302:
635:
Proceedings of the 4th IFIP-TC6 International
Conference on Networking Technologies, Services, and Protocols, Performance ofo Computer and Communication Networks, Mobile and Wireless Communication Systems
332:
555:
535:
515:
495:
475:
455:
432:
412:
392:
372:
352:
207:
187:
167:
147:
127:
107:
215:
81:
can decidedly slow spreading processes over the network. This is of great interest for studying the spread of information and disease.
646:
Jagerman, D. L. and
Melamed, B. (1994.) "Burstiness Descriptors of Traffic Streams: Indices of Dispersion and Peakedness",
633:
Ying, Y.; Mazumdar, R.; Rosenberg, C.; Guillemin, F. (2005.) "The
Burstiness Behavior of Regulated Flows in Networks",
714:
67:
71:
709:
676:
P. Holme, J. Saramäki. Temporal
Networks. Phys. Rep. 519, 118–120; 10.1016/j.physrep.2012.03.001 (2012)
576:
78:
89:
One relatively simple measure of burstiness is burstiness score. The burstiness score of a subset
566:
571:
51:
47:
598:
Lambiotte, R. (2013.) "Burstiness and
Spreading on Temporal Networks", University of Namur.
310:
540:
520:
500:
480:
460:
440:
417:
397:
377:
357:
337:
192:
172:
152:
132:
112:
92:
70:
of inter-event times. Distributions of bursty processes or events are characterised by
703:
297:{\displaystyle \mathrm {Burst} (e,t)=\left({\frac {E_{t}}{E}}-{\frac {1}{T}}\right)}
63:
32:
686:
20:
620:
D'Auria, B. and
Resnick, S. I. (2006.) "Data network models of burstiness",
28:
36:
660:
648:
Proceedings of the 1994 Conference on
Information Sciences and Systems
59:
55:
40:
27:
is the intermittent increases and decreases in activity or
607:
Neuts, M. F. (1993.) "The
Burstiness of Point Processes",
46:
Burstiness is observable in natural phenomena, such as
557:
a bursty period. A negative score implies otherwise.
543:
523:
503:
483:
463:
443:
420:
400:
380:
360:
340:
313:
218:
195:
175:
155:
135:
115:
95:
77:
Burstiness of inter-contact time between nodes in a
549:
529:
509:
489:
469:
449:
426:
406:
386:
366:
346:
326:
296:
201:
181:
161:
141:
121:
101:
66:. Burstiness is, in part, due to changes in the
16:Intermittent increases and decreases in activity
31:of an event. One measure of burstiness is the
437:Burstiness score can be used to determine if
8:
334:is the total number of occurrences of event
594:
592:
661:"Burstiness and Memory in Complex Systems"
687:An Evolution of Computer Science Research
542:
522:
502:
482:
462:
442:
419:
399:
379:
359:
339:
318:
312:
279:
265:
259:
219:
217:
194:
174:
154:
134:
114:
94:
659:Goh, K.-I. and Barabasi, A.-L. (2006.)
588:
394:is the total number of occurrences of
7:
609:Commun. Statist.—Stochastic Models
232:
229:
226:
223:
220:
14:
457:is a "bursty period" relative to
497:occurs more often during subset
189:compared to its occurrences in
248:
236:
50:, or other phenomena, such as
1:
477:. A positive score says that
685:A. Hoonlor et al. (2013). "
731:
149:is a measure of how often
691:Communications of the ACM
68:probability distribution
551:
531:
511:
491:
471:
451:
428:
408:
388:
368:
348:
328:
298:
203:
183:
163:
143:
123:
103:
622:Adv. in Appl. Probab.
552:
532:
517:than over total time
512:
492:
472:
452:
429:
409:
389:
369:
349:
329:
327:{\displaystyle E_{t}}
299:
204:
184:
164:
144:
129:relative to an event
124:
104:
35:—a ratio between the
577:Time-varying network
541:
521:
501:
481:
461:
441:
418:
398:
378:
358:
338:
311:
216:
193:
173:
153:
133:
113:
93:
79:time-varying network
72:heavy, or fat, tails
209:. It is defined by
62:network traffic or
715:Applied statistics
567:Burst transmission
547:
527:
507:
487:
467:
447:
424:
404:
384:
364:
344:
324:
294:
199:
179:
159:
139:
119:
99:
550:{\displaystyle t}
530:{\displaystyle T}
510:{\displaystyle t}
490:{\displaystyle e}
470:{\displaystyle e}
450:{\displaystyle t}
427:{\displaystyle T}
407:{\displaystyle e}
387:{\displaystyle E}
367:{\displaystyle t}
347:{\displaystyle e}
287:
274:
202:{\displaystyle T}
182:{\displaystyle t}
162:{\displaystyle e}
142:{\displaystyle e}
122:{\displaystyle T}
102:{\displaystyle t}
64:vehicular traffic
48:natural disasters
722:
694:
683:
677:
674:
668:
657:
651:
644:
638:
631:
625:
624:, 38(2):373–404.
618:
612:
605:
599:
596:
572:Poisson clumping
556:
554:
553:
548:
536:
534:
533:
528:
516:
514:
513:
508:
496:
494:
493:
488:
476:
474:
473:
468:
456:
454:
453:
448:
433:
431:
430:
425:
413:
411:
410:
405:
393:
391:
390:
385:
373:
371:
370:
365:
353:
351:
350:
345:
333:
331:
330:
325:
323:
322:
303:
301:
300:
295:
293:
289:
288:
280:
275:
270:
269:
260:
235:
208:
206:
205:
200:
188:
186:
185:
180:
168:
166:
165:
160:
148:
146:
145:
140:
128:
126:
125:
120:
108:
106:
105:
100:
85:Burstiness score
730:
729:
725:
724:
723:
721:
720:
719:
700:
699:
698:
697:
684:
680:
675:
671:
658:
654:
645:
641:
632:
628:
619:
615:
606:
602:
597:
590:
585:
563:
539:
538:
519:
518:
499:
498:
479:
478:
459:
458:
439:
438:
416:
415:
396:
395:
376:
375:
356:
355:
336:
335:
314:
309:
308:
261:
258:
254:
214:
213:
191:
190:
171:
170:
151:
150:
131:
130:
111:
110:
109:of time period
91:
90:
87:
17:
12:
11:
5:
728:
726:
718:
717:
712:
702:
701:
696:
695:
678:
669:
652:
639:
637:, 3462:918–29.
626:
613:
611:, 9(3):445–66.
600:
587:
586:
584:
581:
580:
579:
574:
569:
562:
559:
546:
526:
506:
486:
466:
446:
423:
403:
383:
363:
343:
321:
317:
305:
304:
292:
286:
283:
278:
273:
268:
264:
257:
253:
250:
247:
244:
241:
238:
234:
231:
228:
225:
222:
198:
178:
158:
138:
118:
98:
86:
83:
15:
13:
10:
9:
6:
4:
3:
2:
727:
716:
713:
711:
710:Markov models
708:
707:
705:
692:
688:
682:
679:
673:
670:
666:
662:
656:
653:
649:
643:
640:
636:
630:
627:
623:
617:
614:
610:
604:
601:
595:
593:
589:
582:
578:
575:
573:
570:
568:
565:
564:
560:
558:
544:
524:
504:
484:
464:
444:
435:
421:
401:
381:
361:
341:
319:
315:
290:
284:
281:
276:
271:
266:
262:
255:
251:
245:
242:
239:
212:
211:
210:
196:
176:
156:
136:
116:
96:
84:
82:
80:
75:
73:
69:
65:
61:
57:
53:
49:
44:
42:
38:
34:
30:
26:
22:
693:, 56(10):79
690:
681:
672:
665:Physics Data
664:
655:
647:
642:
634:
629:
621:
616:
608:
603:
436:
354:in subset
306:
88:
76:
45:
24:
18:
169:appears in
43:of counts.
33:Fano factor
704:Categories
583:References
25:burstiness
21:statistics
650:, 1:24–8.
537:, making
277:−
29:frequency
561:See also
37:variance
52:network
307:Where
60:email
374:and
56:data
41:mean
39:and
689:",
414:in
19:In
706::
663:,
591:^
434:.
74:.
23:,
667:.
545:t
525:T
505:t
485:e
465:e
445:t
422:T
402:e
382:E
362:t
342:e
320:t
316:E
291:)
285:T
282:1
272:E
267:t
263:E
256:(
252:=
249:)
246:t
243:,
240:e
237:(
233:t
230:s
227:r
224:u
221:B
197:T
177:t
157:e
137:e
117:T
97:t
58:/
54:/
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.