Index
References to figures are in italics.
A
absent events, 124–125
accuracy, 61–62
tradeoffs between timeliness and, 65–66
adaptability, 76–77
adaptors, 29
DBMS adaptors, 134–135
on request-driven interfaces, 135
Adverse Event Reporting System (AERS), 64–65
advertising example, 66
agents, 16
agility, 6–7
and EDA, 38–41
analyst-driven BI, 171–172
application flow, 91–94
application integration, EPN for, 100–101
architecture styles, 140–141
CEP-enabled applications, 146–148
monitors for heterogeneous systems, 145–146
monitors for homogenous systems, 144–145
pure-play monitoring systems, 143–144
subsystems that pre-process event streams, 142–143
attention amplification, 56–57, 204
attention from experts, 204–205
automatic responses, 196
automatic sense and respond, 188
B
BAM. See business activity monitoring (BAM)
batch-oriented processing, 35–38
BEP. See business event processing (BEP)
best practices
designing for long-term business benefits, 194–195, 197–200
stepwise development of eventprocessing functionality, 194, 195–196
using models of business and its environment, 194, 196–197
BI. See business intelligence (BI)
BPM. See business process management (BPM)
BREs. See business rule engines (BREs)
BRMS. See business rule management systems (BRMS)
business activity monitoring (BAM), 171, 172
BAM networks, 195
positioning BI and event processing, 174–175
business applications
architecture styles, 140–148
driving, 138
business drivers
categories of, 9–14
and system design, 8
business event processing (BEP), 51–52
ways that applications communicate business events, 130, 131
business intelligence (BI), 67
analyst-driven BI, 171–172
event processing in, 171–175
positioning BI and event processing, 174–175
strategy-driven BI, 173
business objects, 130
business process elapsed time, reducing, 5–6
business process management (BPM)
the BPM discipline, 165–166
BPM software, 166–167
and CEP, 169–170
and EDA, 167–169
overview, 165
business process management suites (BPMS), 166–167
business rule engines (BREs), 175
individual vs. set-based processing, 178–179
request-driven vs. event-driven, 177–178
temporal support, 178
business rule management systems (BRMS), 175–176
and CEP engine similarities, 176–177
businesses, and the future of event processing, 209–210
buy-versus-build tradeoffs, 200
C
calling, 103
notification through a call, 105–106
causality, 123
CEBP. See communication-enabled business process (CEBP) systems
See also timeliness
CEP. See complex event processing (CEP)
architecture styles, 140–148
and BPM, 169–170
CEP computation, 121
CEP-enabled applications, 146–148
multistage CEP applications, 143
pattern detection, 121–123
programming CEP software, 120–122
time windows, 123–124
using output of, 138–139
See also partially automated CEP
changing situations, responding to, 73–74
channels, 96
data-sharing channels, 104–105
civil infrastructure, 83
Code Pink alerts, 86–87
communicating one-way, 106–107
communication-enabled business process (CEBP) systems, 190
competition, 3
completeness, 62–64
complex event processing (CEP), 43
benefits of automated over manual CEP, 50–51
event-driven CEP, 47–49, 51–52
fully automated sense-and-respond CEP, 49–50
manual CEP, 43–45
partially automated CEP, 45–47
request-driven CEP, 52–53
time-driven CEP, 52
complex events, 117–118
event hierarchies, 118–120
event-processing rules and patterns, 120–124
variations on, 124–126
composite events, 117
impact of interconnectedness on security, 69
consumer applications driving development, 212
consumer pull, 12
consumers, 96–97
context, 28
context aware software, 47–48
continuous intelligence, vs. periodic intelligence, 139–140
continuous-processing systems, 35–38
contracts
for event-driven interactions, 24–25
for request-driven interactions, 25–26
for time-driven interactions, 26–27
copyright laws, 67–68
CORBA Component Model, 156
corporate performance management (CPM) applications, 77
cost-benefit metrics of event-processing systems, 55–56, 83–84
tradeoffs between accuracy and, 62
costs of false negatives and false positives, 63
costs of inaccuracy, 61
costs of inaccurate predictions of rare events, 62
reducing by double-checking, 61–62
Covey, Stephen R., 56
cross-trading applications, 73–74
crowd sourcing event processing components, 189
current events, reporting, 101–102
customer privacy, and event-processing applications, 67–68
customer relationship management (CRM) applications, 77
cyber-physical systems, 82–83
cyber-security of infrastructure, 68
D
D’Amario, Alfred, 74–75
dashboard technology, 160
data acquisition, 30
data consistency, 7
and EDA, 41–42
data sources, 195
crowd sourcing event processing components, 189
variety of, 188–189
on the Web, 189
data-sharing channels, 104–105
DBMS adaptors, getting observational notifications from, 134–135
decision support, 138
defense and homeland security applications, 80–81
derived events, 118
See also complex events
detecting attacks from within, 68–69
detecting events, 196
direct pull, 103
drug pedigrees, 82
E
EDA. See ee event-driven architecture (EDA)
educating IT staff, 157–158
effort, 58–60
required from business users for a successful pilot project, 193
e-mail, as a hybrid system, 29
energy applications, 88–89
enterprise decision management (EDM), 179
entertainment and leisure applications, 88
EPAs. See event-processing agents (EPAs)
e-pedigrees, 82
EPNs. See event-processing networks (EPNs)
ESP. See event-driven CEP
event analytics, 123
event channels, 96
event data, 130
event duration, 114
event handlers. See consumers
event hierarchies, 118–120
event processing
acquiring skills, 157–158
action items for successful event processing, 157–163
barriers and dangers, 211
in BPM, 171
in business intelligence, 171–175
defined, 4
developing event models and managing events, 161–163
drivers for adoption, 211–213
future of, 203–210
impact of on multiple roles, 183
impact on society, 210
implementing event-processing software infrastructure, 159–160
incorporating into IT architecture, 158–159
integrating into SOA initiatives, 160–161
positioning BI and event processing, 174–175
using event-enabled packaged applications, 159
event provenance, 68–69
event sources, 95–96
comparative value of, 136–137
event streams, 52
Event-Based Programming (Faison), 111–112
event-driven architecture (EDA)
agility, 38–41
and BPM, 167–169
communicating one-way, 106–107
data consistency, 41–42
free of requests, 107–108
information dissemination, 42–43
overview, 33–35
principles of, 34–35, 101–108, 115
pushing notifications, 102–106
reporting current events, 101–102
timeliness, 35–38
event-driven behavior, 1–2, 34
event-driven CEP, 47–49, 51–52
event-driven interactions, 17–18, 20, 21–22
contracts for, 24–25
evaluation of, 24
event-driven SOA, 151–153
service components, 156
specifying SOA services and events, 153–156
event-generating intermediaries, 98
event-processing agents (EPAs), 95
event-processing applications
analyzing suitable business domains for event processing, 79–89
attention amplification, 56–57
based on models, 196–197
business users tailoring systems themselves, 58
buy-versus-build tradeoffs, 200
cost-benefit metrics, 55–56
and customer privacy, 67–68
effort required to tailor systems for different business users, 58
enabling business users to tailor systems to their needs, 57–58
event design as important as database design, 59–60
features driving demand, 71–79
identifying applications suitable for event processing, 182
new applications vs. improvements to existing ones, 184–185
responding to events continuously or rarely, 185–186
smart grid example, 60
tailoring the application to suit the user, 199
templates, 59
See also REACTS
event-processing networks (EPNs), 76–77
for application integration, 100–101
for information dissemination, 99
reference architecture for, 94–101
for situation awareness, 99–100
event-routing intermediaries, 97–98
events
in a business context, 2–4
complex events, 117–126
detectable-condition view, 111–112, 114
detecting, 196
guidelines for designing events, 115
responses to, 30–31
state-change view, 111, 112–113
types of, 116–117
event-stream processing (ESP). See event-driven CEP
expert attention, 204–205
explicit models, 197
external sources, getting observational notifications from, 135–136
F
Faison, Ted, 111–112
false negatives, 62–63
fat-finger trades, 61–62
finance applications, 87–88
fire-and-forget communication, 106–107
flow. See application flow
folders, capture of event information in, 28–30
fully automated sense-and-respond CEP, 49–50
benefits of automated over manual CEP, 50–51
G
genetics, 117
globalization, 3
glossary, 219–225
H
Hangar Flying (D’Amario), 74–75
healthcare applications, 86–87
and the future of event processing, 206–207
horizontal causality, 123
hub-and-spoke, 76–77
human activity, stages of, 14, 15
hybrid systems, 27–31
I
implicit models, 197
inaccuracy, costs of, 61–62
information availability, 7–8
information dissemination, 7
and EDA, 42–43
EPN for, 99
infrastructure, and the future of event processing, 208–209
instance agility, 6
integrated circuit industry, 212
intelligent decision management (IDM), 179
interactions, 14–16
combinations of interaction types, 27–31
event-driven, 17–18, 20, 21–22, 24–25
flow of control in, 92
request-driven, 17, 18, 19, 21, 23–24, 25–26
shared expectations in event-driven interactions, 17
time-driven, 16, 18, 19, 20–21, 22–23, 26–27
types of, 16–20
interconnectedness, 212
intermediaries, 97
event-generating, 98
event-routing, 97–98
interval events, 114
J
joins, 122
K
key performance indicators (KPIs), 47
and periodic management systems, 140
KPIs. See key performance indicators (KPIs)
L
Large Hadron Collider, 85
logic coupling, 39
Luckham, David, 51, 111, 122, 216
M
management by exception, 74–76
manual CEP, 43–45
benefits of automated CEP over, 50–51
mass customization, 6
MBE. See management by exception
MD PnP. See Medical Device Plugand-Play interoperability program
Medical Device Plug-and-Play interoperability program, 87
message-oriented middleware. See MOM
messaging software, 159–160
models, 212
monitoring products, 160
monitors for heterogeneous systems, 145–146
monitors for homogenous systems, 144–145
N
natively generated events, getting observational notifications from, 133–134
NIMBY syndrome, 209
nonrenewable resources, and the future of event processing, 205
notifications, 7
in capital markets trading applications,128
observational notifications, 127–128, 132–137
pushing, 102–106
role of in business applications, 127–128
through a call, 105–106
transactional notifications, 127–131
using, 138–139
O
observational notifications, 127–128, 132–137
OLTP. See online transaction processing (OLTP)
one-way communication, 106–107
online transaction processing (OLTP), 74
Organization for the Advancement of Structured Information Standards (OASIS), 156
outside experts, 158
P
packaged applications, 159
partially automated CEP, 45–47
benefits of automated over manual CEP, 50–51
See also CEP software
pattern detection, 121–123
pattern discovery, 123
pattern instances, 122
pattern matching, 122–123
PC-cubed trends, 13–14, 84, 191, 212
and hybrid systems, 27
pedigree, 117
performance, 13
designing for, 197–199
performance management systems, 173
periodic intelligence, vs. continuous intelligence, 139–140
periodic pull, 103–104
personal information managers, 27–28, 29
pervasiveness, 12–13
physical world
automating, 139
getting observational notifications from, 133
pilot projects, 192
effort required from business users, 193
estimating return on investment from, 193–194
size of in event processing, 194
for well-defined applications, 192–193
PoC. See pilot projects
polling, 103–104
The Power of Events (Luckham), 111, 122
precision marketing, 6
predictive systems, 30
better timeliness from, 66
price, 12
proactive computations, 27
problem features, 78–79
process agility, 6–7
process elapsed time, reducing, 5–6
producer push, 12
producers, 95–96
proof of concept. See pilot projects
publish-and-subscribe model, 108–109
pure-play monitoring systems, 143–144
push via callback, 104
pushing notifications, 102–106
R
REACTS, 55–56
accuracy, 61–62
completeness, 62–64
cost/benefit measures, 83–84
effort, 58–60
relevance, 56–58
security, 67–69
timeliness, 64–67
Reengineering the Corporation (Hammer and Champy), 166
reference architecture
applying, 98–101
for event-processing networks, 94–101
reference data, 131
regulation, 3–4
rejected-order notification, 40
relevance, 56–58
renewable resources, and the future of event processing, 206
reporting current events, 101–102
request-driven CEP, 52–53
request-driven interactions, 17, 18, 19, 21
contracts for, 25–26
evaluation of, 23–24
resilience, 69
resources, 215–218
responding immediately, 106
responses to events, 30–31, 187
rule engines
and CEP software, 46
and event processing, 175–179
S
science, 84–85
and the future of event processing, 208
SCM. See supply-chain management
search engines, as hybrid systems, 29
and the future of event processing, 207–208
seismology example, 65–66
service components, 156
service-oriented architecture (SOA)
event-driven SOA, 151–156
integrating event processing into SOA initiatives, 160–161
overview, 149–151
The 7 Habits of Highly Effective People (Covey), 56
sharing messages, getting observational notifications from, 134
situation awareness, 35, 43, 81, 82, 85, 148, 152, 107, 172, 174, 182, 191–195, 203–208
EPN for, 99–100
smart grid example, 60
smart infrastructure, 82–83
SOA. See service-oriented architecture (SOA)
social networks, 187–188
societal impact of event processing, 210
spoofing, 68
staff education, 157–158
starting out, 181–192
estimating costs and benefits and planning for the future, 191–192
identifying applications suitable for event processing, 182
identifying data sources, 188–189
identifying events and data transformations, 190–191
identifying scenarios and responses, 186–188
identifying user communities, 183–186
state data, 130–131
STP. See straight-through processing (STP)
straight-through processing (STP), 38
strategy-driven BI, 173
subsystems that pre-process event streams, 142–143
supply-chain management, 142, 145–146
synthesized events, 118
See also complex events
system design, relation of business drivers to, 8
system fragility, 211
system resilience, 69
systems administration, 199–200
T
Taylor, Frederick Winslow, 166
technology push, 12–14
terminology, 219–225
time windows, 123–124
time-driven CEP, 52
time-driven interactions, 16, 18, 19, 20–21
advantages of, 23
contracts for, 26–27
evaluation of, 22–23
and EDA, 35–38
tradeoffs between accuracy and, 65–66
ways to improve, 67
See also celerity
track-and-trace applications, 81–82
transactional notifications, 127–131
transactions, 130
trends, in technology, 12–14
U
uncertain events, 124
U.S. National Institute of Standards and Technology (NIST), 213
V
value-time functions, 64–65
virtual enterprises instrumentation, 77–78
interacting with world outside of, 188
looking outside of, 72–73
users outside of, 184
VOEvents, 78
W
water management applications, 88
web scrapers, 135
when-then rules, 25
Windows Communication Foundation (WCF), 156
workforce of the 21st century, 85–86
and the future of event processing, 208
World Wide Web, getting observational notifications from, 135–136