A broad range of embedded networked sensing (ENS) applications have appeared for large-scale systems, introducing new requirements leading to new embedded architectures, associated algorithms, and supporting software systems. These new requirements include the need for diverse and complex sensor systems that present demands for energy and computational resources, as well as for broadband communication. To satisfy application demands while maintaining critical support for low-energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. In this article, we described the LEAP design approach, in which the system is able to adaptively select the most energy-efficient hardware components matching an application’s needs. The LEAP platform supports highly dynamic requirements in sensing fidelity, computational load, storage media, and network bandwidth. It focuses on episodic operation of each component and considers the energy dissipation for each platform task by integrating fine-grained energy-dissipation monitoring and sophisticated power-control scheduling for all subsystems, including sensors. In addition to the LEAP platform’s unique hardware capabilities, its software architecture has been designed to provide an easy way to use power management interface and a robust, fault-tolerant operating environment and to enable remote upgrade of all software components. LEAP platform capabilities are demonstrated by example implementations, such as a network protocol design and a light source event detection algorithm. Through the use of a distributed node testbed, we demonstrate that by exploiting high energy-efficiency components and enabling proper on-demand scheduling, the LEAP architecture may meet both sensing performance and energy dissipation objectives for a broad class of applications.

This paper describes a new embedded networked sensor platform architecture that combines hardware and software tools providing detailed, fine-grained real-time energy usage information. We introduce the LEAP2 platform, a qualitative step forward over the previously developed LEAP and other similar platforms. LEAP2 is based on anew low power ASIC system and generally applicable supporting architecture that provides unprecedented capabilities for directly observing energy usage of multiple subsystems in real-time. Real-time observation with microsecond-scale time resolution enables direct accounting of energy dissipation for each computing task as well as for each hardware subsystem. The new hardware architecture is exploited with our new software tools, etop and endoscope. A series of experimental investigations provide high-resolution power information in networking, storage, memory and processing for primary embedded networked sensing applications. Using results obtained in real-time we show that for a large class of wireless sensor network nodes, there exist several interdependencies in energy consumption between different subsystems. Through the use of our measurement tools we demonstrate that by carefully selecting the system operating points, energy savings of over 60% can be achieved while retaining system performance.

Dual-radio, dual-processor nodes are an emerging class of wireless sensor network devices that provide both low-energy operation as well as substantially increased computational performance and communication bandwidth for applications. In such systems, the secondary radio and processor operates with sufficiently low power that it may remain always vigilant, while the main processor and primary, high-bandwidth radio remain off until triggered by the application. By exploiting the high energy efficiency of the main processor and primary radio along with proper usage, net operating energy benefits are enabled for applications. The secondary radio provides a constantly available multi-hop network, while paths in the primary network exist only when required. This paper describes a topology control mechanism for establishing an end-to-end path in a network of dual-radio nodes using the secondary radios as a control channel toselectivelywake up nodes along the required end-to-end path. Using numerical models as well as testbed experimentation, we show that our proposed mechanism provides significant energy savings of more than 60% compared to alternative approaches, and that it incurs only moderately greater application latency.

A broad range of embedded networked sensor (ENS) systems for critical environmental monitoring applications now require complex, high peak power dissipating sensor devices, as well as on-demand high performance computing and high bandwidth communication. Embedded computing demands for these new platforms include support for computationally intensive image and signal processing as well as optimization and statistical computing. To meet these new requirements while maintaining critical support for low energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. The LEAP architecture integrates fine-grained energy dissipation monitoring and sophisticated power control scheduling for all subsystems including sensor subsystems. The LEAP2 platform is a second generation LEAP system with even higher resolution energy monitoring as well as the unique ability to do per process and per application energy profiling via a dedicated high performance ASIC. Our demonstration will highlight this profiling capability through a custom monitoring application named etop.

A broad range of embedded networked sensor (ENS) systems for critical environmental monitoring applications now require complex, high peak power dissipating sensor devices, as well as on-demand high performance computing and high bandwidth communication. Embedded computing demands for these new platforms include support for computationally intensive image and signal processing as well as optimization and statistical computing. To meet these new requirements while maintaining critical support for low energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. The LEAP architecture integrates fine-grained energy dissipation monitoring and sophisticated power control scheduling for all subsystems including sensor subsystems. The LEAP2 platform is a second generation LEAP system with even higher resolution energy monitoring as well as the unique ability to do per process and per application energy profiling via a dedicated high performance ASIC. This poster will demonstrate the hardware platform capabilities as well as the energy-aware software currently available for LEAP2.

This paper presents a robust adaptive type-I hybrid ARQ scheme that can adapt to a slowly-varying wireless channel. The proposed system can improve system throughput substantially compared to a conventional type-I hybrid ARQ scheme. Most previous research on adaptive ARQ has assumed that the return channel used for acknowledgements is error free. This simplifying assumption is often necessary for initial performance evaluation but is unrealistic in practice. In this paper, we extend an existing adaptive ARQ scheme by making it robust to channel errors in both the forward and feedback channels. We also propose a solution to maintain code synchronization in the presence of packet errors and describe an implementation that combines the adaptive ARQ scheme with a SACK protocol that allows bi-directional transmission and piggybacked acknowledgements. In addition we have built a wireless test platform for mobile radio in an attempt to accurately measure the adaptive error control performance not only as a standalone entity, but also as a part of a complete protocol stack.