Two grants focus on biologically inspired wireless networking

PI: Chien-Chung Shen (CIS) Co-PI: Lou Rossi (Math)

Advances in information technology have resulted in the emergence of new environments such as mobile ad hoc networks (MANETs), wireless sensor and actor networks (WSANs), and large-scale Grid and P2P networks, which in essence are constituted by networked autonomous nodes. Although these environments present enormous potential to facilitate new applications and services, they also pose difficult design challenges---these environments are intrinsically dynamic, unreliable, and large scale. Traditional design approaches that assume that the system is composed of reliable components, and/or that the system is of relatively small scale are not applicable in such environments. In addition, approaches that are based on central and/or explicit control over the system as a whole either introduce a single point of failure or make the system not adaptable; such approaches are not applicable in such environments either. It is therefore critical to explore new design paradigms and approaches that do not suffer from these defects.

The phenomenon of self-organization is pervasive in nature, where biological organisms efficiently self-organize (a large number of) unreliable and dynamically changing components (such as cells and individuals of a swarm) to develop a wide diversity of functions. In addition, these biological organisms enjoy the desirable properties of robustness to the failure of individual components, adaptivity to changing conditions, and the lack of reliance on explicit central coordination. In this proposal, we seek inspiration from the study of swarm behavior in nature, such as slime mold, to design and analyze robust, autonomic networking protocols for the environments of MANETs, WSANs, and large-scale Grid and P2P networks.

National Science Foundation: Emerging Models and Technology program:
Biologically Inspired Autonomic Networking Protocols: Analysis and Implementation

PI: Chien-Chung Shen (CIS) Co-PI: Lou Rossi (Math)

The proposal aims to develop autonomic networking protocols based upon bottom-up modeling of simple, interacting units. The advantage to this approach is that one can reduce the dimensionality of the complex system to a small set of primitive functions and parameters governing the simple units that comprise the system. In particular, we seek to model the behavior of slime mold physarum polycephalum to design autonomic networking protocols for WSANs.

This proposal addresses an inverse problem and aims to develop autonomic networking protocols based upon bottom-up modeling of simple, interacting units. The advantage to this approach is that one can reduce the dimensionality of the complex system to a small set of primitive functions and parameters governing the simple units that comprise the system. In particular, we seek to model the behavior of slime mold physarum plasmodium to design autonomic networking protocols for wireless sensor and actor networks. When several food sources are presented to a starved slime mold, the slime mold will attempt to reach all food sources. The initially flat and unorganized mold will move the majority of its mass to the various food sources, leaving each section of its body joined only by thin tubes which carry nutrients and other chemicals. Although the biological mechanisms used by slime molds are not fully understood, these simple creatures are remarkably able to form Steiner tree like structures connecting multiple food sources. Often, the tubes of a slime mold will be arranged in a geometry that balances efficiency (keeping the total tube length short) and robustness (having multiple paths in case of a tube being severed). Slime molds may operate using the flow of nutrients and other chemicals to reinforce beneficial tubes, while responding to internal hydrostatic pressure to shorten or remove other tubes. Additionally, nutrient flow likely follows gradients from areas rich in nutrients to areas in need of nutrients. The problems faced by slime molds are similar to those which exist in wireless sensor and actor networks.

Army Small Business Innovative Research (SBIR) Phase I: Bio-Inspired Approaches to Secure Scalable Networking" PI: Scalable Network Technologies, Inc. Co-PIs: Rossi (Math) and Shen (CIS)

We will adapt the biological metaphor of swarm intelligence to design an adaptive networking architecture and a set of energy-efficient, robust, secure, and scalable networking protocols for tactical wireless communication networks. We also propose to mathematically model and analyze the behavior and performance of these protocols.

In this SBIR effort, we will further extend our prior NSF results to address tactical wireless communication networks specific issues. The specific Phase I technical objectives include

. We will design a practically useful and theoretically well founded Swarm Intelligence based networking architecture, which uses 'modularity' as a means to simplify the construction of protocols for tactical wireless communication networks.

. We will design a suite of networking protocols, including unicast routing, multicast routing, and data aggregation, for MANET and WSN. We will augment these protocols with energy-efficiency, security, and/or reliability capabilities. We will evaluate (via extensive QualNet simulation) the performance of the designed protocols/ capabilities in terms of scalability, energy efficiency, latency, control overhead, and route reconfiguration time using tactical scenarios of hundreds of nodes. In particular, we will conduct a feasibility study of adaptability of these protocols with changing networking goals, and evaluate the feasibility of protocol implementation in a real-time, distributed, and scalable manner.