Abstract-Design of current sensor network platforms has favored low power operation at the cost of communication throughput or range, which severely limits support for real-time monitoring applications with high throughput requirements. This letter presents the design of the versatile Opal platform that couples a Cortex M3 MCU with two IEEE 802.15.4 radios for supporting sensing applications with high transfer rates without sacrificing communication range. We present experiments that evaluate Opal's throughput and range when operating with one or two radios, and we compare these results with an Iris-based node and TelosB nodes. We introduce the spatial energy cost metric that measures the energy to transfer one bit of information in a unit area for comparing the performance of the platforms. The results show that Opal operating with dual radios increases the throughput compared to single radio platforms with the same data-rate by a factor of 3.7, without sacrificing communication range. Opal operating with one radio can deliver a 460% increase in throughput over other single radio nodes at reduced range. We also analyze the implications of Opal's design for multi-hop communication, showing that the dual radio architecture removes the bandwidth bottleneck in multi-hop communications that is inherent to single radio platforms. I. INTRODUCTIONWireless Sensor Network (WSN) applications have evolved beyond the vision of smart dust and are now also being deployed to gather acoustic and visual data with a high demand for communication throughput. Equipment and deployment costs have proven to be a limiting factor for high spatial density deployments [1], highlighting the benefits of longer range communication. Sensor network users have also realized the higher-than-expected node cost and are moving towards deployments with more widely spaced nodes at the expense of data granularity.Energy-efficiency has so far been a dominant design target in WSN platforms, due to the limited battery capacity imposed by the device form factor. However, recent advances in energy harvesting, such as solar, have shown networks that can operate for years [1]. While energy remains a key consideration, the focus on energy-efficiency has so far sidelined other design considerations in WSNs, such as communication throughput and range.This letter introduces the Opal platform as a high throughput sensing module that delivers comparable energy efficiency to existing platforms. Opal includes two onboard 802.15.4 radios operating in the 900 MHz and 2.4 GHz bands to provide communication diversity [2] and an aggregate transfer rate of 3 Mbps. It embeds a 96 MHz Cortex SAM3U processor with dynamic core frequency scaling, a feature that can be used to fine-tune processing speed with the higher communication rates while minimizing energy consumption.
Energy management is a critical concern in wireless sensornets. Despite its importance, sensor network operating systems today provide minimal energy management support, requiring applications to explicitly manage system power states. To address this problem, we present ICEM, a device driver architecture that enables simple, energy efficient wireless sensornet applications. The key insight behind ICEM is that the most valuable information an application can give the OS for energy management is its concurrency. Using ICEM, a low-rate sensing application requires only a single line of energy management code and has an efficiency within 1.6% of a hand-tuned implementation. ICEM's effectiveness questions the assumption that sensornet applications must be responsible for all power management and sensornets cannot have a standardized OS with a simple API.
Many wireless sensor networks must sustain long lifetimes on limited energy resources. Two major approaches, transmission power control and sleep scheduling, have been proposed to reduce the radio power consumption in the transmission state and the idle state, respectively. In this paper, we first review existing transmission power control and sleep scheduling approaches and then describe a Unified Radio Power Management framework for the design and implementation of holistic radio power management solutions in wireless sensor networks. It has two key components: (1) a novel optimization approach called Minimum Power Configuration that minimizes the aggregate radio power consumption of all ratio states and (2) a Unified Power Management Architecture (UPMA) that aims to support the flexible cross-layer integration of different power management strategies. A novel feature of UPMA is that it enables cross-layer coordination and joint optimization of different power management strategies that exist at multiple network layers. additional energy at run time, the amount of energy available remains scarce. Therefore, power management is crucial for making WSNs viable in many realworld applications.Radio is a major source of energy consumption in WSNs. Table I shows the power characteristics of two representative radio interfaces widely used in existing wireless sensor platforms. Two observations can be drawn from this table. First, the transmission power consumption has a wide tunable range, which offers opportunities for significant energy saving. Second, the power consumption in sleep state is several orders of
We believe datacenters can benefit from more focus on per-node efficiency, performance, and predictability, versus the more common focus so far on scalability to a large number of nodes. Improving per-node efficiency decreases costs and fault recovery because fewer nodes are required for the same amount of work. We believe that the use of complex, general-purpose operating systems is a key contributing factor to these inefficiencies.Traditional operating system abstractions are ill-suited for high performance and parallel applications, especially on large-scale SMP and many-core architectures. We propose four key ideas that help to overcome these limitations. These ideas are built on a philosophy of exposing as much information to applications as possible and giving them the tools necessary to take advantage of that information to run more efficiently. In short, high-performance applications need to be able to peer through layers of virtualization in the software stack to optimize their behavior. We explore abstractions based on these ideas and discuss how we build them in the context of a new operating system called Akaros.
A challenge for many wireless sensor networks is to remain operational for long periods of time on a very limited power supply. While many power management protocols have been proposed, a solution does not yet exist that allows them to be seamlessly integrated into the existing systems. In this paper we study the architectural support required to resolve this issue. We propose a framework that separates sleep scheduling from the basic MAC layer functionality and provide a set of unified interfaces between them. This framework enables different sleep scheduling policies to be easily implemented on top of multiple MAC.
Radio power management is of paramount concern in wireless sensor networks that must achieve long lifetimes on scarce amounts of energy. While a multitude of power management protocols have been proposed in the past, the lack of system support for flexibly integrating them with a diverse set of applications and network platforms has made them difficult to use.Instead of proposing yet another power management protocol, this paper focuses on providing link layer support towards realizing a Unified Power Management Architecture (UPMA) for flexible radio power management in wireless sensor networks. In contrast to the monolithic approaches adopted by... Read complete abstract on page 2.Read complete abstract on page 2.Complete Abstract: Complete Abstract:Radio power management is of paramount concern in wireless sensor networks that must achieve long lifetimes on scarce amounts of energy. While a multitude of power management protocols have been proposed in the past, the lack of system support for flexibly integrating them with a diverse set of applications and network platforms has made them difficult to use. Instead of proposing yet another power management protocol, this paper focuses on providing link layer support towards realizing a Unified Power Management Architecture (UPMA) for flexible radio power management in wireless sensor networks. In contrast to the monolithic approaches adopted by existing power management solutions, we provide (1) a set of standard interfaces that allow different power management protocols existing at the link layer to be easily implemented on top of common MAC level functionality, (2) an architectural framework for enabling these protocols to be easily swapped in and out depending on the needs of the applications that require them, and (3) a mechanism for coordinating the existence of multiple applications, each of which may have different requirements for the same underlying power management protocol. We have implemented these features on the Mica2 and Telosb radio stacks in TinyOS-2.0.Microbenchmark results demonstrate that the separation of power management from MAC level functionality incurs a negligible decrease in performance when compared to existing monolithic implementations. Two case studies show that the power management requirements of multiple applications can be easily coordinated, sometimes even resulting in better power savings than any one of them can achieve individually.Abstract: Radio power management is of paramount concern in wireless sensor networks that must achieve long lifetimes on scarce amounts of energy. While a multitude of power management protocols have been proposed in the past, the lack of system support for flexibly integrating them with a diverse set of applications and network platforms has made them difficult to use. Instead of proposing yet another power management protocol, this paper focuses on providing link layer support towards realizing a Unified Power Management Architecture (UPMA) for flexible radio power management in wireless sensor ...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.