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Mobile Computing and Databases –A Survey Daniel Barbar á. Pallavi Phene [email protected] November 12 th , 2002. “People and their machine should be able to access information and communicate with each other easily and securely, in any medium or combination of media—voice,

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Mobile computing and databases a survey daniel barbar l.jpg

Mobile Computing and Databases –A SurveyDaniel Barbará

Pallavi Phene

[email protected]

November 12th, 2002


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“People and their machine should be able to

access information and communicate with

each other easily and securely, in any

medium or combination of media—voice,

data, image, video, or multimedia—any time,

anywhere, in a timely, cost-effective way”

Dr. George H. Heilmeier

IEEE Communication Mag.

October 1992


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MANETsMobile Ad-hoc NETworks

Networks formed by Wireless, Mobile hosts without (necessarily) using a pre-existing infrastructure.


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Problems

a) Routes between nodes may potentially contain multiple hops


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Problems

b) Hidden Terminal Problem

C

A

B


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Problems

c) Near Far Problem

Near-by terminals over power signals from far-away terminals

BS

A

B

C


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Problems

d) Hand-offs

Base Stations (BS)

Mobile Host (MH)


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Effect of Mobility

  • Physical Layer

    • Channel varies with user location and time

  • Data Link Layer

    • Reliable communication interrupted by bursts

  • Network Layer

    • Re-routing due to movement of hosts

  • Presentation Layer

    • Source coding for efficiency

  • Application Layer

    • Location Dependent Applications


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Mobile Computing

“In mobile networking, computing activities are not disrupted when the user changes the computer's point of attachment to the Internet. Instead, all the needed reconnection occurs automatically and non-interactively.”

Charles E. PerkinsSun Microsystems


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Outline

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges



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Outline

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Characteristics of Wireless Networks

  • Asymmetry in Communications

  • Frequent Disconnections

  • Power Limitations

  • Screen Size


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Outline

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Mobile Computing and Databases

  • Asymmetry & Power Limitations

    • Data Dissemination

  • Asymmetry & Frequent Disconnections

    • Transaction Mgmt and Data Consistency

  • Frequent Disconnections

    • Location Dependent Querying

  • Screen Size

    • Interface for Browsing


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Outline

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Data Dissemination

It is a push-based model for broadcasting data to the client rather than waiting for the client to request the specific data.


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Data Dissemination

  • Advantage

    • no interruptions by the client requests;

    • send additional related data;

  • Disadvantage

    • figuring out the “relevant” additional data

  • Depends

    • On ability of the server to predict the clients’ needs


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Types of push-architectures

  • Periodic Push

    • delivery is performed on a regular, repeating schedule

    • client can disconnect and still not lose data

  • Aperiodic Push

    • has no such schedule

    • assumes that clients are either always listening and able to respond to what is being sent

    • makes more effective use of the downstream communication channel


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Methods of Data Dissemination

  • Broadcast Disks

  • Interleaved Push and Pull (IPP)

  • Invalidation Reports (IR)


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Broadcast Disks

  • It is a periodic dissemination architecture

  • Multiple disks of different sizes are superimposed on the broadcast medium (Server Broadcast Programs)

  • Exploits the client storage resources for caching data (Client Cache Mgmt)


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Server Broadcast Programs

  • Server takes the union of required items (pages) and broadcasts the resulting set cyclically.

  • Number of disks (num_disks) determine the number of different frequencies with which pages will be broadcast.

  • For each disk, the number of pages (num_pages(i)) and the relative frequency of broadcast (rel_freq(i)) are specified.


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An Example

  • num_disks = 3

  • Disk 1

    • num_pages(1) = 1

    • rel_freq(1) = 4

  • Disk 2

    • num_pages(2) = 2

    • rel_freq(2) = 2

  • Disk 3

    • num_pages(3) = 8

    • rel_freq(3) = 1


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Client Cache Management

  • Clients cache the pages for which the local probability of access is higher than the frequency of broadcast.


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Interleaved Push and Pull (IPP)

  • Integration of a pull-based and a push-based Broadcast Disk approach.

  • Communication Bandwidth shared between 2 Channels

  • Front-Channel

    • used by servers for push-based operations i.e. for maintaining Broadcast disks and providing responses to client pull operations

  • Back-Channel

    • used by clients for pull-based operations


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Improving Scalability of IPP

  • Adjusting pull bandwidth

  • Providing a Pull threshold

  • Increase available pull bandwidth by chopping off the slowest part of the broadcast schedule


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Invalidation Report (IR)

  • The server uses IRs to notify clients about changes in the items being cached by the clients

  • IRs contain only the changes in the data values; Static/unchanged data is not re-sent

  • IRs Can cause “false-negatives”

  • “Quasicopies” and “adaptive IRs” may be used


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Broadcast Disks the clients cache using GCoRe (Group with Cold Update-Set Retention)in Real-Time Environments

  • Real-time environments are time-critical

  • Broadcast disks do not accommodate transmission failures

  • Require a technique to add reliability to the Broadcast Disks technique

  • Organizations suitable for RT environments

    • Flat

    • Rate Monotonic

    • Slotted Rate Monotonic


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Organization of Broadcast Disks to Ensure Fault Tolerance the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Achieved using AIDA (Adaptive Information Dispersal Algorithm), which is an elaboration of IDA (Information Dispersal Algorithm)

  • AIDA uses minimum controlled redundancy to guarantee timeliness and fault tolerance up to any degree of confidence


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IDA the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Divides a file into N independent pieces, such that combining any m pieces is sufficient to retrieve the file

Dispersal and Reconstruction of Information using IDA


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AIDA the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • In AIDA a bandwidth allocation operation is inserted after the dispersal operation but prior to transmission

  • This allows the system to scale the amount of redundancy used in the transmission

  • Number of pieces transmitted n is allowed to vary from m (no redundancy) to N (maximum redundancy)

  • Using bandwidth allocation, the redundancy of unimportant items can be reduced and that of critical items increased


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AIDA the clients cache using GCoRe (Group with Cold Update-Set Retention)

Dispersal and Reconstruction of Information using AIDA


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An Example of a Flat Broadcast Program the clients cache using GCoRe (Group with Cold Update-Set Retention)


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Another Consideration: Directories the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Indexing on Air

    • transmitting index of what data items are being broadcast

  • Advantage

    • allows clients to be inactive some of the time and hence save power

  • Distributed Indexing

    • sending only part of the Index

  • Methods of Distributed Indexing

    • Temporal Addresses

    • Multicast Addresses


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Outline the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Data Consistency the clients cache using GCoRe (Group with Cold Update-Set Retention)

“Consistency requires that data bound by a transaction be semantically preserved.”


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Session Guarantees the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Read Your Writes

    • Any read operation in the session must reflect the values established by previous writes in that session

  • Monotonic Reads

    • Successive reads reflect a non-decreasing set or writes

  • Writes Follow Reads

    • Writes are propagated after the reads on which they depend

  • Monotonic Writes

    • Writes are propagated after writes that logically precede them


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Maintaining Data Consistency the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Certification Reports

  • Isolation Only Transaction (IOT)

  • Data Replication


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Certification Reports the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Are used to support transaction management in mobile environments

  • CRs contain lists of items that are in the read and write set of active transactions

  • CRs are used by the clients to verify if the transactions being run by them need to be aborted

  • The server completes the verification only when the client cannot detect any conflict

  • If the transaction can commit, then the server will put the values in the database and notify the client


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Isolation Only Transactions(IOT) the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Guarantees only Consistency of Databases

  • When the transaction completes, it enters either a committed or pending state.

  • If in committed state, then the results are sent to the servers to be committed

  • If in pending state, the transactions is in wait state and is validated later


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Data Replication the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Required so that processing continues smoothly in case of disconnections

  • Technique requires referee nodes that update and store the core (updateable data items) set descriptions

  • Other issues

    • maintaining replication of directories (Primary by Row)

    • replication in weakly connected systems (Lazy Release Consistency)


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Outline the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Location Dependent Querying the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Ad-hoc queries will be addressed to large databases

    • regarding the local area

      • e.g.: people, places, routes, services etc

    • location transparent

      • e.g.: recent sales figure of a particular product, who stores a particular product on his PDA etc.


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  • Problem the clients cache using GCoRe (Group with Cold Update-Set Retention)

    • Minimizing communication cost to retrieve the query result

  • Solutions

    • integrate GPS into IP to enable creation of location independent services

    • e.g. Genesis, Advanced Traveler Information Systems (ATIS), Mobisaic (using Dynamic URLs and Active Documents)


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Outline the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Interfaces for Browsing the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Query by Icons (QBI)

    • query processing facility supporting exploration and querying of databases from a mobile computer based on the manipulation of icons

    • addresses the screen size, memory and battery power, communication bandwidth limitations

    • Features

      • Iconic visual language

      • Semantic Data Model

      • Meta-query tools


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Architecture of QBI the clients cache using GCoRe (Group with Cold Update-Set Retention)


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QBI Interface the clients cache using GCoRe (Group with Cold Update-Set Retention)


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Query Example the clients cache using GCoRe (Group with Cold Update-Set Retention)


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Outline the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Characteristics of Wireless Networks

  • Mobile Computing and Databases

  • Data Dissemination

  • Data Consistency

  • Location Dependent Querying

  • Interfaces for Browsing

  • Challenges


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Challenges the clients cache using GCoRe (Group with Cold Update-Set Retention)

  • Prototyping

  • Bandwidth Utilization

  • Transactional Properties

  • Optimization of Location Dependent Query Processing

  • Data Visualization


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Thank You! the clients cache using GCoRe (Group with Cold Update-Set Retention)


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