Nrk api introduction

Version 9 (Anthony Rowe, 10/18/2008 01:01 am)

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 = Introduction =
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The rapid proliferation of sensor networks has placed increasing demands upon the
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system infrastructure for supporting scalable distributed sensor applications. As applications
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for sensors in areas as diverse as security surveillance, traffic monitoring, smart
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spaces and smart buildings continues to grow, infrastructural support for sensor network
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applications in the form of system software is becoming increasingly important.
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The push provided by the scaling of technology and the need to support increasingly
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complicated and diverse applications has resulted in the need for traditional multitasking
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operating system (OS) abstractions and programming paradigms. The case for
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small-footprint real-time OS support in sensor networks is strengthened by the fact that
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many sensor networking applications are time-sensitive in nature i.e. the data must be
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delivered from the source to the destination within a timing constraint. For example,
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in a surveillance application, data relayed by a task which is responsible for detecting
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intruders and subsequently alerting the gateway nodes of the system should be able
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to reach the gateway on a timely basis. In this paper, we present Nano-RK, a smallfootprint
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embedded real-time operating system with networking support.
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Nano-RK supports the classical operating system multitasking abstractions allowing
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sensor application developers to work in a familiar paradigm resulting in small
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learning curves, quicker application development times and improved productivity.
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We show that an efficient implementation of such a paradigm is practical. We associate
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tasks with priorities and support priority-based preemption i.e, a task can always
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be preempted by a higher-priority task that becomes eligible to run. For timing sensitive
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applications, we use priority-based preemptive scheduling to implement the ratemonotonic
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paradigm of real-time scheduling so that a periodic sensor task set with
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timing deadlines can be scheduled such that their timing guarantees are honored.
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Since sensor nodes are resource-constrained and energy-constrained, we provide functionality 
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whereby the operating system can enforce limits on the resource usage of
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individual applications and on the energy budget used by individual applications and
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the system as a whole. In particular, we implement CPU reservations and Network
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Bandwidth reservations wherein dedicated access of individual application to system
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resources is guaranteed by the OS. The OS also implements sensor reservations to
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enforce usage on the number of accesses to individual sensors. Since the energy used
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by each task is the total sum of energy consumed by the CPU, the radio interface and the
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individual sensors, a particular setting for each of these leads to an energy reservation.
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Since we use a static design-time approach for admission control, we provide tools for
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estimating the energy budget of each application and (hence) the system lifetime. The
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CPU , network and sensor reservation values of tasks can be iteratively modified by the
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system designer until the lifetime requirements of the node are satisfied.
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