The Landscape of Pervasive & Mobile Computing Standards Sumi Helal Synthesis Lectures on Mobile and Pervasive Computing Preface



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10.3 THE BIG PICTURE


To facilitate this large-scale operation, Continua has created a series of working groups, all governed by a board of directors. These groups pursue independent subgoals and tasks and periodically report to the larger Continua organization. The Technical Working Group has organized its work into numerous subgroups, including one for each of the four interoperable interfaces and one for each of the three focus areas. It also has subgroups that focus on some overarching subject, such as the overall architecture or system security and privacy.

Much of the work is restricted to Continua’s members. However, another way to participate is to join the corresponding SDOs, which also lets you fully participate in the discussion and construction of the bedrock standards (for example, see the “PAN Interface Standards” sidebar).

Continua plans to complete its Version One Guidelines in the first quarter of 2008. At the same time, it will launch its certification and testing program. These guidelines, tests, and procedures will ensure interoperability of the components within the personal healthcare ecosystem. This paves the way for new and innovative products to radically improve health and quality of life as well as eliminate unnecessary costs from the healthcare system.



Figure 10.2. The Continua End-to-End reference architecture.


PAN INTERFACE STANDARDS

Here are a few Peripheral Area Network Interface standards-development activities that are underway.

Data and protocol

The ISO/IEEE 11073 Personal Health Data Working Group is defining transport-independent personal-health data and protocol standards. The group’s charter is to provide standards that

address transport-independent application and information profiles between PAN devices and application-hosting devices. Application and information profiles comprise exchange format, data representation, and terminology. The common exchange format should let different domains share data. For more information, contact the group chair at phd-chair@ieee.org.

Wireless transport

The Bluetooth SIG Medical Devices Working Group is tasked with enabling interoperability between Bluetooth-enabled medical, health, and fitness devices, and systems that can aggregate

and perform operations on device data. (Such data could be from cellular phones, health appliances, set-top boxes, or PCs.) This effort includes the development of a profile that allows

consumers to easily connect any two devices that support the medical device profile. Such devices have unique needs, and this working group aims to address those needs through focused

representation of the medical- and fitness-device industries. For more information, contact the group chair at

med-chair@bluetooth.org.



Wired transport

The USB-IF Personal Healthcare Device Working Group is tasked to enable personal healthcare devices to seamlessly interoperate with USB hosts. The group’s initial goal is to define a USB Personal Healthcare Device Class specification. The specification will enable health-related devices, such as blood pressure cuffs and exercise watches, to connect via USB to consumer electronic products such as PCs and health appliances. Interoperability of health-related devices and consumer electronic products will facilitate the communication between a patient and a doctor, an individual and a fitness coach, or an elderly person and a remote caregiver. For more information, contact the group chair at personal_healthcare_chair@usb.org.



chapter 11

PERVASIVE APPLICATION STANDARDS

  • RFID, NFC, multi-modal tags, in asset tracking, compliance and control

  • Columns utilized:

    • None. However, original materials plus some content from another Synthesis Lecture (Roy’s) will be utilized.

chapter 12

THE FUTURE LANDSCAPE OF STANDARDS

  • Conclusions and visionary outlook at the future of these standards

  • Columns utilized: none.

chapter 13

Sensor Networks—Motes, Smart Spaces and Beyond

Sensor networks have come a long way since their humble beginnings in DARPA-funded academic research projects in the 1990s and have morphed into a significant research area in their own right. Over the last decade or so, networked sensing devices have become embedded all around us. In this article we look at how sensor network research and applications have evolved and how emerging trends could determine where they’re headed.


13.1 The Birth of the Mote


Mainstream research in sensor networks began around the mid-1990s with a number of DARPA-funded research initiatives undertaken by top US universities such as the University of California, Berkeley. The goal of this research was to design and create tiny autonomous computers (called sensor platforms or in some cases motes) that could unobtrusively observe their environment through built-in sensors and report back to a remote base station. The primary use cases involved scattering hundreds or thousands of these sensor platforms in an area and tasking them with monitoring vehicular movement or environmental conditions and periodically reporting the data. To achieve such a goal, researchers envisioned a number of characteristics that would set these sensor platforms apart from other computers available at that time, namely:

  • Primitive processing capability: Since the sensor platforms weren’t designed for general-purpose computing they required primitive yet robust processing capabilities. Unlike desktop PCs and servers, the platform would typically be designed around a low-cost microcontroller with limited processing and memory resources.

  • Self-organized networking: The sensor platforms were designed for deployment in areas without existing network infrastructures so developing new networking capabilities became an important focus of sensor network research. Researchers envisioned that the platforms would collaborate to set up ad-hoc networks for routing sensor data and relaying it to a remote base station.

  • Low power operation: The sensor platforms had to be self-sufficient and capable of operating on battery power for a reasonably long time. This implied that low power consumption was more important than high throughput for both processing and networking hardware.

  • Tiny form factor: The sensor platforms had to be small enough to remain unobserved and be easily deployed in large numbers without being conspicuous. This was publicized as the “smart dust” concept where sensor platforms could become so tiny that they’d be as ubiquitous and observable as mere specks of dust.

  • Target applications: Perhaps due to the nature of research funding, the initial target applications favored relatively simple monitoring tasks where data was simply collected and stored, or aggregated in some form and transmitted out of the sensor network. Applications were written as part of the platforms’ firmware with a focus on execution efficiency and resource management rather than programmability and ease of application development.

  • Lack of mechanical actuation: Mechanical actuation wasn’t a primary application requirement, possibly because the targeted applications were more concerned with passive activities such as sensing and monitoring. Moreover, due to the low power operation requirement, mechanical actuation was effectively out of the question for most use cases. There were some efforts to have certain types of actuation such as the motion-enabled XYZ mote developed by the Embedded Networks and Applications Lab at Yale, but they were largely limited to specific niches.

Out of these characteristics and requirements, two major focus areas emerged that defined sensor network research for a long time, namely, selforganizing networks and power-efficient computing. However, as sensor networks became more ubiquitous, new requirements emerged that redefined their design philosophy, as we shall see later on in this article. Meanwhile, let us take a look at two popular first generation sensor platforms which shared similar characteristics yet they targeted different application domains.

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