Biology-Inspired Approach for Communal Behavior in Massively Deployed Sensor Networks

Research in wireless sensor networks has accelerated rapidly in recent years. The promise of ubiquitous control of the physical environment opens the way for new applications that will redefine the way we live and work. Due to the small size and low cost of sensor devices, visionaries promise smart systems enabled by deployment of massive numbers of sensors working in concert. To date, most of the research effort has concentrated on forming ad hoc networks under centralized control, which is not scalable to massive deployments. This thesis proposes an alternative approach based on models inspired by biological systems and reports significant results based on this new approach. This perspective views sensor devices as autonomous organisms in a community interacting as part of an ecosystem rather than as nodes in a computing network. The networks that result from this design make local decisions based on local information in order for the network to achieve global goals, thus we must engineer for emergent behavior in wireless sensor networks. First we implemented a simulator based on cellular automata to be used in algorithm development and assessment. Then we developed efficient algorithms to exploit emergent behavior for finding the average of distributed values, synchronizing distributed clocks, and conducting distributed binary voting. These algorithms are shown to be convergent and efficient by analysis and simulation. Finally, an extension of this perspective is used and demonstrated to provide significant progress on the noise abatement problem for jet aircraft. Using local information and actions, optimal impedance values for an acoustic liner are determined in situ providing the basis for an adaptive noise abatement system that provides superior noise reduction compared with current technology and previous research efforts

The Environment for Application Software Integration and Execution (EASIE) version 1.0. Volume 4: System installation and maintenance guide

The Environment for Application Software Integration and Execution (EASIE) provides both a methodology and a set of software utility programs to ease the task of coordinating engineering design and analysis codes. This document provides necessary information for installing the EASIE software on a host computer system. The target host is a DEX VAX running VMS version 4; host dependencies are noted when appropriate. Relevant directories and individual files are identified, and compile/load/execute sequences are specified. In the case of the data management utilities, database management system (DBMS) specific features are described in an effort to assist the maintenance programmer in converting to a new DBMS. The document also describes a sample EASIE program directory structure to guide the program implementer in establishing his/her application dependent environment

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system

Antifragile Systems: An Enabler for System Engineering of Elegant Systems

No abstract availabl

The Environment for Application Software Integration and Execution (EASIE), version 1.0. Volume 2: Program integration guide

The Environment for Application Software Integration and Execution, EASIE, provides a methodology and a set of software utility programs to ease the task of coordinating engineering design and analysis codes. EASIE was designed to meet the needs of conceptual design engineers that face the task of integrating many stand-alone engineering analysis programs. Using EASIE, programs are integrated through a relational data base management system. In volume 2, the use of a SYSTEM LIBRARY PROCESSOR is used to construct a DATA DICTIONARY describing all relations defined in the data base, and a TEMPLATE LIBRARY. A TEMPLATE is a description of all subsets of relations (including conditional selection criteria and sorting specifications) to be accessed as input or output for a given application. Together, these form the SYSTEM LIBRARY which is used to automatically produce the data base schema, FORTRAN subroutines to retrieve/store data from/to the data base, and instructions to a generic REVIEWER program providing review/modification of data for a given template. Automation of these functions eliminates much of the tedious, error prone work required by the usual approach to data base integration

Emergent Adaptive Noise Reduction from Communal Cooperation of Sensor Grid

In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault toleran

Biology Inspired Approach for Communal Behavior in Sensor Networks

Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control

Method of Adjusting Acoustic Impedances for Impedance-Tunable Acoustic Segments

A method is provided for making localized decisions and taking localized actions to achieve a global solution. In an embodiment of the present invention, acoustic impedances for impedance-tunable acoustic segments are adjusted. A first acoustic segment through an N-th acoustic segment are defined. To start the process, the first acoustic segment is designated as a leader and a noise-reducing impedance is determined therefor. This is accomplished using (i) one or more metrics associated with the acoustic wave at the leader, and (ii) the metric(s) associated with the acoustic wave at the N-th acoustic segment. The leader, the N-th acoustic segment, and each of the acoustic segments exclusive of the leader and the N-th acoustic segment, are tuned to the noise-reducing impedance. The current leader is then excluded from subsequent processing steps. The designation of leader is then given one of the remaining acoustic segments, and the process is repeated for each of the acoustic segments through an (N-1)-th one of the acoustic segments

Communal Cooperation in Sensor Networks for Situation Management

Situation management is a rapidly evolving science where managed sources are processed as realtime streams of events and fused in a way that maximizes comprehension, thus enabling better decisions for action. Sensor networks provide a new technology that promises ubiquitous input and action throughout an environment, which can substantially improve information available to the process. Here we describe a NASA program that requires improvements in sensor networks and situation management. We present an approach for massively deployed sensor networks that does not rely on centralized control but is founded in lessons learned from the way biological ecosystems are organized. In this approach, fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that achieve globally-meaningful results. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems

Biology-inspired Architecture for Situation Management

Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft