Guest Editorial: Special Section on Mission-Oriented Sensor Networks

SENSOR Networks represent a new frontier in technology that promises to push traditional computation beyond the digital abstractions of cyberspace to interact with the real world in human timeframes. Miniature computational devices, often embedded in mobile wireless platforms, interact directly with the physical world, cognizant of a common mission, spanning time and space to monitor changes in the operational environment, and collaborating to actuate distributed tasks in dynamic and uncertain environments. While once the fascinating stuff of science fiction, sensor networks are rapidly becoming the reality that captivates the imagination of researchers and practitioners to enable inexpensive devices to act as numerous eyes and ears of soldiers in surveying a hostile battlefield from a safe distance or to track bio/chemical plumes in the environment for homeland security. Mobile robots with embedded sensor systems explore the surface of Mars and integrated systems of undersea robots are being designed to develop high fidelity nowcasts and forecasts of the ocean through time-space coordinated sampling or to hunt for mines or handle hazardous materials. In general, the next phase of automation calls on networks of sensors to take on the dull, dirty, and dangerous functions of human interest, and to accomplish them with the perception and adaptation of humans and in collaboration with humans. Sensors of physical phenomena with integrated servomechanisms have been commonplace throughout the latter half of the 20th century, controlling thermostats and valves, monitoring flow or adapting to changes in pressure or stress, and providing alarms for fire or flooding. They have been expected to perform these and many other localized isolated tasks with precision and reliability. The distinction of present day demands on sensor networks is in the comprehensive perception of locally sensed changes in the physics of the environment and adaptive time-space coordinated activity of individual servo-mechanisms in support of a common mission. This special section deals with recent advances in the study of Sensor Networks as interacting autonomous mobile sensor nodes. The objective is to address the engineering design issues for achieving dependable performance through dynamic distributed collaboration of many inexpensive, low reliability sensors with limited sensing and communication ranges. Advances in integrated wireless communications, fast servo-controlled sensors/actuators, and micro and nano technologies have together enabled inexpensive devices, often on mobile platforms, to be air dropped or deployed in unknown or dynamic environments. These devices are expected to self-organize and form ad hoc networks to continuously survey a battlefield for enemy targets over long periods of time, conserving precious resources unless some enemy activity is detected. Upon detection, the nodes form dynamic clusters to localize and track enemy targets. Traditional programming, computation, communication, and control techniques must all advance to comprehend the distributed dynamics of the environment and actuate a timely response. Research papers in this section address design trade offs for situation awareness, adaptive and dependable infrastructure, and coordinated inference in mission-oriented mobile sensor networks. The first paper by Bergamo, Asgari, Wang, Maniezzo, Yip, Hudson, Yao, and Estrin solves the far field acoustic source localization problem through beamforming. Waveforms originating at a given source are used by a set of spatially separated acoustic sensors to localize the source through time synchronized estimates of direction of arrival. Experiments in free space and reverberant scenarios demonstrate the power of very low cost devices to achieve sophisticated space-time operation in real-time. The next paper in this section uses distributed annealing algorithms to govern the purposeful motion of nodes. Unlike most ad hoc wireless networks (e.g., cellular networks) that must adapt to the mobility needs of their users, mission-oriented sensor networks incorporate purposeful mobility. Adaptation to environmental and operational disturbances requires resource bounded optimal response. The severe power and processing constraints on sensor network operations call for energy-aware task execution and the pragmatic use of mobility to ensure that mission goals are accomplished. Sensitivity to mobility-induced location errors is evaluated by Son, Helmy, and Krishnamachari. They provide empirical algorithms to mitigate the resulting problems. Again, this addresses the pragmatic use of mobility to reliably accomplish mission objectives. Continuous self-organization of distributed sensors may be needed for area coverage. Ravelomanana, in his paper, formulates fundamental characteristics of design of ad hoc networks that analyze critical transmitting/sensing ranges for connectivity and coverage in three-dimensionsal networks. Chen, Hou, and Sha develop dynamic clustering algorithms for target tracking. The large number of nodes deployed precludes manual configuration in an operational field or in buildings and homes. Cerpa and Estrin develop self-configuring algorithms for network topologies. Ma and Ayler address system lifetime optimization for in-home networks through an optimal architecture and a resource bounded protocol. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 3, NO. 3, JULY-SEPTEMBER 2004 209