Trustworthy Autonomous Intelligent Systems

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Modern society relies on services and applications that are delivered by a variety of systems and infrastructures: data centers, clouds spanning core, edge, and sensor/IoT computing, Internet service provider networks, cellular networks, multimodal transportation networks, and power grids. These services and applications infrastructures are increasingly more diverse in their characteristics and their requirements call for more sophisticated, precise and responsive control. For example, power grids no longer provide only unidirectional delivery of energy, but must now support dynamic power transfer from different types of renewable and conventional energy sources to meet existing and new power demands, such as electric vehicles. As well, in mobility there is a transition from private cars to the seamless multimode travel (trains, buses, subways, shared vehicles and bicycles, and walking). Furthermore, mobility, energy, computing and networking infrastructures must consider environmental impacts such as carbon footprint and air pollution. ******The goal of this research program is to advance the understanding, creation, design, and operation of trustworthy autonomous intelligent control and management systems (CMSs) that direct the allocation of resources in large-scale infrastructures to enable the delivery of services and applications that vary in terms of quality, quantity/volume, and cost. The CMSs mediate between the demand services and availability of resources. Many of these services are mission critical, and so the CMS be trustworthy and reliable, in the presence of fluctuations in supply and demand, and of failures and attacks. The scale and complexity of infrastructures require that the CMS leverage artificial intelligence (AI) and machine learning (ML) to enable autonomous operation. We address four challenges to achieve our CMS goal:*** 1. Intent-Driven Networking. How can high-level statements regarding policies and intent be translated into high-fidelity low-level management and control actions?*** 2. Analytics and Learning for Autonomous Operation. How can analytics, AI and ML be applied in management and control of distributed large-scale infrastructures to enable trustworthy self-optimizing, self-configuring, self-healing, self-protecting adaptive behavior? *** 3. Mechanism Design: Incentives and Pricing. How can high-level global objectives be translated into incentives and pricing signals that induce globally beneficial user resource consumption?******Our methodology for CMSs integrates: 1. Algorithm design; 2. Implementation in software; 3. Proof-of-concept systems.******Our research impacts will be:*** Secure, private, responsive and reliable delivery of applications in computing clouds, IoT and 5G networks*** Dramatic reduction in the number of vehicles on the road through multimode travel, autonomous vehicles and Mobility-on-Demand*** Mitigation and elimination of pollution in metropolises through renewable energy and vehicle electrification.*****