Debs 2010 context based computing tutorial

Context Aware Computing and its Utilization in Event-based Systems DEBS 2010 Tutorial Opher Etzion (opher@il.ibm.com) Ella Rabinovich (ellak@il.ibm.com)

Our entire culture is context sensitive In the play “The Tea house of the August Moon” one of the characters says: Pornography question of geography This says that in different geographical contexts people view things differently Furthermore, the syntax of the language (no verbs) is typical to the way that the people of Okinawa are talking When hearing concert people are not talking, eating, and keep their mobile phone on “silent”.

Our IT systems are catching up Context is becoming a first class citizen in computing Gartner has designated Context enriched services and Context delivery architecture as Part of its application integration Hype Cycle of 2009

This tutorial’s agenda Part I: Context in general Introduction – context in pragmatics and language Roles of contexts in computing Introduction contexts in event processing Part II: Context in depth Introduction to Context categories Temporal context Segmentation context BREAK Spatial context State contexts Context composition Part III: Context in practice Operational semantics of context Context implementation in practice in event processing Context implementation in other computing areas Conclusion

Context in language and pragmatics

Context in language – why are we laughing from jokes? A man walks in the street with a duck, his friend approaches him Friend: why are you walking with a duck? Man: I went out of home and this duck followed with me and doesn’t leave me alone Friend: take him to the zoo Next day the same man still walks in the street with a duck, his friend approaches him again Friend: why haven’t you taken the duck to the zoo? Man: I took him to the zoo, cinema, pub– he still doesn’t leave me alone Where is the context switch?

Another joke example Four researchers are exploring the jungle, and are captured by a tribe of cannibals The chief of the tribe said: we shall eat this one today, this one tomorrow, and this one the day after His deputy asks: what about the blond Guy? The chief answers: we shall release him, since he helped me preparing to the PhD qualification exam in MIT

The context switch principle The cannibals are wild The cannibal chief has PhD from MIT

Meaning disambiguation by context The table? “ The” is always within context

Some parts of the language affected by context Addressing people Request form Code switching for multi-lingual people Discourse context – e.g. shared experience

Context as “behavior selection” In some countries I carry money in my wallet, in other countries I hide the money under my clothes When the radio tells me about a traffic jam in the highway I take an alternative route If I am getting a request from an important person I re-arrange my priorities to handle it first (otherwise I put it in a queue) A Jewish person who observes the religious laws does not eat diary food within six hours from the time of eating meat I need to get to a certain address in Sidney using public transportation, I am looking for fastest way (train, bus, boat) Spatial Context State-oriented Context Segmentation Context Temporal + segmentation Context Spatial + temporal + state-oriented context

Context in pragmatics – travelling in Sydney Request Determine Context Select Service Take me to address X Requester is now in location Y; no car; has daily ticket for all public transport; it is rush hour Selected alternative

Roles Of Context In Computing Context in the world of software: A major step towards modeling the real world functional behavior Most of the software considers only direct information Context-aware software acts also upon (indirect) relevant information, which represents the conditions under which the processing is done Examples Automatic tow service ordering system Calls routing application “ Context-aware computing is the concept of leveraging information about the end user to improve the quality of the interaction” (Gartner 2007)

Software Architecture in the Context of History Era of the Mainframe OLTP Batch Agility of Enterprise IT 1960s 1980s 1970s 1990s 2000s 2010s Era of the Server Two-tier Era of the Web SOA Three-tier CoDA Era of Context Presence Mobility Web 2.0 Social computing Time 2020s Advanced SOA = event-driven SOA CoDA = Context-driven Architecture Web Web Services Multi-channel PC LAN Server Internet Advanced SOA XTP CEP S/360 SNA Mainframe (Gartner 2007)

Context-aware Computing Context (indirect relevant information) Service Input (direct imperative information) Data stores Web feeds Services Events Sensors Queues Logs

Context Applications Telecommunication GeoVector applications Smart phones users can find out when the museum opens, find an ATM on the way home, ask for a coupon, make a purchase by simply pointing the mobile device at the desired direction or object Smart call routing systems Routing phone calls based on the user’s location and pre-defined preferences At home – wire line phone At office – IP phone or instant messaging application At the movie theater – SMS only

Context Applications – cont. Social computing Google search and advertising Improving search relevance, and placement of advertisements according to context Amazon B2C offers the user the most-relevant experience in e-commerce by using: History of a user's activity and his location, current activities by other relevant users, political and social news environment Facebook bases its service offering on user’s context Content a user creates, seeks and finds depends on his social context: identity, memberships, and the power of his connections to other members

Introduction to context in event processing

Context has three distinct roles (which may be combined) Partition the incoming events The events that relate to each customer are processed separately Grouping events together Different processing for Different context partitions Determining the processing Grouping together events that happened in the same hour at the same location

Contextual representation of event Spatial coordinates System entry point Detection time Occurrence time

Introduction to context categories

Context Definition A context is a named specification of conditions that groups event instances so that they can be processed in a related way. It assigns each event instance to one or more context partitions . A context may have one or more context dimensions. Temporal Spatial State Oriented Segmentation Oriented

Context Types Examples Spatial State Oriented Temporal Context “ Every day between 08:00 and 10:00 AM” “ A week after borrowing a disk” “ A time window bounded by TradingDayStart and TradingDayEnd events” “ 3 miles from the traffic accident location” “ Within an authorized zone in a manufactory” “ All Children 2-5 years old” “ All platinum customers” “ Airport security level is red” “ Weather is stormy” Segmentation Oriented

Context Types Context Fixed location Entity distance location Event distance location Spatial State Oriented Fixed interval Event interval Sliding fixed interval Sliding event interval Temporal Segmentation Oriented

Context Building Block Context identifier Context dimension Context type Context parameters Context initiator policies Building Block Describing Context Context Details Explicit Partitions Partition identifier Partition parameters Composition Details Relationships Member contexts Priority Order Location service global state

Temporal Context Events grouping - group events to process them together based on the fact they have occurred during the same interval Example: count all the bids within the auction period EPA applicability - indicate that a certain event processing agent is applicable within certain intervals and is not applicable in other intervals. Example: detect if all printers at the same floor are off-line during working hours. Temporal interval is a half open interval [Ts, Te) Ts is start-point, included in the interval Te is end-point, not included in the interval Temporal context is aimed to partition the temporal space into time intervals.

Fixed Interval Fixed interval Interval start Interval end Recurrence Temporal ordering In a fixed interval context each window is an interval that has a fixed time length; there may be just one single window or a periodically repeating sequence of windows. July 12, 2010, 2:30 PM + 3 hours 08:00 10:00 08:00 10:00 08:00 10:00

E vent Interval In an event interval context each window is an interval that starts when the associated EPA receives an event that satisfies a specified predicate. It ends when it receives an event that satisfies a second predicate, or when a given period has elapsed. Event interval Initiator event list Terminator event list Expiration time offset Expiration event count Initiator policy Terminator policy Temporal ordering Patient’s admittance Patient’s release Earthquake From patient’s admittance to patient’s release + 3 days Within 3 days from an earthquake

Sliding Fixed Interval In a sliding fixed interval context each window is an interval with fixed temporal size. New windows are opened at regular intervals relative to one another. Sliding fixed interval Interval period Interval duration Interval size (events) Temporal ordering 2 hours 2 hours 2 hours 1 hour 1 hour 1 hour

Sliding Event Interval A sliding event interval is an interval of fixed size (events number) that continuously slides on the time axis. Sliding event interval Event list Interval size (events) Event period Temporal ordering Every 3 blood pressure measurements

Context Initiator Policies Within three days of an volcano eruption: initiator event = volcano eruption, expiration time offset = + 3 days March 5, 2010 10:00 March 7, 2010 06:00

Context Initiator Policies – cont. A context initiator policy is a semantic abstraction that defines the behavior required when a window has been opened and a subsequent initiator event is detected. add ignore refresh extend

Context Terminator Policies Starting with Island volcano eruption till full flight resumption initiator event = volcano eruption, terminator event = flights resumption

Context Terminator Policies – cont. A context terminator policy is a semantic abstraction that defines the behavior required when several windows have been opened by subsequent initiators. first last all

Temporal Ordering Policy Determine whether a specific event falls within the interval: By the detection time - the timestamp created by the system when the event enters the system By the occurrence time - the time in which the event source specifies as the time in which the event occurred in reality May 1, 2010, 11:45:00 AM May 1, 2010, 11:45:00 AM

Segmentation Oriented Context A segmentation-oriented context assigns events to context partitions based on the values of one or more event attributes, either using the value of these attributes to pick a partition directly, or using predicate expressions to define context partition membership. Segmentation-oriented Attribute list Partition identifier Partition expression Unrestricted number of partitions Segmentation by CustomerId Fixed number of partitions Segmentation by different age ranges age < 21 age  30 and age < 50 age  50 and age < 67 age  67

Segmentation Oriented Context – cont. Unrestricted number of partitions: Average of customer’s deposits over last month John Tim Helen David

Segmentation Oriented Context – cont. Fixed number of partitions Distribution of alcohol consumption by age 18-25 26-50 50-

Fixed location A f ixed location context has predefined context partitions based on specific spatial entities. An event is included in a partition if its location attribute indicates that it is correlated with the partition’s spatial entity. Relations between the event’s location and the context entity’s location An event is classified to a context partition if satisfy a spatial relationship with fixed entity

Fixed location examples A person enters the house: The house location is an area, the person’s location is a point; the relation is touches A car parks across two lanes The car parked location is an area, the lane is an area; the relation is overlaps An Alzheimer patient has gone outside of the safe zone defined by his family. His location is a point, the zone is an area; the relation is disjoint

Entity Distance Location An entity distance location context assigns events to context partitions based on their distance from a given entity. This entity is either specified by an event attribute or is given as part of the context specification Entity d1 d2

Entity distance location examples A driver enters the restaurant’s interest context when arriving to a certain radius from the restaurant A bus is within the context of a certain bus station if it is within a certain distance from the station

Event Distance Location An event distance location context assigns events to context partitions based on their distance from the location of the event that triggered the creation of the partition. d1 d2

Event distant location example A fire breaks within a certain radius from the earthquake epicenter The distance space is partitioned, different actions for different partitions A suspect fits the criminal’s profile is arrested within a certain radius from the crime scene

Where states are coming from? Explicit state machines Observation in Workflow/BPM State of some entity Typically stored in DB/ global variable

State examples When the CPU is overloaded When a backup is running When a person is presenting When the mood in Wall Street is bullish.

The temporal aspects of state Occurs while a state is valid? The “while” may be determined by detection time or by occurrence time If the state is – raining, Then it makes sense that the association of events is determined according to occurrence time If the state is – CPU is overloaded Then it makes sense that events that result in further processing are associated according to their detection time.

Composite context A composite context is a context that is composed from two or more contexts. Example: the set of context partitions for the composite context is the Cartesian product of the partition sets of its constituent contexts.

Composition of context – some observations: The most common combination is: segmentation and temporal The relations between the composed contexts can be – union or intersection (intersection is the more common) There may be multiple composition participants In some cases a priority is needed to disambiguate the context affiliation State: rainy union Temporal: every day between midnight and 6am Segment: customer Temporal: Every 10 orders Segment: driver Temporal: Within 1 hour from an accident Spatial: within 5KM from the accident Segment: customer Temporal: Every 10 orders

Priorities in event composition Temporal: Every 10 orders Segment: customer First create group of 10 orders and this group by customer The temporal context has higher priority

Priorities in event composition Segment: customer Temporal: Every 10 orders First group of by customer and then count 10 orders for each customer The segmentation context has higher priority

Operational semantics of context

Context in Applications Currently in most applications the context logic is embedded in the traditional code. No separation of concerns resulting in: No reuse of context logic Change management is troublesome and non-efficient Increased application maintenance cost Reduced business agility Application Context

Context Decoupling Externalizing the rapidly-changing context logic from the traditional application code leads to: Increased flexibility and adaptability Better reflection of business policies on business logic All building blocks are explicitly defined Reduced application development and maintenance time, as well as costs Application Context

Introducing Context Service Context is a logical component in EPN Context service is a runtime component implementing and managing the context

The Role of Context Service Initiation of new context’s partitions Terminating of existing context’s partitions Deciding on affiliation of an object instance to a certain partition Based on the partition attributes Based on the object attributes Context service manages the active contexts lifecycle Context service context 2 EPA 1 EPA 2 Partitions EPA 1 Partitions Context 1 Context 2 Context 3 EPA 1 EPA 2 Partitions context 1 Context service

Context Service – Points for Consideration Context partitions and event instance management Architecture for the context service Centralized vs. distributed architecture

Partition and Event Instance Management The role of managing the content in each of the partitions can either fall on the context service the agent (EPA) associated with the specific context In case the context service is managing the partition’s content: In case the agent is managing the partition’s content: E1 ,E2, E3 EPA 1 EPA 2 Partitions Context 1 E1,E2 E3 Context service Agent Pattern evaluation E1,E2 E1 ,E2, E3 Agent Pattern evaluation EPA 1 EPA 2 Partitions Context 1 Context service E1,E2 E3

Centralized vs. Distributed Architecture Should take into consideration some functional and non-functional requirements Functional requirements Correctness of initiator/terminator/participant semantics Non functional requirements Performance, scalability, reliability

Centralized Context Service Performance bottleneck Non scalable in terms of throughput and number of agents Agent Context service Agent Agent Agent

Distributed Context Service on Agent’s Level Managing shared context in a completely distributed environment Requires devising control mechanisms to communicate the changes in shared context state to all interested parties Agent Context service Agent Context service Agent Context service Agent Context service Agent Context service

Hybrid Approach Hybrid approach – distributed context service on the system’s level Context service – one per one runtime engine The context state is shared between distributed instances of the context service Agent Context service Agent Context service Agent Context service Context state

Context Implementation in Practice: Event Processing Implementations

Context in Practice - Streambase CREATE WINDOW tenSecondsInterval ( SIZE 10 ADVANCE 1 {TIME} ); CREATE WINDOW eventsInterval ( SIZE 10 ADVANCE 1 {TUPLE} TIMEOUT 20 ); Sliding fixed interval Sliding event interval

Context in Practice – Oracle EPL SELECT * FROM Withdrawal RETAIN 5 EVENTS SELECT * FROM Withdrawal RETAIN 4 SECONDS

Context in Practice –Sybase (Aleri/Coral8) CCL CREATE WINDOW Book_w SCHEMA Book_t KEEP ALL ; INSERT INTO Book_w SELECT * FROM Book_s; The KEEP policy specifies the kind of window. Here are some examples: KEEP LAST PER Id KEEP 3 MINUTES KEEP EVERY 3 MINUTES KEEP UNTIL (”MON 17:00:00”) KEEP 10 ROWS KEEP LAST ROW KEEP 10 ROWS PER Symbol

Context in Practice – Progress Apama

Context in Practice – AMiT A key is a collection of event attributes that are used to match different events. These attributes must have syntactic compatibility, and are usually semantically equivalent. OrderId Key String CustomerOrder OrderId CustomerOrderCancel OrderId OrderDelivery Id OrderShipmentReport Number

Context in Practice – AMiT A lifespan is a time interval during which pattern detection is relevant – temporal context. A lifespan is bounded by an initiator and a terminator . Initiator – beings the lifespan. The initiator can be an event, absolute time, startup (CEP engine startup). A lifespan can use more than one initiator Terminator – ends the lifespan. The terminator can be event, expiration time, absolute time, or no-terminator. A lifespan can use more than one terminator

Contexts implementations in other types of computing

Data in context Contextual data: Temporal database: transaction time, valid time Spatial database: geographic abstraction Spatio-temporal database: intersection of these two

ContextPhone http://www.cs.helsinki.fi/group/context /

MIT Media Lab – context in kitchen appliances The Context-Aware Computing group is focused on demonstrating the possibilities for controlling systems with interpreted human intention. The goal is to demonstrate how “context” such as who we are, what we are doing, where we are doing it, why we might be doing it, and when it should be done can simplify our ability to control systems. http://context.media.mit.edu/press/index.php/about/

MIThril – context aware wearable computing http://www.media.mit.edu/wearables/mithril/ Based on sensing and machine learning – context engine and wearable sensors and processors

Sixth sense http://www.media.mit.edu/research/highlights/sixthsense-wearable-gestural-interface-augment-our-world

Context and websites Contextualization of websites: making them appear in searches of certain category (reverse engineering of the search engine algorithms) Using the user’s context to generate results Contextualization of websites: making them appear in searches of certain category (reverse engineering of the search engine algorithms)

IBM Entity Analytics – context acquisition by dependencies Good Guys Subjects of Interest Hotel guests Loyalty club enrollment Employees Vendors Victims Specially designated nationals Excluded persons Gaming license revocations Known cheaters Interpol FBI Most Wanted

Context Separation of context from the logic Next phase of abstraction independence BPM and rules provided separation between programming in the large and programming in the small Databases provided data independence

Context is: One of the key building blocks in event processing modeling A language construct that starts to appear in event processing languages An emerging concept in enterprise computing

Debs 2010 context based computing tutorial

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