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We note that this problem is a generalization of the single event propagation problem, which is more dif cult to cope with because of the severe energy restrictions of the particles. Certainly, because of the dense deployment of sensor particles close to each other, communication between two particles is much more energy-ef cient than direct transmission to the sink. Furthermore, short-range hop-by-hop transmissions can effectively overcome some of the signal propagation effects in long-distance transmissions and may help to smoothly adjust propagation around obstacles. Finally, the low-energy transmission in multihop communication may enhance security, protecting from undesired discovery of the data propagation operation. On the other hand, long-range transmissions require the participation of few particles and therefore reduce the overhead on particle resources and provide better network response times. Furthermore, long-range communication permits the deployment of clustering and other ef cient techniques, developed for ad hoc wireless networks. In particular, a clustering scheme enables cluster heads to reduce the amount of transmitted data by aggregating information. The above suggest that many diverse approaches exist to the solution of the multiple event propagation problem P. Further to choosing between long or short transmissions, certain additional tradeoffs are introduced by choosing between xed or varying transmission range. In particular, we wish to focus on the following important properties: (a) Obstacle Avoidance: This may be achieved by increasing transmission range when an obstacle is encountered. (b) Fault Tolerance: Increasing range may reach active sensors when the current range does not succeed, because of either faulty or sleeping sensors close to sensor which is currently transmitting or in the case of very low network densities.

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Request(~ aFn, &aStat, &A[0, 0]) Request(~ aFn, &aStat,&A[a1, 0]) Request(~ aFn, &aStat, &A[a1, a2])

; Lim, B; Stanton, L W Inhibition of SARS coronavirus infection in vitro with clinically approved antiviral drugs Emerging Infect Dis 2004, 10, 581 586..

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(c) Network Longevity: An interesting aspect of the problem under investigation is the lifetime of particles, since it affects the ability of the network to propagate data to the sink, because available routes are reduced as more particles consume their energy resources and die Varying transmission range may bypass the sensors lying close to the sink, which tend to be overused in the case of xed range transmissions, since all data pass through them in this case The same holds also in the case of a geographical concentration of event generation 1564 The Variable Transmission Range Protocol (VTRP) In this protocol, each particle p that has received info(E) from p (via, possibly, other particles) does the following: Phase 1: The Search Phase It uses a periodic low-energy broadcast of a beacon in order to discover a particle nearer to S than itself.

DoCancel(aReqMask)

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Among the particles returned, p selects a unique particle p that is best with respect to progress toward the sink More speci cally, the particle pE that among all particles found achieves the bigger progress on the p S line should be selected (see Figure 152) Phase 2: The Direct Transmission Phase Then, p sends info(E) to p and sends a success message to p (ie, to the particle from which it originally received the information) Phase 3: The Transmission Range Variation Phase If the search phase fails to discover a particle nearer to S, p enters the transmission range variation phase More speci cally, each particle maintains a local counter , with initial value = 0 Every time the search phase fails, this counter is increased by 1 Thus is an indication of the number of failures to locate an active particle.

84. Dianzani, F.; Scagnolari, C.; Vincenzi, E.; Bellomi, F.; Clementi, M.; Antonelli, G. Antiviral action of interferons on human coronavirus. Abstracts of the 17th International Conference on Antiviral Research, Tucson, AZ, USA, 2 6 May 2004. Antiviral Res. 2004, 62, A87, no. 152. 85. Haagmans, B. L.; Kuiken, T.; Martina, B. E.; Fouchier, R. A. M.; Rimmelzwaan, G. F.; van Amerongen, G.; van Riel, D.; de Jong, T.; Itamura, S.; Chan, K.-H.; Tashiro, M.; Osterhaus, A. D. M. E. Pegylated interferon-a protects type 1 pneumocytes against SARS coronavirus infection in macaques. Nat. Med. 2004, 10, 290 293. 86. Fouchier, R. A. M.; Hartwig, N. G.; Bestebroer, T. M.; Niemeyer, B.; de Jong, J. C.; Simon, J. H. Osterhaus, A. D. M. E. A previously undescribed coronavirus associated with respiratory disease in humans. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 6212 6216. 87. Van der Hoek, L.; Pyrc, K.; Jebbink, M. F.; Vermeulen-Oost, W.; Berkhout, R. J. M.; Wolthers, K. C.; Wertheim-Van Dillen, P. M.; Kaandorp, J.; Spaargaren, J.; Berkhout, B. Identi cation of a new human coronavirus. Nat. Med. 2004, 10, 368 373.

DoCancel(aReqMask)

Based on , the particle modi es its transmission range R according to a change function F( ) We here consider four different functions for varying the transmission range: (a) Constant Progress This choice is more suitable in the case where the network is comprised of a large number of particles and thus, a small increment of the transmission range will probably suf ce to locate an active particle Based on this assumption, the change function is de ned as follows: F( ) = Rnew = Rinit + c , (ie, c = 10) This is considered as the basis VTRP and is denoted as VTRPc (b) Multiplicative Progress In this case, the transmission range of the particle is increased mode drastically We call this variation of our protocol VTRPm F( ) = Rnew = Rinit + Rinit m , a small value (ie.

Laboratorio de Virolog a, Departamento de Qu mica Biologica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires

Request(0x7FFFFFFF, aReqMask, 0)

, m = 3) where m is a constant set to where c is a constant set to a small value.

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