerque, New Mexico

https://hpsr2023.ieee-hpsr.org/

https://twitter.com/ieeehpsr2023

*IEEE HPSR 2023 Organizing Committee is planning for an in-person conference and encourages the authors to participate physically; however, we understand that the pandemic situation is not over yet. Therefore, depending on the situation during the conference time, remote participation and online presentation may be allowed under special circumstances.

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IEEE International Workshop on StateLess as a Service for Edge Computing (EDGELess 2023)

https://sites.google.com/view/edgeless-2023

Call for Papers

The workshop will primarily focus on addressing the challenges encountered in deploying and developing edge computing applications using the serverless paradigm. As we know, serverless computing, also known as Function as a Service (FaaS), has gained significant momentum in recent times and is deemed the next-generation cloud service delivery paradigm. Serverless computing will help users, and developers smoothly and seamlessly deploy their applications for Edge computing environments like sensor-based technologies, the Internet of Things, cyber-physical systems, big data analytics, machine learning, cognitive computing, and artificial intelligence. All the service providers of the major league, i.e., Amazon, Google, Microsoft, have successfully launched commercially usable serverless computing platforms. Although the services are commercially available and functional, several unresolved and challenging issues persist.

This workshop aims to provide a forum for researchers and practitioners to exchange innovative ideas, latest research findings, practical experiences, lessons learned, and future directions to propel the research on utilizing serverless infrastructure for smart and pervasive computing. The topics include, but are not limited to:

Edge-Serverless for middleware applications

Opportunities in Serverless Edge Computing

Stateless Life-cycle

Cloud to Edge Integration

Architecture support for edge computing

Fine-grained Auto-scaling

Faster response sensitive applications

Edge computing in IoT offloading

Workload characterization and analysis at the edge

On-device artificial intelligence

Audio/video streaming techniques

Real-time multimedia techniques

Quality of Service (QoS) improvements techniques

Edge-Serverless coordinated issues

Cold Starts handling

Energy efficient edge computing

Workshop Co-Chairs:

Sourav Kanti Addya, National Institute of Technology Karnataka, India.

Eirini Eleni Tsiropoulou, University of New Mexico Albuquerque, NM, USA.

Sandip Chakraborty, Indian Institute of Technology Kharagpur, India.

 Submit Paper to StateLess as a Service for Edge Computing (EDGELess 2023): https://edas.info/N30489

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IEEE International Workshop on Automated and high performance Networks Through Intent-BAsed Networking (ANTIBAN)

https://sites.google.com/view/hpsrantiban2023/home?pli=1

Call for Papers

Intent-Based Networking (IBN) is a new technology that aims to automate the configuration of networks and facilitate the interaction of all-levels of users with the underlying infrastructure and network equipment. IBN, through the submission of high-level intents describing what the user wants instead of how to do it, is expected to create a flexible and vendor agnostic manner to manage the network, while reducing the complexity and the manually error-prone process to configure the network.

IBN is creating immense opportunities for any kind of network operator and infrastructure provider and reduces the knowledge gap between novice and expert users. However, IBN as a relatively new technology presents a multitude of open challenges that need to be addressed. For instance, how can an intent be expressed appropriately by network users of different experience and addressed to networks with different capabilities? Furthermore, how can intents be accurately translated into low-level configuration policies? Additionally, how can the intent activation be conducted efficiently and be assured throughout its lifetime to guarantee a high- performance configuration that will present the necessary self-properties of an autonomous network?

The above are just few of the many challenges that IBN has to tackle. Accordingly, this workshop is soliciting conceptual, theoretical and experimental contributions to a set of currently unresolved challenges in the area of IBN and autonomous networks, with the goal to create High Performance and self-managed networks.

Topics:

Intent expression through Natural Language Processing

Intent modeling and policy extraction

IBN specific languages

Automated policy conflict detection and resolution

Intent activation towards high performance networks

Intent assurance for self-managed networks (Self-Healing, Self-Configuration, Self-

Optimization, Self-Protection, etc.)

Architectural considerations for management and orchestration of IBN Systems

Performance analysis of IBN Systems

Business and techno-economics opportunities for IBN applications and use cases

Workshop Co-Chairs:

  *   Marios Avgeris, Carleton University, Ottawa, Canada.
  *   Aris Leivadeas, École de Technologie Supérieure (ÉTS), Montreal, Canada.

Submit Paper to Automated and high performance Networks Through Intent-BAsed Networking (ANTIBAN): https://edas.info/N30492

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IEEE International Workshop on Resource-Constraint Machine Learning: Unlocking the potentials of edge computing devices and networks
https://rcmlworkshop.github.io/

Call for Papers

Machine learning (ML) systems are gaining immense popularity and are increasingly deployed in edge computing devices and networks. These devices are characterized by limited computing capabilities, being also restricted by power constraints. Similarly, edge-first networks face delays, jitter, and packet losses due to resource contention, high traffic loads, and other reasons. ML can be used to process and analyze data from edge devices and sensors to extract useful information and insights. This information can then be used to make decisions about how to manage and optimize at run-time both the edge devices and the network. Additionally, ML can help to identify patterns and correlations in data, which can be used to improve decision-making. However, there are a number of challenges associated with implementing machine learning on edge devices and networks.

The RCML Workshop aims to stimulate research on the latest advancements in resource-constraint machine learning for edge systems. Research results from funded projects in the general area of machine learning optimizations for edge computing are especially encouraged. Overall, the workshop seeks original manuscripts in the scope of the workshop, but not limited to:

Resource-aware machine learning algorithms

Energy-efficient hardware accelerators for machine learning

Machine learning for edge-first networks

Resource management in edge-first networks

Approximate computing

Reconfigurable systems

Methods for machine learning optimization and compression

Emerging design technologies for future computing

Power-efficient and sustainable computing

Internet of Things

Case studies of machine learning for edge systems

Protocols for communication in edge-first networks

End-to-end protocols, flow and congestion control

Pervasive and wearable computing and networking

Artificial intelligence and machine learning for wireless networks

Attack modelling, prevention, mitigation, and defense in wireless networks

Reinforcement learning and deep learning for networks

Workshop Chair:

Iraklis Anagnostopoulos, Southern Illinois University Carbondale, USA.

Submit Paper to Resource-Constraint Machine Learning: Unlocking the potentials of edge computing devices and networks: https://edas.info/N30491

Important Dates

Paper Submission Due: April 5, 2023

Acceptance Notification: April 21, 2023

Author Registration Deadline: April 24, 2023

Final Version Submission Due: May 1, 2023 (Firm)

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Eirini Eleni Tsiropoulou, Assistant Professor
Computer Engineering Vice Chair
Director of Recruiting and Admissions

Department of Electrical and Computer Engineering
University of New Mexico Albuquerque, NM, 87131
Office: 326B
Tel.: (505)-277-5501
Email: eirini at unm.edu<mailto:eirini at unm.edu>
Website: PROTON Lab<http://ece-research.unm.edu/tsiropoulou/index.html>
PROTON Lab's News: @Tsiropoulou_EE<https://twitter.com/Tsiropoulou_EE>

"Those who know, do. Those that understand, teach." ~ Aristotle