Most power management protocols are packet-based and optimized for applications with mostly asynchronous (i.e. unexpected) traffic. We present AppSleep, a stream-oriented power management protocol for latency tolerant sensor network applications. For this class of applications, AppSleep demonstrates an over 3/spl times/ lifetime gain over B-MAC and SMAC. AppSleep leverages application characteristics in order to take advantage of periods of high latency tolerance to put the network to sleep for extended periods of time, while still facilitating low latency responses when required. AppSleep also gives applications the flexibility to efficiently and effectively trade latency for energy when desired, and enables energy efficient multi-fragment unicast communication by only keeping the active route awake. We also present Adaptive AppSleep, an application driven addition to AppSleep which supports varying latency requirements while still maximizing energy efficiency. Our evaluation demonstrates that for an overlooked class of applications, stream-oriented power management protocols such as AppSleep outperform packet-based protocols such as B-MAC and S-MAC.
The deployment of large-scale sensor networks in industrial environments presents technical challenges in achieving ease of deployment, flexibility in operation, and overall commercial viability. Sensor deployments are characterized by non-uniform placement of nodes, intermittent node connectivity, and the aggregation and reliable transfer of a large amount of data as networks scale to larger and larger sizes. Operation challenges include efficiently utilizing battery powered nodes, dynamically selecting sample periods and equipment clusters of interest, integrating with existing sensing and analysis infrastructure and easily correlating faults identified by the sensor network back to key factory operations and equipment. Commercial aspects involve returning value to the organization with hardened network nodes and reliable network operation that easily justifies the sensor network deployment and operating costs. We will demonstrate a sensor network in the ultra-pure water facility of an Intel fabrication plant, including details on the fab vibration application, the hardware nodes, and the heterogeneous wireless network.
Sensing technology is a cornerstone for many industrial applications. Manufacturing plants and engineering facilities, such as shipboard engine rooms, require sensors to ensure product quality and efficient and safe operation. We focus on one representative application, preventative equipment maintenance, in which vibration signatures are gathered to predict equipment failure. Based on application requirements and site surveys, we develop a general architecture for this class of industrial applications. This architecture meets the application's data fidelity needs through careful state preservation and over-sampling. We describe the impact of implementing the architecture on two sensing platforms with differing processor and communication capabilities. We present a systematic performance comparison between these platforms in the context of the application. We also describe our experience and lessons learned in two settings: in a semiconductor fabrication plant and onboard an oil tanker in the North Sea. Finally, we establish design guidelines for an ideal platform and architecture for industrial applications. This paper includes several unique contributions: a study of the impact of platform on architecture, a comparison of two deployments in the same application class, and a demonstration of application return on investment.
Most power management protocols are packet-based and optimize for applications with mostly asynchronous (i.e. unexpected) traffic. We present AppSleep, a stream-oriented power management protocol for latency tolerant sensor network applications. For this class of applications, AppSleep demonstrates an over 3x lifetime gain over B-MAC and SMAC. AppSleep leverages application characteristics in order to take advantage of periods of high latency tolerance to put the network to sleep for extended periods of time, while still facilitating low latency responses when required. AppSleep also gives applications the flexibility to efficiently and effectively trade latency for energy when desired, and enables energy efficient multi-fragment unicast communication by only keeping the active route awake. We also present Adaptive AppSleep, an application driven addition to AppSleep which supports varying latency requirements while still maximizing energy efficiency. Our evaluation demonstrates that for an overlooked class of applications, stream-oriented power management protocols such as AppSleep outperform packet-based protocols such as B-MAC and S-MAC.
This document describes the assumptions, problem statement, and goals for transmitting IP over IEEE 802.15.4 networks.The set of goals enumerated in this document form an initial set only.
This document describes the frame format for transmission of IPv6
packets and the method of forming IPv6 link-local addresses and
statelessly autoconfigured addresses on IEEE 802.15.4 networks.
Additional specifications include a simple header compression scheme
using shared context and provisions for packet delivery in IEEE
802.15.4 meshes. [STANDARDS-TRACK]
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