The Network Science and Engineering (NetSE) program has been created to develop the science and engineering of these networks, yielding new scientific understanding about their complexity and informing their future design. The program subsumes and expands upon the former CISE programmatic areas of Future INternet Design (FIND), Science for the Internet Next Generation (SING) and Next-Generation Information Systems (NGNI). NetSE specifically challenges individuals and teams with different perspectives, e.g. theoreticians and experimentalists, as well as different domain expertise, e.g. mathematicians, information, computer, social and economic scientists, and engineers, to come together to address this important challenge.
NetSE seeks proposals focused on developing the scientific foundations necessary to understand and reason about socio-technical networks. Of particular interest are frameworks that explicitly incorporate human values at multiple levels and scale, inform the development of applications, services and network technologies, and give coherence to the highly diverse ways users might create and access information in the future. NetSE also encourages research proposals focused on exploring network architecture innovations. Encouraged to take "clean slate" approaches unconstrained by the current Internet, researchers are empowered to rethink network functions, layers and abstractions in the context of a range of scientific, technical and social challenges and opportunities. NetSE emphasizes integrative activities focused on creating and synthesizing network components into theoretically grounded architectures that address fundamental policy and design trade-offs, support sound economic models, and promote social benefits. Future networks must also be designed to provide users with timely and coherent access to massive quantities of highly distributed information. Consequently, the NetSE program encourages research on Internet-scale, topologically-aware models for accessing, processing and aggregating multiple high-volume information flows; and on cognitive capabilities, context-awareness, and architectures that enable the discovery, invocation and composition of globally distributed, highly evolving services and information systems. These new kinds of models, capabilities, and architectures in turn enable the exploration of new applications that provide information based on both content and context, and the improvement of existing classes of applications, such as gaming, virtual worlds, augmented reality and tele-presence.
NetSE proposals should include a description of how research ideas will be validated, for example through formal verification, simulation, modeling, proof-of-concept development, prototype testing on a testbed, or when applicable, usability evaluation involving human subjects.
The program will support projects that strengthen the scientific foundations of trustworthiness, in order to inform the creation of new trustworthy technologies. We especially seek new models, logics, algorithms, and theories for analyzing and reasoning about all aspects of trustworthiness -- security, privacy, and usability-- about all systems and data components and their composition. Building on its predecessor program Cyber Trust, the Trustworthy Computing program will also continue to support projects that explore the fundamentals of cryptography, that examine and strengthen security weaknesses in current algorithms and protocols, and that explore new computing models that have potential to improve trustworthiness and our ability to reason with respect to different aspects of trustworthiness.
A trustworthy system depends on its building blocks and their interoperability. These building blocks range from hardware processes, possibly with new features to support trustworthiness, to network protocols and system software, to applications software and data. While today many researchers focus on one of the many building blocks that comprise our systems, the Trustworthy Computing program encourages investigators to explore research opportunities directed towards integrating these building blocks through new security architectures, with emphasis on those that are generic but also including those that are application-specific.
As computing systems continue to pervade every aspect of daily life, people need to be able to trust them-so much of their lives depend on them. The Trustworthy Computing program seeks proposals to provide scientific and technological perspectives on privacy. Threats to citizens' privacy arise in many sectors of daily life, e.g., health, financial, and e-commerce, and assuring privacy is essential to the foundations of democracy, e.g., voting and the freedom of speech. The program will support the exploration of new scientific methodologies and technologies to formulate, reason about, and resolve conflicts among privacy policies, and to explore the interplay among privacy, security and legal policies. Further, we need new models, methods, algorithms, and tools, including logics and privacy metrics, to safeguard the information of individuals wherever it may digitally reside. Future systems also raise complex security concerns regarding integration of identity and privacy protection. Needed are attack-resistant methods and protocols for identity management commensurate with application requirements, that preserve privacy and enforce accountability.
The Trustworthy Computing program also seeks proposals focused on usability. Incorporating trustworthiness into a system should not place undue demands on human users or impact human or system performance. People are often the weakest link in security. How can we make it easy for people to use computing systems yet still protect them from unforeseeable attacks on their security and privacy? The needs of users are many, and include being informed of threats and breaches, to managing the appropriate dissemination of personal information on social networks, to controlling access to information that may be harmful to minors. System design for usability in different contexts demands new approaches to integrating and balancing among different functionalities, understanding human perception of trust including privacy, informing users of potential pitfalls, and predicting the potential consequences of user decisions. Needed are new methods, supported by automation, to promote usability and provide users with security controls they can understand.
Understanding the interplay between people and technology is also essential, for trustworthiness cannot be assured through technological innovation alone. Consequently, the Trustworthy Computing program will support multidisciplinary research proposals that consider both the social and technical dimensions of creating a trustworthy computing future, recognizing that such research must be undertaken in a context that considers regulatory and legal implications.
If we are to make progress toward realizing a trustworthy computing future, we must characterize trustworthiness and the many different classes of threats. While current solutions largely focus on known security threats, the Trustworthy Computing program seeks proposals aimed at characterizing future threats too, where such threats may be driven by adversarial motives that are yet to be identified or understood. Methods must be developed to evaluate systems for trustworthiness, so that they can be confidently used. Evaluation may include a combination of methods that involve analytical reasoning, simulation, experimental deployment and, where possible, deployment on live systems. New technology is required, such as testbeds and methodologies that enable system experimentation at scale without exposing operational systems to threats, such as those that may be unintentionally introduced by trustworthiness enhancements. Metrics must be developed that can confidently predict system trustworthiness based on realistic assumptions of the capabilities of adversaries, and they must be measurable or amenable to reasoning. Requirements for trustworthiness must be defined, so that they inform the effective design of trustworthy computing and communications systems.
The need to operate in heterogeneous, unpredictable and challenging environments requires ground-breaking approaches and methodologies to advance our understanding of how computation is performed and how resources are managed, at varying levels of granularity and scale. The proliferation of Internet-scale applications and services poses new challenges and require radical thinking of how distributed computation is carried out and how future file and storage systems are designed and managed. The difficulty of these challenges grows with the number of users and the intensity of the data. This is further compounded by the need for energy-efficient and self-managing systems and computing capabilities, support for pervasive access to both personal and very large-scale storage and data resources, including support for caching, replication and consistency at scale. Fundamental advances in methods and models to address power, thermal and sustainability issues in the design and operation of computing resources from chips to large scale data centers and study of tradeoffs between energy efficiency, performance and reliability are also essential to reduce the carbon footprint of fast expanding information technologies that are shaping our society. Frameworks, approaches and methodologies to address these challenges must show potential to improve system's characteristics, such as manageability, configurability, operational sustainability, usability and performance, while reducing vulnerabilities.
As mobile device technology continues to evolve, pervasiveness and ubiquity are increasingly becoming essential requirements of future distributed systems. The dynamic and heterogeneous nature of ubiquitous and pervasive computing environments, coupled with the interaction between human and devices, give rise to unique fundamental and socio-technical challenges. At the core of these challenges is the concept of context, its representation and the underlying principles that underpin how human behavior, activity and interaction with the environment are captured at the appropriate levels of detail. Advances in context-aware, pervasive and ubiquitous computing require new programming models, abstractions and languages. Methodologies and tools are also needed to monitor, evaluate and predict the performance of ubiquitous systems and assess users' experience. Collaborations with researchers in artificial intelligence and the social sciences that provide new perspectives on how human and context-aware ubiquitous computing are encouraged.
Fully leveraging the opportunities and unprecedented levels of parallelism offered by multi-core architectures poses new challenges which bring into question traditional frameworks, approaches and methodologies for system and software design in large-scale, high performance environments. Addressing these challenges requires sound parallel execution and memory models, innovative system-level approaches to automatic parallelization of sequential programs, novel compiler techniques and dynamic run-time execution to expose and exploit inherent parallelism and optimize code generation, and new design approaches for high performance I/O systems. Understanding parallel systems and applications also requires innovative methodologies and tools for quantitative and qualitative characterization, evaluation, monitoring and prediction of system behavior at different levels, including the implications of workloads in system design in large-scale, high performance environments.
CSR seeks advances that are specific to an application domain or a particular hardware platform as well as generic across domains and/or platforms. Also sought are proposals focused on advancing the state-of-the art in systems and software research for compute-intensive applications and hardware. Proposal focused on data-intensive applications and hardware should be submitted to the Data-intensive Computing cross-cutting program: http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf09558. Investigators interested in the CSR program may also wish to consider the Software and Hardware Foundations program: http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf09555, which supports foundational software and hardware research essential to enhance the capability of computing systems. CSR PIs should describe credible plans for demonstrating the utility and potential impact of their proposed work.
For more information on the types of projects supported by the CSR program, please visit our web site athttp://www.nsf.gov/cise/cns/csr_pgm.jsp.
Networking Technology and Systems [CORE] (NeTS) Future computer and communication networks must be available anytime and anywhere, be accessible from any communication device, be resource-efficient, require little or no management overhead, be resilient and adaptive to failures and malicious attacks, and be trustworthy for all types of communications. They must be able to evolve over time to incorporate new technologies, support new classes of applications and services, and meet new requirements and challenges. They also need to accommodate growth and unforeseen changes across many dimensions, including types of applications, traffic load, network size and topology, physical link characteristics, different mobility patterns, and heterogeneity, while achieving high-energy efficiency and reduced performance degradation.
The Networking Technology and Systems (NeTS) program supports the exploration of innovative and possibly radical network architectures, algorithms, protocols, and technologies that are responsive to the evolving requirements of current and yet to be discovered network services and applications operating in various environments. The NeTS program will enable scientific and technological advances leading to the development of future generation, high performance networks. The scope of the program ranges from personal area and home networks, to wireless and sensor networks, to enterprise, core and optical networks, and peer-to-peer and application-level networks.
Of interest is research in innovative paradigms, architectures, algorithms and protocols to address various challenges, in wired, wireless and sensor networks. Examples include the interconnection of heterogeneous networks, topology management, resource and service discovery, naming and addressing, routing and congestion control, mobility management at different levels and granularities, virtualization at scale and programmability of hetergeneous physical substrates, strategies for the location of intelligence within the network and at endpoints, and the impact of widely distributed, data intensive computing resources as in cloud computing. In the area of network control and management, NeTS will entertain innovative projects focused on novel frameworks, methods, protocols and tools that enable effective network monitoring, security, management, performance measurement, modeling, quality of service and diagnosis. Proposed solutions are expected to bring the network closer to autonomy, where the need for human intervention is minimal.
NeTS also seeks transformative research focused on the development of scalable, non-intrusive mechanisms, tools, and methodologies for network measurement and characterization, network simulation and network performance analysis, including the development and distribution of benchmarks targeted at specific classes of networking research, both for wired and wireless networks and protocols.
Research outcomes in the form of software and hardware technologies should be scalable, energy-efficient, ensure robust network operation, even in the most demanding and high performance environments, and be able to support automatic instantiation of protocols and facilitate their evolution. Projects focused on innovative holistic approaches to address the end-to-end requirements of current and emerging applications in large-scale, heterogeneous networks are encouraged.
Networking research and education projects of an inter-disciplinary nature should be directed to the Network Science and Engineering (NetSE) cross-cutting program (click here for solicitation - NSF 09-558). For example, projects that take a broad social, technical and economic perspective focusing on how networks are optimally designed to meet social, economic or legal challenges should be directed to the NetSE program.
For more information on the types of projects supported by the NeTS program, please visit the following web sitehttp://www.nsf.gov/cise/cns/nets_pgm.jsp.
Algorithmic Foundations [CORE] (AF) The Algorithmic Foundations program supports research characterized by algorithmic thinking accompanied by rigorous analysis. Research on algorithms for problems that are central to computer science, as well as new techniques for the rigorous mathematical analysis of such algorithms, are solicited. Moreover, there is an interest in theoretical work to bound the intrinsic difficulty of problems to determine the measures of complexity in formal models of computation, classical or new. The goal is to understand the fundamental limits of resource-bounded computation and to obtain optimal solutions within those limits. Specifically, the time and space complexity of finding exact and approximate solutions in deterministic and randomized models of computation are the central concern of the program. Resources other than time and space, such as communication, heat, power, etc., are also of interest. In addition to the traditional, sequential computing paradigm, research on models of computing such as, parallel and distributed models are welcomed. Such research includes optimizations across complex processor/memory hierarchies. Quantum computing, error correction, and techniques for dealing with decoherence are of interest.. The program also supports rigorous work in experimental algorithmics in all of these models that relies on hypothesis formulation, experiment design, observation, modeling, and prediction in arriving at an understanding of algorithm behavior.
The program supports research in algorithms needed in other areas both within and outside computer science. Algorithmic research in databases, networks, communications, operating systems, languages and compilers and machine abstractions. New techniques for the design and analysis of algorithms in areas such as cryptography, computational geometry, computational biology, numerical, symbolic, algebraic, and scientific computing are appropriate for the program. In computational geometry, research can range from theoretical problems to algorithms for applications that arise in computational biology and computer graphics. Numerical methods include recent algorithmic innovations such as smoothed analysis and symbolic methods include symbolic constraint satisfaction problems. Hybrid numeric-symbolic-algebraic methods in support of multi-scale, multi-grid methods and computation on peta-scale machines are also welcome. An emerging area of interest lies at the interface of computer science and economics. This program supports research on computing economic equilibria, mechanism design, graphical economic models and other topics in computational game theory and economics. Relevance to the application areas is important and collaborations with researchers in these areas are encouraged. However, research funded by this program must advance the study of algorithms.
More information on topics of interest within the program is available at:
The program supports basic research in wireless communications, information theory and coding, and networking. Included in the CIF research program is the reliable transmission of information, in both analog and digital form, in the presence of a variety of channel impairments (noise, multipath, interference, etc.). A number of channel architectures are of interest, including multiple-input multiple-output (MIMO) channels, feedback channels, optical channels, quantum channels, and biological channels. CIF has a strong interest in the theoretical performance limits for various communication systems architectures and in the presence of various channel impairments. Also of interest are performance metrics and tradeoffs, such as error probability and latency tradeoffs, resulting with coding/decoding algorithms, diversity techniques, and other types of signal processing.
The CIF program also supports fundamental research in networking including network information theory, network coding, cross-layer research at the lower layers, as well as foundational research at higher layers. Also of interest are research issues that lie at the intersections of communications and information theory, signal processing, and networking. Examples include the impact of physical-layer performance on the higher network layers; sensor networks including applications to environmental monitoring, civil infrastructure monitoring, data communications system monitoring, and power grid monitoring; and network tomography, which involves detecting and classifying spatially distributed anomalies within complex large-scale systems from multiple monitoring (sensor) sites.
In addition to the contemporary signal processing topics that have enabled the IT revolution, there is growing interest within the program in new paradigms that enlarge the scope of signal and information processing from the domain of the linear to the realm of the nonlinear - from linear algebra to algebra, from Euclidean to curved spaces, from uniform to highly non-uniform time and space sampling, to signal processing on graphs. Research that will develop efficient power aware and hardware-friendly algorithms and research on signal/information processing algorithms for the new network science of distributed, decentralized, and cooperative algorithms that avoid global communications is encouraged. The exploration of new approaches to manage massive datasets, such as compressive sampling/sensing, also promises advances in the field.
This program is particularly interested in the application of signal/information processing in complex systems. Some examples of exciting applications are monitoring the Nation's critical infrastructures, signal processing in biological systems, and biomedical signal and image processing. These and other emerging application domains pose new constraints and challenges, leading to the reexamination of old questions and assumptions.
More information on topics of interest within this program is available at: http://www.nsf.gov/cise/ccf/cif_pgm09.jsp
CDI seeks ambitious, transformative, multidisciplinary research proposals within or across the following three thematic areas:
With an emphasis on bold multidisciplinary activities that, through computational thinking, promise radical, paradigm-changing research findings, CDI promotes transformative research within NSF. Accordingly, investigators are encouraged to come together in the development of far-reaching, high-risk science and engineering research and education agendas that capitalize on innovations in, and/or innovative use of, computational thinking. Research and education efforts around the world are beginning to address various aspects of the CDI themes, and CDI projects are expected to build upon productive intellectual partnerships involving investigators from academe, industry and/or other types of organizations, including international entities, that advance CDI objectives within the rapidly evolving global context.
Congruent with the three thematic areas, CDI projects will enable transformative discovery to identify patterns and structures in massive datasets; exploit computation as a means of achieving deeper understanding in the natural and social sciences and engineering; abstract, model, simulate and predict complex stochastic or chaotic systems; explore and model nature’s interactions, connections, complex relations, and interdependencies, scaling from sub-particles to galactic, from subcellular to biosphere, and from the individual to the societal; train future generations of scientists and engineers to enhance and use cyber resources; and facilitate creative, cyber-enabled boundary-crossing collaborations, including those with industrial and international dimensions, to advance the frontiers of science and engineering and broaden participation in STEM fields.
The FY 2008 competition will include three emphasis areas (Agents of Change; Dynamics of Human Behavior; and Decision Making, Risk and Uncertainty). HSD encourages projects investigating complexity and systems thinking, with a goal of revealing the emergent properties of dynamic systems. HSD also encourages projects identifying human drivers of environmental change and exploring the consequences of environmental change on humans. Such research is central in equipping us to handle the most pressing environmental problems for our nation and the world.
HCC research targets diverse computing platforms such as traditional computers, handheld and mobile devices, robots, and wearable computers, at scales ranging from an individual device with a single user to large, evolving, heterogeneous socio-technical systems that are emerging from the increasingly pervasive availability of networking technologies. Environments of interest range from physical interaction with a single device to systems in which places and people, both physical and virtual, merge. As all electronic communications media become digital and interconnected, computing is also playing a central role in how humans communicate, work, learn, and play, dramatically transcending traditional geographical and cultural boundaries. HCC research explores and improves our understanding of new human-computer and human-human interactions, collaboration, and competition, developing systems that are aware of their social surroundings and of the conceptualizations, values, preferences, abilities, special needs, and diverse ranges of capability of the people that use them. HCC researchers and educators explore systems that interact with people using various and possibly multiple modalities such as innovative computer graphics, and haptic, audio, and brain-machine interfaces. HCC research outcomes are expected to transform the human-computer interaction experience, so that the computer is no longer a distraction or worse yet an obstacle, but rather a device or environment that empowers the user at work, in school, at home and at play, and that facilitates natural and productive human-computing integration.
The HCC program encourages research on how humans, in various roles and domains, perceive computing artifacts as they design and use them, and on the wider social implications of those artifacts. HCC supports social and behavioral scientists as well as computer and information scientists whose research contributes to the design and understanding of novel computing technologies and systems.
More information on topics of interest to the HCC program is available at: http://www.nsf.gov/cise/iis/hcc_pgm.jsp
The Information Integration and Informatics (III) program focuses on the processes and technologies involved in creating, managing, visualizing, and understanding diverse digital content in circumstances ranging from individuals through groups, organizations, and societies, and from individual devices to globally-distributed systems. Further, data are only part of a "knowledge life cycle" that progresses from data through knowledge and insight and, ultimately, to action. III funds innovative information technology research that can transform all stages of the knowledge life cycle.
III-funded projects are expected to lead to advances that are driven by specific information-technology challenges. Projects directed mainly at data-collection building and use, that apply existing data technologies to (perhaps) novel data sets, or that propose other activities with limited computing and information technology research potential are not appropriate for this program. III-supported activities can range from theoretical investigations to projects grounded in multi-disciplinary collaborations where data are central to the III-area research. In the case of multi-disciplinary projects proposers should explain the utility of the proposed work to the application domain and demonstrate expertise in that domain among the project participants. Regardless of research modality, proposals should make clear what computing and information technology challenges are being addressed and how the effectiveness of the work will be assessed.
More information on topics of interest to the III program is available at: http://www.nsf.gov/cise/iis/iii_pgm.jsp
Researchers across all areas of RI are addressing progressively richer environments, larger-scale data, and more sophisticated computational and statistical approaches, looking to nature in many cases to model cognitive and computational processes. Interactions across traditional disciplines are also of increasing importance. For example, speech and dialogue research seeks to understand the cognitive psychological underpinnings of conversation that contribute to the robustness of human speech perception and intention understanding. Computer vision is exploring approaches developed in language processing to represent the semantic information in images and video in ways useful for mining, navigation, and robotic interaction, and working with ideas developed in computer graphics and physics-based modeling to understand and depict collections of images. A cognitive architecture may bridge sophisticated planning and problem solving modules with perception and action modules, perhaps accounting for certain human or animal behaviors. Robotic systems need to understand and interact with humans in unfamiliar and unstructured environments. Computational understanding of neurons, networks, and the brain increasingly draws on computer vision, robotics, and machine learning, and provides insights into the coding, representations, and learning underlying intelligent behavior in nature.
These examples are meant to convey the general goals of RI, not to limit its scope. The program supports projects that will advance the frontiers of all RI research areas, as well as those that integrate different aspects of these fields.
More information on topics of interest to the RI program is available at: http://www.nsf.gov/cise/iis/ri_pgm.jsp
Investments in the MSPA-MCS program aim to deepen support of collaborative research in fundamental mathematics and statistics, and computer science with a focus primarily on mathematical and statistical challenges posed by large data sets, managing and modeling uncertainty, and modeling complex nonlinear systems.