White Paper: Engineering Emergent Protocols
Abstract:
Two approaches are proposed for revolutionary gains in MEMS device communication. The first is to view all network devices as computational or active devices. Computation can take many forms. The amount of computation may vary, but every device has some type of computation, either programmed or ambient. Use of computation in an optimal manner is the same challenge faced by active networks. Thus, advances in active networks and networks of MEMS devices are mutually beneficial. The second approach is to optimize networks of MEMS devices via exploiting emergence. Understanding emergence requires understanding complexity; this relationship is explored relative to networking. The results lead toward emergence that can be precisely engineered to achieve desired characteristics. The purpose of the research proposed in this white paper is to understand and develop a theory for basic emergent protocols using computer science formalisms and simulation techniques for higher order emergent protocols. Emergence is a concept or property in the macroscopic behavior of a system that is not contained within the microscopic description (Figure 1). It is a natural phenomenon in which structured collective behavior appears from the interaction of simple subsystems, such as MEMS devices. The research proposed in this white paper will integrate emergent protocols in network service protocols to create a new class of featherweight, survivable protocols called “emergent protocols. ” The challenge will be to identify emergent protocols that arise from the operation of the device and its interaction with other MEMS devices, especially in an environment of suboptimal connectivity where messages can be lost and the system must operate with only a partial knowledge of its environment. By understanding the emergence of new behaviors in such a dynamic environment, the proposed research will induce emergent protocols that imple-Non-Locality Primitive actions at lower level cause instantaneous information transfer at macroscopic level
Citations
| 13 | Complexity, Entropy and the Physics of Information – Zurek - 1990 |
| 10 | Minimum Message Length and Kolmogorov – Wallace, Dowe - 1999 |
| 1 | Adaptive Model Prediction Using Time – Tinker, Agra - 1990 |
