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BOX 7-4

41,533 2,077 39,457 0 39,457

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Gallais A, Carle J, Simplot-Ryl D, Stojmenovic I Localized sensor area coverage with low communication overhead IEEE Trans Mobile Comput 2008;7(5):1 12 Gu L, Stankovic JA Radio-triggered wake-up capability for sensor networks Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 04); Toronto, Canada; 2004 Gui C, Mohapatra P Power conservation and quality of surveillance in target tracking sensor networks ACM Mobicom; Philadelphia, USA; 2004 Gupta H, Das SR, Gu Q Connected sensor cover: self-organization of sensor networks for ef cient query execution Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc); Annapolis, USA; 2003 Huang C, Tseng Y The coverage problem in a wireless sensor network Proceedings of the 2nd ACM International Conference on Wireless Sensor Networks and Applications; San Diego, USA; 2003 pp 115 121 Jiang J, Dou W.

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An RFP is a time-honored method for choosing vendors in which the company gives a group of vendors the opportunity to show their capabilities by responding to a specific set of business requirements and information requests. RFPs typically request a broad swath of information product or service data, vendor financial and structure data, customer references, qualifications with similar work, and more. Requiring interested vendors to respond to a well-thought-out RFP can be a highly effective approach for both gathering additional data without

1. . . . 2. #include <upc_relaxed.h> 3. #include "globals.h" 4. / dynamically allocated sh_grids[] to be matched to / / [2][N][N][N] / 5. shared [BLOCKSIZE] double *shared sh_grids; 6. shared double dTmax_local[ THREADS] ; 7. int main(void) 8. { 9. int nr_iter; 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. if(MYTHREAD == 0) { / allocate the memory required for grids[2][N][N][N] / sh_grids = (shared [BLOCKSIZE] double *shared) upc_global_alloc(2*N*N*N/BLOCKSIZE,BLOCKSIZE*sizeof(double)); CHECK_MEM(sh_grids); } /* synchronization * / upc_barrier; /* do all the remaining, as usual * / ...

For this example, the population size was chosen to be 500 and the number of generations was 200. When this problem was run 50 times using different random number seeds, GP created a 100 % correct program 49 times, and the probability of finding a correct solution at generation 200 was 72 %. Some interesting results were observed. First, all 49 correct programs were different. The differences ranged from the selection of different variables to some counter-intuitive program trees when compared to programs that a human programmer might have devised. One of the less intuitive programs is shown in Figure 15.9. Note that the first function called is the route function. This operation relies purely on the ordering of evaluation of function arguments, rather than a procedural sequencing more commonly found in human-generated programs. This demonstrates rather nicely that one of the features of GP is that it explores and exploits hidden relationships and features which can lead to highly optimal solutions. The main point

A coverage preserving density control algorithm for wireless sensor networks Proceedings Third International Conference Ad-Hoc Networks and Wireless (ADHOC-NOW); Vancouver, British Columbia; 2004 Kumar VSA, Arya S, Ramesh H Hardness of set cover with intersection Proceedings of the 27th International Colloquium on Automata, Languages and Programming; Geneva, Switzerland; 2000 pp 624 635 Kuruvila J, Nayak A, Stojmenovic I Hop count optimal position based packet routing algorithms for Ad hoc wireless networks with a realistic physical layer Proceedings of IEEE Mobile Ad Hoc and Sensor Systems (MASS); Fort Lauderdale, Florida, USA; 2004 Li Q, Rus D Global clock synchronization in sensor networks Proceedings of IEEE Infocom 2004; Hong Kong; 2004 Ovalle-Martinez F, Nayak A, Stojmenovic I, Carle J, Simplot-Ryl D Area based beaconless reliable broadcasting in Ad hoc and sensor networks Int J Sens Netw (IJSNet) 2006;2(2): 147 159 Romer K, Blum P, Meier L.

Now we shall nd s and t such that (cf. Eq. (6.3)) 6 s 858 t 84 Let us rst solve for the remainders in Eqs. (6.4) (6.6) and write them in reverse order. Then we obtain 6 18 1 12 12 84 4 18 18 858 10 84 6:7 6:8 6:9

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