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Cloud and Autonomic Computing (CAC)

The opinions, findings, and conclusions or recommendations expressed are those of the Center author(s) and do not necessarily reflect the views of the National Science Foundation.

Center Overview

The Center for Cloud and Autonomic Computing (CAC) pursues research and development in cloud and autonomic computing methods and the application of those methods to systems of interest to industry and government partners. CAC's mission is to advance the knowledge of how to design cloud and autonomic computing systems - that is, computers that are capable of self-healing, self-protecting, and self-optimizing themselves with little involvement of users or system administrators.

At the intersection of cloud computing and autonomic computing, CAC aims to achieve self-management capabilities within and across the layers of cloud computing systems and applications to enable independent operation, minimize cost and risk, accommodate complexity and uncertainty, and enable systems of systems with large numbers of components.

CAC activities on cloud computing cut across several layers of information technology (IT) systems, including: hardware platforms for computing, storage, and networking; design of data centers that aggregate platforms to provide cloud services; systems software and distributed computing middleware providing programming interfaces and management primitives within and across multiple cloud data centers; applications that leverage the on-demand and scalable nature of cloud platforms; and cybersecurity.

Universities

Texas Tech University
University of Arizona

View Center Website

Center Personnel

Alan Sill
Center Staff
+1 806 742 3884
Alan.Sill@ttu.edu

Salim Hariri
Center Staff
+1 520 626 6000
hariri@ece.arizona.edu

Research Focus

Autonomic computing engines and applications

Consolidated and virtualized data centers and clouds have become the dominant computing platforms in industry and research for enabling complex and compute-intensive applications. As scales, operating costs, and energy requirements increase, however, maximizing efficiency, cost-effectiveness, and utilization of these systems becomes paramount. Furthermore, the complexity of application workloads makes on-demand scalability critical. CAC is developing autonomic computing and applications frameworks that can support a wide range of applications.

Distributed systems

CAC is developing networks that respond to dynamic network configurations while ensuring high performance, fault tolerance, and security, and integrating these networks with virtualization techniques to provide seamless peer connectivity to a wealth of applications.

Network defense

Autonomic defense systems detect and protect against all types of network attacks. CAC has developed expertise through advanced modeling and deployment of real-world capable systems using autonomic methods for network threat assessment, mitigation, and defense.

Power management

CAC research in this area targets the development of a theoretical framework and a general methodology for autonomic power and performance management of high-performance distributed systems.

Software management

The explosive growth in scale and functionality of enterprise software systems and underlying IT infrastructures has resulted in complex systems whose control and timely management is rapidly exceeding human ability. CAC research in this area is dedicated to developing and integrating autonomic techniques for monitoring, modeling, configuring, controlling, and optimizing the behaviors of applications, services, and resources, to ensure their robust and resilient operation in the face of these challenges.

Virtualized data centers

CAC is working to develop self-monitoring and self-optimization techniques that, when applied to the management of virtualized containers, can lead to increased efficiencies in resource utilization and reduced costs of provisioning.

Awards

1624668

I/UCRC: Phase II: Industry/University Cooperative Research Center for Cloud and Autonomic Computing (CAC)

The explosive growth of IT and cloud infrastructures, coupled with the diversity of their components and a shortage of skilled IT workers, have resulted into systems whose control and timely management exceeds human ability. The mission of the NSF Industry/University Cooperative Research Center for Cloud and Autonomic Computing (CAC) is to advance the knowledge of how to design and engineer computing systems and applications that are capable of managing themselves, adapting their resources and operations to current workloads and anticipating the needs of their users. The CAC with three university sites (the University of Arizona, the Mississippi State University, and Texas Tech University) will lead research of innovative designs and programming paradigms for cloud and computing systems that can self-configure, self-heal, self-optimize and self-protect with minimal involvement of IT administrators or users. We are planning to involve the Auto Industry through the University of Detroit Mercy (UDM), who is an affiliated member with UA. The CAC not only advances the science of autonomic computing but also accelerates its transfer to industry by closely working with industrial partners in the definition of projects pursued by the CAC, and contributing to the education of a workforce capable of designing and deploying cloud and autonomic computing systems. The CAC will involve students and faculty from underrepresented groups through several dissemination and recruiting initiatives at each site.Today's IT and cloud infrastructures face significant management challenges that result from, among other factors, their distributed nature, their need to adapt to unanticipated demands, their heterogeneity, their size, large numbers of users and great complexity and diversity of IT and cloud services. The mission of CAC is to engage academics, industrial and government partners in joint efforts that accelerate both our understanding of the fundamentals of cloud and autonomic computing, and the transfer of these fundamentals into industry solutions and education of a workforce capable of designing autonomic systems in general and cloud systems in particular. The CAC will conduct research on how to enable systems to be self-managed with respect to performance, fault, security, resilience, power consumption, etc. Unlike past attempts that address these properties in isolation, the CAC will endeavor to pursue integrated approaches that address more than one property. The technical scope of the Center?s activities includes design and evaluation methods, algorithms, architectures, software, mathematical foundations and benchmarks for cloud and autonomic systems. Solutions are studied for different levels of both centralized and distributed systems, including the hardware, networks, storage, middleware, services and information layers. The CAC solutions will focus more on self-management and security issues in Internet of Things (IoT), critical infrastructures and cloud systems and applications. The following are concrete examples of industry-relevant technical challenges that the CAC will address in the context of autonomic IT infrastructures: Automatic management of performance and energy consumption in large scale data centers and cloud systems; Securing and protecting the operations of sensors and actuators in IoT environments and their applications or services; Predictive modeling of quality-of-service of IT and cloud resources and applications; Dynamic resource provisioning and scheduling of computer resources; Autonomic management and protection of critical infrastructures; and Automation of system management operations of Internet of Things (IoT) resources and services. Read More >

1939140

Phase-II IUCRC Texas Tech University: Center for Cloud and Autonomic Computing

In this project, Texas Tech University will extend the previously successful industry-driven research program of the Cloud and Autonomic Computing (CAC) Industry-University Cooperative Research Center (IUCRC) as part of the NSF IUCRC program. The CAC Center currently comprises participants from two principal academic institutions, Texas Tech University (TTU) and the University of Arizona (UA), as well as two affiliate sites associated with TTU: the University of North Texas and Texas State University, and two international sites associated with UA: Universidad de Sonora, Mexico and American University of Malta. The mission of the NSF CAC Center across all participating sites is to conduct research and development activities that advance the knowledge of how to design and engineer highly distributed (cloud) and highly automated (autonomic) computing systems for practical applications with stakeholders including industry, federal agencies, and academia together. This grant will extend the IUCRC research of the CAC at TTU from Phase I to Phase II.The TTU site of the NSF CAC focuses on advances in algorithms, methods, standards, and tools for cloud and highly automated computing systems. The Phase-II program of CAC@TTU site will continue research and development in areas including: 1) code development and Application Programming Interface (API) design for data acquisition, procedural, and workflow control; 2) high-performance data analytics and visualization in the cloud and autonomic computing settings; 3) improvements to practical applications of methods that use these and other cloud and autonomic computing techniques and methods; 4) standards implementations and design for cloud software and underlying infrastructure; and 5) applications of the above to data center control based in both industry and academic arenas. The CAC@TTU site will pursue these overall themes while remaining open to new and emerging opportunities that relate to the needs of current and future industry members or that come up through pursuit of the program of research.NSF funding for this project plays a key role in facilitating and promoting research collaboration among stakeholders including industry, federal agencies, and academia. This project will also train a broadly inclusive and globally competitive science workforce for the nation by integrating the latest development and advanced knowledge into mentoring and educational activities. Texas Tech University is a Hispanic-Serving Institution, and the Phase-II CAC@TTU effort will leverage its experience in Phase I to carry out research and development activities to have broader impacts, including targeted efforts to integrate hands-on learning experiences for historically under-represented population groups, actively engaging undergraduate students in research programs, and organizing community activities such as workshops and conferences. These activities will also be coordinated with the overall CAC center program of broader engagement.The Phase-II CAC@TTU site will distribute portions of its output through GitHub repositories (https://github.com/nsfcac) and websites including https://nsfcac.org/, http://cac.ttu.edu/, and https://discl.cs.ttu.edu/ for public releases of software, data, and results. The project members will provide industry motivation, expertise, and materials to facilitate research and development progress. The websites and repositories will be maintained for three years past the project completion date, and principal investigators will strive to maintain the associated output software products that remain in use as long as possible.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. Read More >

Member Organizations

IUCRC affiliated member organizations are displayed as submitted by the Center. Non-federal organizations are not selected, approved, or otherwise endorsed by the National Science Foundation.

Black Fur
Dell EMC
DOD/NSF JITC
Lancium LLC
Lbk. County Detn. Center
Legendary Labs
Los Alamos National Lab
Monsoon Blockchain
National Security Agency
US Navy