Podcast
Questions and Answers
What is the primary function of Complex Event Processing (CEP) in the context of IoT?
What is the primary function of Complex Event Processing (CEP) in the context of IoT?
- To store and archive IoT sensor data for future analysis.
- To identify patterns in multiple events and trigger actions. (correct)
- To manage the power consumption of IoT devices.
- To provide network security for IoT devices.
In IoT, actions are typically based on single events rather than combinations of events.
In IoT, actions are typically based on single events rather than combinations of events.
False (B)
Which of the following event sources can be used in Complex Event Processing?
Which of the following event sources can be used in Complex Event Processing?
- IoT sensor data
- Social media feeds
- Weather reports
- All of the above (correct)
Real-time reactions are not critical for mission-sensitive IoT use cases.
Real-time reactions are not critical for mission-sensitive IoT use cases.
Which of the following is an example of a simple event in Complex Event Processing?
Which of the following is an example of a simple event in Complex Event Processing?
A combination of simple events is known as a ______ event.
A combination of simple events is known as a ______ event.
Which type of CEP engine is more suitable for IoT environments due to its scalability and fault tolerance?
Which type of CEP engine is more suitable for IoT environments due to its scalability and fault tolerance?
High latency and low accuracy are desirable characteristics in detecting events for IoT applications.
High latency and low accuracy are desirable characteristics in detecting events for IoT applications.
What are the two key factors that the quality of decisions depend on in Complex Event Processing?
What are the two key factors that the quality of decisions depend on in Complex Event Processing?
Dropping unprocessed events to cope with overload situations in CEP is known as ______.
Dropping unprocessed events to cope with overload situations in CEP is known as ______.
What is a potential drawback of using buffering as a solution to overload situations in CEP?
What is a potential drawback of using buffering as a solution to overload situations in CEP?
What is the main benefit of using parallel CEP execution for high and fluctuating event rates?
What is the main benefit of using parallel CEP execution for high and fluctuating event rates?
Static resource provisioning for peak loads is a cost-effective solution for CEP when traffic is consistently high.
Static resource provisioning for peak loads is a cost-effective solution for CEP when traffic is consistently high.
Which of the following is NOT a requirement for CEP operators to support parallel CEP execution?
Which of the following is NOT a requirement for CEP operators to support parallel CEP execution?
Splitting internal processing steps for parallel execution is known as ______ parallelization.
Splitting internal processing steps for parallel execution is known as ______ parallelization.
What is the primary limitation of intra-operator parallelization?
What is the primary limitation of intra-operator parallelization?
Match the components of data parallelization with their respective functions:
Match the components of data parallelization with their respective functions:
What is a limitation of key-based partitioning in data parallelization?
What is a limitation of key-based partitioning in data parallelization?
What type of partitioning model may struggle with unknown or variable pattern sizes?
What type of partitioning model may struggle with unknown or variable pattern sizes?
In batch-based partitioning, communication overhead remains constant regardless of pattern size fluctuation.
In batch-based partitioning, communication overhead remains constant regardless of pattern size fluctuation.
Flashcards
Complex Event Processing (CEP)
Complex Event Processing (CEP)
Identifies and correlates multiple events to detect predefined patterns and trigger actions across systems, people, and devices.
CEP Event Sources
CEP Event Sources
Data from IoT sensors, social media, GPS, weather reports, RFID, etc.
Simple Event (in CEP)
Simple Event (in CEP)
A single occurrence, like an RFID scan.
Complex Event (in CEP)
Complex Event (in CEP)
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CEP Engine Function
CEP Engine Function
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Centralized CEP Engine
Centralized CEP Engine
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Distributed CEP Engine
Distributed CEP Engine
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Load Shedding
Load Shedding
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Buffering (in CEP)
Buffering (in CEP)
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Intra-operator Parallelization
Intra-operator Parallelization
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Data Parallelization
Data Parallelization
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Splitter Function (in CEP)
Splitter Function (in CEP)
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Merger Function (in CEP)
Merger Function (in CEP)
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Key-based Partitioning
Key-based Partitioning
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Batch-based Partitioning
Batch-based Partitioning
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Study Notes
- Complex Event Processing (CEP) identifies and correlates multiple events to detect predefined patterns, triggering actions across systems, people, and devices.
- Actions in IoT often rely on combinations of events rather than single occurrences.
- Event sources for CEP include IoT sensor data, social media, GPS, weather reports, and RFID.
- CEP supports real-time reactions, which is critical for time-sensitive IoT use cases like traffic management, smart grids, and logistics.
- Simple events are single occurrences, while complex events are combinations of simple events.
- A CEP Engine matches incoming events with stored rules/patterns, triggering corresponding actions.
CEP Engine Types
- Centralized CEP engines have high bandwidth but are less scalable and have a single point of failure.
- Distributed CEP engines are more scalable and fault-tolerant, making them better for IoT applications.
- IoT requires low latency and high accuracy in detecting events.
- Accurate decision-making, such as in traffic violation detection, depends on avoiding false positives and negatives.
- Decision quality depends on the timing of event delivery and the consistency and completeness of delivered event sets.
Performance Challenges
- Overload situations occur when CEP can't keep up with the event arrival rate.
- Load shedding drops unprocessed events, potentially causing inconsistencies.
- Buffering queues events, but it can introduce unacceptable delays.
- Set buffering limits to balance latency and reliability.
- High and fluctuating event rates make buffer limits difficult to maintain.
- Parallel CEP execution helps handle workloads efficiently and meet buffer constraints.
- Static resource provisioning for peak loads leads to underutilization and higher costs during low traffic.
- Dynamic adjustment of operator parallelism based on current event rates reduces resource waste and cost.
- CEP operators should support parallelization, dynamic reconfiguration, and adaptive resource provisioning.
CEP Parallelization Techniques
- Intra-operator parallelization splits internal processing steps for parallel execution, limited by query complexity.
- Data parallelization partitions event streams for processing by multiple identical operator instances.
Data Parallelization Components
- Splitter distributes events based on a partitioning model.
- Operator instances execute the queries in parallel.
- Merger reassembles and orders the output events.
Partitioning Models
- Key-based partitioning uses a key in each event to assign events to partitions, but is limited by the number of unique key values.
- Batch-based partitioning splits events into batches large enough to match a pattern, but may struggle with unknown or variable pattern sizes and involves communication overhead due to pattern size fluctuation.
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