Relative bearing between robots is important in applications like pursuit-evasion [11] and SLAM [7]. This is also true in sensor networks, where the bearing of one sensor node relative to another has been used for localization [5], [18], [20] and topology control [14], [21], [6]. Most systems use dedicated sensors like an IR array or a camera to obtain relative bearing. We study the use of radio signal strength (RSS) in commodity radios for obtaining relative bearing. We show that by using the robot's mobility, commodity radios can be used to obtain coarse relative bearing. This measurement can be used for a suite of applications that do not require very precise bearing measurement. We analyze signal strength variations in simulation and experiment and also show an algorithm that uses this coarse bearing computation in a practical setting.

Automakers are trying to make vehicles more intelligent and safe by embedding processors which can be used to implement ldquoby-wirerdquo applications for taking smart decisions on the road or assisting the driver in doing the same. Given this proliferation, there is a need to minimize the computing power required without affecting the performance and safety of the applications. The latter is especially important since these by-wire applications are distributed and real-time in nature and involve deadline bound computations on critical data gathered from the environment. These applications have stringent requirements on the freshness of data items and completion time of the tasks. Our work studies one such safety-related automotive application namely, automatic merge control (AMC) which ensures safe vehicle maneuver in the region where two or more roads intersect.As our contributions, we (i) propose two merge algorithms for amc: head of the lane (HoL) and all feasible sequences (AFS) (ii) demonstrate how DSRC-based wireless communication protocol can be leveraged for the development of AMC (iii) present a real-time approach towards designing AMC by integrating mode-change and real-time repository concepts for reducing the processing power requirements and (iv) provide a scheduling strategy to meet AMC taskspsila timing requirements. Simulations and implementation on robotic vehicular platforms demonstrate the advantages of using our approach for constructing merge-by-wire systems.

We present a tool, PerfCenter, that takes as input the deployment, configuration, message flow and workload details of the hardware and software servers in an application hosting center, and predicts the performance of the applications. We allow for a hierarchical specification of the data center, where software is deployed on machines, machines consist of hardware devices and are deployed on LANs. We also explicitly model network links between LANs and model the contention at those links due to messages exchanged between servers. While tools and methodologies for such analysis have been proposed earlier, our approach allows for the most natural specification of a "data center" architecture, and is best suited for aiding in design decisions regarding deployment and configuration of software on various hardware architecture scenarios. The tool takes this high level input and generates the underlying queueing network, which is then solved analytically. Since we allow for synchronous method calls, and model contention at software as well as hardware resources, the generated queueing network is solved using approximate methods. We validate the solution against results obtained from a measurement testbed, and found that the predicted values were reasonably accurate.