| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 20, 2013 |
| Latest Amendment Date: | August 20, 2013 |
| Award Number: | 1319684 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Darleen Fisher
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2013 |
| End Date: | October 31, 2013 (Estimated) |
| Total Intended Award Amount: | $250,000.00 |
| Total Awarded Amount to Date: | $250,000.00 |
| Funds Obligated to Date: |
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| Recipient Sponsored Research Office: |
3451 WALNUT ST STE 440A PHILADELPHIA PA US 19104-6205 (215)898-7293 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
PA US 19104-6205 |
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Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| NSF Program(s): | Networking Technology and Syst |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Network protocol stacks typically follow a multi-layer hierarchical architecture. What determines the required number of layers, or the number of protocols at each layer? The space of applications, services and user expectations (at the top layer) and the space of elementary functions (at the bottom layer) are constantly evolving -- how does this dynamic environment affect the organization of layered protocol stacks? What determines the evolvability of a protocol stack in the presence of changes? How does evolvability relate to other important system-wide properties such as robustness (the ability to deal with unexpected change), optimality and modularity? These are some of the high-level questions that this research project focuses on.
Intellectual Merit: This research seeks to reexamine the fundamentals of protocols design and investigate the role of and dependencies between several central concepts: layering, modularity, complexity, robustness, optimality. The central theme in this research, however, is evolution -- networking architectures are not designed to work in a static environment. Applications, services, user expectations, communication and computing technologies, as well as the underlying economics, are all in a constant state of flux.
Rather than rely on a single modeling framework, this research starts with two preliminary models, referred to as Stratum and Lexis. The two models share some features but are also significantly different and complementary. They both capture the time-varying character of a layered design process aiming to support a dynamic set of applications from an underlying set of (also dynamic) elementary functions. Stratum is more constrained than Lexis as it considers, first, a specific ordering for the available building blocks, and second, an endogenous model for the ``death rate'' of existing applications. Lexis, on the other hand, is more general and more abstract, and captures how a time-varying set of regular expressions can be constructed hierarchically from a time-varying alphabet, re-using simpler regular expressions as much as possible.
The Stratum and Lexis models are initial steps towards developing a base understanding of what factors influence the evolvability and sustainability of protocols. With this base in place, further domain-specific insight can be developed and yield targeted guidelines for the design of future network protocols.
Broader Impact: There are currently four large NSF-funded Future Internet Architecture (FIA) projects that pursue a ``clean-slate'' design approach for a future Internet that is more robust, secure, evolvable, etc. A goal of this research is to both inform and learn from the efforts of the four FIA projects.
The broader impact of this project also includes the release of two extensible simulators (corresponding to Stratum and Lexis) that will allow students and instructors to experiment with how network architectures evolve in dynamic environments and under optimization objectives and constraints. No such tools are available today.
Additionally, this project has a significant inter-disciplinary component in both its ?inputs and outputs.? Specifically, much of the prior work behind this research (inputs) has originated in economics, physics and evolutionary biology. Conversely, the project's results (outputs) are likely to be relevant to other disciplines such as software engineering, smart manufacturing and the science of organizations.
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