Performance Modeling and Benchmarking of Event-Based ... - DVS

More documents

Recommendations

Info

58 CHAPTER 4. PERFORMANCE ENGINEERING OF EVENT-BASED SYSTEMS underlying scenario of this scenario, the consumer wants to pull all existing Event tokens. Since the number of existing Event tokens is changing, our model has to dynamically adjust itself to pull all tokens. As illustrated in Figure 4.13 we model Phase I similar to Pattern 4 by defining a Timer place and a token named Disconnected. While the Timer is processing the Disconnected token (and the Disconnected exists), the consumer is disconnected. In Phase II the connection is established: the Disconnected token is transformed by transition T3 to a Trigger token. This token is stored in an ordinary place named Trigger Store. While the Trigger token exists, the consumer is connected to the broker. When the connection is established, the consumer tries to pull all waiting event notifications (Phase III ). The number of notifications are waiting for the consumer is unknown. Therefore, we pull them one by one by firing transition T2-I for each Event notification. If no further Event exists in the depository of the broker, the consumer closes the connection. In our model this is performed by transition T2-II which transforms the Trigger token back to a Disconnected token. It has to be guaranteed that T2-II is only fired if no further Event tokens exist (→ transition priorities). QPN Definition Places: Place Type Description Producer S Publishes events. Broker Q Stores all incoming events. Timer Q Timer queue (scheduling strategy: Infinite Server). If the Timer is empty, the consumer is connected to the broker. Trigger Store O Stores Trigger token. If the consumer is disconnected, it is empty. Consumer S Pulls events from broker. Colors: Color Event Trigger Disconnected Description Represents the published event. Triggers pull commands. Represents disconnected state. Init No. of Colors: Color Place Count Trigger Trigger Store 1 Transitions: Id Input Output FW Description T1 1 Event (P roducer) 1 Event (Broker) 1 Producer publishes event. T2-I 1 Event (Broker) 1 Event (Consumer) ∞ Pull one event. 1 Trigger (Trigger 1 Trigger (Trigger Store) T2-II 1 Trigger (Trigger Store) T3 1 Disconnected (Trigger Store) Store) 1 Disconnected (T imer) 1 If no event is available → go back to sleep. 1 Event (Broker) 1 Establishes a connection.
4.2. PERFORMANCE MODELING PATTERN 59 Pattern 6: Request Controlled Pull I Timer 1‘Sleep! T3 Trigger Store 1‘Event! 1‘Event 1‘Event 1‘Event 1‘Event Producer T1 Broker T2 Consumer T2-I: Pull Event T3-I: Consumer is ready Broker Event Trigger Store Trigger T2-II: Go to sleep Broker Trigger 1 1 1 1 1 Consumer Event Timer Sleep Consumer Event Timer Sleep 1 T3-II: Wake up 1 1 1 Trigger Store Trigger Trigger Store Trigger Figure 4.14: Standard Pull Patterns Characteristics • Pull-based communication on demand • Resource modeling (number of service places) Example An event consumer connects frequently to a broker to check whether notifications are waiting. If yes, the consumer downloads one of them, closes the connection and processes the event notification. As soon as the event has been processed the consumer connects again to the broker to pull the next event. If no event is available, the consumer closes the connection and waits for a specified period of time before pursuing the next pull attempt. Description This scenario differs mainly from the previous ones in that the pull attempt of the consumer is not only controlled by time but also by the availability of the consumer. The consumer tries to pull the next event as soon as he is ready, i.e. after the last event was processed. Only if no further event is available at the depository of the broker, the consumer disconnects and the next connection is triggered after a specified time interval. This behavior is reflected in transitions 2 & 3. When the consumer has processed an event, the Event token is transformed by transition 3-I to a Trigger token. Next, transition 2 is fired.
Page 1:
Performance Modeling and Benchmarki
Page 4 and 5:
priorities. Finally, we validated o
Page 6 and 7:
4.3.4 Tool Extension . . . . . . .
Page 8 and 9:
5.7 Proportions of the Interactions
Page 11 and 12:
List of Acronyms Acronym λ t,k j A
Page 13 and 14:
Acronym SPEC-OSG SPE SPN SQL ST SUT
Page 15 and 16:
Chapter 1 Introduction 1.1 Motivati
Page 17 and 18:
PC Server 310 PC Server 310 PC Serv
Page 19 and 20:
1.3. APPROACH AND CONTRIBUTIONS OF
Page 21 and 22: 1.4. THESIS ORGANIZATION 7 • Stan
Page 23 and 24: Chapter 2 Background In this chapte
Page 25 and 26: 2.1. EVENT-BASED SYSTEMS 11 is gene
Page 27 and 28: 2.2. TECHNOLOGY PLATFORMS OF EVENT-
Page 35 and 36: 2.3. INTRODUCTION TO QUEUEING PETRI
Page 37 and 38: 2.3. INTRODUCTION TO QUEUEING PETRI
Page 39 and 40: Chapter 3 Related Work In this chap
Page 41 and 42: 3.2. BENCHMARKING OF EVENT-BASED SY
Page 43 and 44: 3.2. BENCHMARKING OF EVENT-BASED SY
Page 45 and 46: 3.4. CONCLUDING REMARKS 31 hierarch
Page 47 and 48: Chapter 4 Performance Engineering o
Page 49 and 50: 4.1. MODELING METHODOLOGY FOR EBS 3
Page 57 and 58: 4.2. PERFORMANCE MODELING PATTERN 4
Page 71: 4.2. PERFORMANCE MODELING PATTERN 5
Page 87 and 88: 4.3. EXTENSIONS OF QPNS 73 ,-).$%&'
Page 89 and 90: 4.4. CONCLUDING REMARKS 75 Without
Page 91 and 92: Chapter 5 Benchmarking of Event-Bas
Page 93 and 94: 5.1. SPECJMS2007 - A STANDARD BENCH
Page 115 and 116: 5.2. CASE STUDY I: SPECJMS2007 101
Page 123 and 124:
5.2. CASE STUDY I: SPECJMS2007 109
Page 125 and 126:
5.3. JMS2009-PS - A PUBLISH /SUBSCR
Page 127 and 128:
5.3. JMS2009-PS - A PUBLISH /SUBSCR
Page 129 and 130:
5.4. CASE STUDY II: JMS2009-PS 115
Page 131 and 132:
5.4. CASE STUDY II: JMS2009-PS 117
Page 133 and 134:
Chapter 6 Performance Modeling of E
Page 135 and 136:
6.2. MODELING SPECJMS2007 121 Scena
Page 137 and 138:
6.2. MODELING SPECJMS2007 123 BASE*
Page 139 and 140:
6.2. MODELING SPECJMS2007 125 1‘O
Page 141 and 142:
6.2. MODELING SPECJMS2007 127 Sc. 1
Page 143 and 144:
6.2. MODELING SPECJMS2007 129 Perce
Page 145 and 146:
6.2. MODELING SPECJMS2007 131 Serve
Page 147 and 148:
6.3. CONCLUDING REMARKS 133 the mod
Page 149 and 150:
Chapter 7 Conclusions and Outlook W
Page 151 and 152:
7.1. ONGOING AND FUTURE WORK 137 JA
Page 153 and 154:
7.1. ONGOING AND FUTURE WORK 139 th
Page 155 and 156:
Bibliography [1] J. Abbott, K. B. M
Page 157 and 158:
BIBLIOGRAPHY 143 [29] BiCEP Researc
Page 159 and 160:
BIBLIOGRAPHY 145 [61] G. Cugola and
Page 161 and 162:
BIBLIOGRAPHY 147 [92] R. Henjes, M.
Page 163 and 164:
BIBLIOGRAPHY 149 [128] S. Kounev an
Page 165 and 166:
BIBLIOGRAPHY 151 [162] Object Compu
Page 167 and 168:
BIBLIOGRAPHY 153 [197] K. Sachs, S.
Page 169 and 170:
BIBLIOGRAPHY 155 [228] P. Tran, P.
Page 171:
Erklärung Hiermit erkläre ich, di
show all

Performance Modeling and Benchmarking of Event-Based ... - DVS

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?