In this paper, a summary of works in creating truly three-dimensional structures for high-frequency applications will be presented using an additive manufacturing method, laser-based layer-by-layer polymer stereolithography. This polymer stereolithography is shown to have very good fabrication tolerances, which are necessary for making miniature RF components and narrow-band filters. The prototype components using this stereolithography include high-Q resonators, low-loss cavity filters and evanescent-mode filters, antennas, and miniature ion traps for mass spectrometry.

The prospects for and the state of the art of adaptable RF hardware are reviewed, focusing primarily on the traditional frequency planning bottleneck, the filtering stages. First, a case is made that even banded systems can be greatly impacted by a modest amount of tuning. This is done by showing the results of a traditional fixed system in an unlicensed band upgraded with a programmable front-end filter. Next, a system built specifically for wideband tuning is shown that enables band selection across the 20-MHz-6-GHz-band. Cooperative operation of multiple colocated nodes is enabled by high-quality pre-LNA filtering across the bands of operation. Future capabilities of adaptable systems are shown by reviewing the state of the art of adaptable systems, heading toward a field-programmable filter array in which a sea of resonators are dynamically interconnected to create a transfer function on demand. Additionally, a novel synthesis approach is highlighted in which multiple filters can cooperate gracefully without crossover issues between the bands. This approach allows for a vast number of filter states by turning on and off passbands without affecting the adjacent bands. The advancements in adaptable hardware will enable new classes of RF systems which much more efficiently utilize the spectrum.

As sensor networks operate over long periods of deployment in difficult to reach places, their requirements may change or new code may need to be uploaded to them. The current state-of-the-art protocols (Deluge and MNP) for network reprogramming perform the code dissemination in a multihop manner using a three-way handshake where metadata is exchanged prior to code exchange to suppress redundant transmissions. The code image is also pipelined through the network at the granularity of pages. In this article we propose a protocol called Freshet for optimizing the energy for code upload and speeding up the dissemination if multiple sources of code are available. The energy optimization is achieved by equipping each node with limited nonlocal topology information which it uses to determine the time when it can go to sleep since code is not being distributed in its vicinity. The protocol to handle multiple sources provides a loose coupling of nodes to a source and disseminates code in waves each originating at a source with a mechanism to handle collisions when the waves meet. The protocol's performance with respect to reliability, delay, and energy consumed is demonstrated through analysis, simulation, and implementation on the Berkeley mote platform.

With the development of location aware sensor applications, location determination has become an increasingly important middleware technology. Numerous current technologies for location determination of sensor nodes use the received signal strength from sensor nodes using omnidirectional antennas. However, an increasing number of sensor systems are now deploying directional antennas due to their advantages like energy conservation and better bandwidth utilization. In this paper, we present techniques for location determination in a sensor network with directional antennas under different kinds of deployment of the nodes. We show how the location estimation problem can be solved by measuring the received signal strength from just one or two anchors in a 2D plane with directional antennas. We implement our technique using Berkeley MICA2 sensor motes and show that it is up to three times more accurate than triangulation using omnidirectional antennas. We also perform Matlab simulations that show the accuracy of location determination with increasing node density