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8.1 INTRODUCTION A growing number of sensor network applications require point-to-point services. Intuitively, pure sensing applications, where environment is monitored or events are tracked, require some geographical or geometric context for successful operation. In such a context, data interpretation and management is often tied to node positions. In addition to traditional sensing applications are a growing number of proposed applications that require no knowledge of geography yet do require advanced pointto-point services [1 4]. Traditional Internet routing techniques are unsuitable in either setting [5]. In this chapter we focus on the merits and challenges of algorithms and protocols that provide point-to-point services through position-based routing, where forwarding decisions are made by maximizing or minimizing some function of node locations within a coordinate system. The focus of discussion is on those protocols suited to static sensor networks where node positions within the network are known and unknown. The remainder of this chapter is organized as follows: In Section 8.2 we give some context to our presentation as well as some background information relevant to its content. Our discussion of position-based routing protocols suitable to sensor networks begins in Section 8.3 with those protocols where knowledge of sensor positions is assumed to exist prior to protocol execution; while the presentation is cumulative, each section may be read independently of the others. In Section 8.4 we present protocols where no a priori knowledge of position exists; amongst such protocols the routing element is coupled to the localization mechanism. We summarize our discussion in

2. In most cases the communication protocol example in Section 17.1 is actually a soft real time task. If the deadline is missed, the peer entity will retransmit, which will waste bandwidth and reduce throughput but will not cause catastrophic failure.

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C; Jin, B; et al Rational design of potent sialidase-based inhibitors of in uenza virus replication Nature 1993, 363, 148 153 28 Kim, C U; Lew, W; Williams, M A; Wu, H; Zhang, L; Chen, X; Escarpe, P A; Mendel, D B; Laver, W G; Stevens, R C Structure activity relationship studies of novel carbocyclic in uenza neuraminidase inhibitors J Med Chem, 1998, 41, 2451 2460 29 Brouillette, W J; Atigadda, V R; Luo, M; Air, G M; Babu, Y S; Bantia, S Design of benzoic acid inhibitors of in uenza neuraminidase containing a cyclic substitution for the N-acetyl grouping Bioorg Med Chem Lett 1999, 14, 1901 1906 30 Lou, M; Air, G M ; Brouillette, W J Design of aromatic inhibitors of in uenza virus neuraminidase J Infect Dis 1997, 176(Suppl.

Algorithms and Protocols for Wireless Sensor Networks, Edited by Azzedine Boukerche Copyright 2009 by John Wiley & Sons Inc.

We have given de nitions of real time systems and tasks. An operating system cannot be real time in the sense that I have just discussed. Instead the term real time operating system (usually abbreviated to RTOS) refers to an operating system that is capable of running real time applications. In this section I will discuss some of the properties that an RTOS should have.

Section 8.5; then we follow with open problems in Section 8.6 and, nally, exercises in Section 8.7.

1), S62 S65 31 Ives, J A L; Carr, J A; Mendel, D B; Tai, C Y; Lambkin, R; Kelly, L; Oxford, J S; Hayden, F G; Roberts, W A The H274Y mutation in the in uenza A NIHI neurominidase action site following aseltamivir phosphate treatment leave virus severely compromised both in vitro and in vivo Antiviral Res 2002, 55, 307 317 32 Gubareva, L V; Kaiser, L; Hayden, F G In uenza virus neuraminidase inhibitors Lancet 2000, 355, 827 835 33 Oxford, J S; Lambkin, R Targeting in uenza virus neuraminidase new strategy for antiviral therapy Drug Discov Today 1998, 3, 448 456 34 Galbraith, A W; Oxford, J S; Schild, G C; Watson, G L Protective effect of 1-adamantanamine hydrochloride on in uenza A2 infections in the family environment: a controlled double-blind study.

A real time system will generally consist of several logically separate but interacting tasks each with their own deadline. It may also contain nonreal time (or soft real time) tasks. The most important task for any RTOS is to schedule the tasks for execution on the processor in such a way that the deadlines of the real time tasks are always met. In analyzing whether this is possible, the following simpli ed model of task execution is often used. Consider that the system has a set of n tasks, denoted 1 , . . . , n . Each task is assumed to run periodically. Task i is triggered every Ti seconds, runs for a maximum time Ci and is expected to nish within time Di of being triggered. In reality tasks will have a variable execution time, but to ensure that deadlines can be met the worst case execution time (WCET) is assumed. Similarly, aperiodic tasks can be incorporated by treating them as periodic with period equal to the minimum possible time between invocations of the task. We de ne the response time (Ri ) of a task i to be the time from the task being triggered to the task completing. Figure 17.1 illustrates these task-timing parameters.

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