Mobile Databases

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• Mobile Databases

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Mobile computing

• Portable computing devices and wireless
  communications
• Can access data from anywhere, anytime
• Example
• Brokerage services
• News reporting
• Traffic/Vehicle services

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Mobile DB

• Mobile database data management technology
  enabling use of databases on mobile computing
  environment
• Data available anywhere independent of
  availability of fixed network
• Can access public data using internet browser
• Can access private data through distributed DB
• Data on mobile and fixed hosts sharable in
  seamless way
• More complex techniques needed to support this
  distributed transaction processing, commit

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Identifying Mobile characteristics

• Problems more challenging
• Asymmetric communication bandwidth
• Limited and intermittent connectivity
• Limited life of power supply of mobile units
• Changing topology of network
• Origins in distributed systems
• Mobile database assumes a traditional database
  requiring ACID properties

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Mobile databases

• How to guarantee ACID properties
• Environment requires new strategies for
• Processing transactions
• Concurrency control caching, locking
• Data dissemination
• Querying location dependency

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Mobile Computing Architecture

• Mobile units MU or Mobile Hosts MH
• Fixed hosts FH on fixed network
• Base Station BS serves as gateway to fixed and
  wireless network
• Geographic mobility domain divided into cells
• Mobile host wireless connection to BS of cell
• Movement of mobile units unrestricted
• Must maintain info for access contiguity

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Mobile DB

• Mobile DB mix of fixed and wireless network
• DBS distributed among wired and wireless
  components
• Data management shared among base stations, fixed
  hosts and mobile units
• MU can be data client and/or data server
• If a server, with DBMS functionality

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DB
DB
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Mobile DB

• When Mobile DB mix of fixed and wireless network
• Fixed FH location, high capacity, reliability,
  low connection cost
• Wireless support dynamic network topology, low
  capacity, reliability, high connection cost

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Transaction

• What is a transaction?
• A Transaction is not always just an SQL query
• A transaction is also
• From the time you login to SQL Plus until you
  exit

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Mobile strategies

• Provide data cache on mobile host
• Cache replicas of frequently accessed data
• Work offline
• Reduce power consumption
• Client may be unreachable
• Dozing - energy conserving state
• Out of reach
• Proxies used for unreachable (e.g. update info)
• What if data cached updated during disconnection?

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Mobile strategies

• Resources of MU can be limited
• Mobile hosts personalized
• Bring in fraction of data need to access
• MU has low security
• Mobile DBs high degree of unavailability
• Broadcasting accepted way to disseminate data

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Mobile DB - Conservative

• Can assume entire DB distributed among wired
  components
• Full or partial replication
• Base station or fixed host has DBMS functionality
• Must be able to locate mobile units
• Need query and transaction management features
  for mobile environment

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Mobile DB - Conservative

• How is this different from distributed
  non-mobile?
• Difficult to maintain sustained connection to
  server
• Database server typically is stateless,
  especially under broadcast systems
• Mobile clients often cannot maintain a sustained
  network connection

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MANET Extreme DB

• Mobile adhoc networks
• MUs do not need to communicate via a fixed
  network
• In MANET, MU responsible for routing own data,
  acting as BS
• Must be able to handle changes in network topology

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MANET Extreme DB

• Peer-to-peer
• No central control
• Difficult for transaction processing and data
  consistency
• Example applications
• Multi-user games
• Shared white-boards
• Battle information sharing
• Distributed calendars

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Mobile DBs Best of both

• Alternatively assume DB distributed among wired
  and wireless components
• What if MU has DBMS functionality?
• MU can be laptop
• Data management shared among base stations, fixed
  hosts and mobile units
• More interesting problems!! But solvable

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• Assume best of both Mobile DBs for next few
  topics to consider problems/solutions

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Data Management Issues

• Environment requires new strategies for
• Querying location dependency
• Concurrency control
• Processing transactions
• Security
• Data dissemination
• Recovery/fault tolerance

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Query processing

• Must know location of data
• Query optimization more difficult because of
  mobility and resource changes of MU
• MU may be in transit or may cross cell boundaries

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Location-based services

• Location dependent cache information may become
  stale
• Frequently updated location dependent queries
• Apply spatial queries to refresh cache problem

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Transaction models

• Mobile transaction may execute on several BSs
• Central coordination lacking if data distributed
  among wireless components
• Long lived transactions
• ACID properties difficult to guarantee
• Can add proxies for unreachable components
• Proxies keep track of updates to cache

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Data distribution and replication

• Data unevenly distributed among BS and MU
• To compensate for high latency and unreliable
  connectivity
• Frequently accessed data is cached
• Can work offline if necessary
• Consistency constraints and cache management

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Recovery and Fault tolerance

• Site, media, transaction and communication
  failures
• Voluntary shutdown not a site failure
• Transaction failures can occur during handoff

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Security

• Mobile data less secure than data at fixed
  location
• Data is more volatile
• Must manage and authorize access to critical data

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Data Dissemination -Broadcasting

• Assumptions
• Requests are read-only (Most are)
• Because of latency, server can handle fewer
  clients in same amount of time
• Broadcasting acceptable solution
• Scalable single broadcast of data item can
  satisfy all outstanding requests for data item

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Data Dissemination -Broadcasting

• Assumptions
• Requests are read-only (Most are)
• Because of latency, server can handle fewer
  clients in same amount of time
• Broadcasting acceptable solution
• Scalable single broadcast of data item can
  satisfy all outstanding requests for data item

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Broadcasting

• Broadcast-based data dissemination approaches
• Push-based data broadcasting
• Pull-based data broadcasting
• Hybrid data broadcasting

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Push-based broadcasting

• Data contents within a file or database are
  repeatedly broadcast through the broadcast
  channel
• channel becomes a disk
• clients can retrieve data as it goes by
• expected wait time for a data item is the same

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Flat broadcasting
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Broadcast Disks

• broadcast data in different frequencies according
  to their relevant importance
• multi-level memory hierarchy
• hot data are broadcast more frequently then cold
  data
• Data with similar access frequency are grouped
  into disks

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Server Broadcast Program
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Pull-based broadcast

• also called adaptive approaches
• data items are broadcast on-demand
• only requested data will appear as data on air

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Pull-based

• Data broadcasting is prioritized according to
  some metrics
• Most common algorithms are
• First come First Served (FCFS) broadcasts the
  pages in the order they are requested.
• Most Requests First (MRF) broadcasts the page
  with maximum number of pending requests.
• Longest Wait First (LWF) selects the page that
  has the largest total waiting time, i.e., the sum
  of the time that all pending request for the item
  have been waiting. (RW is approximation)

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Pull-based

• MRF best response time at high system loads and
  page requests uniformly distributed
• LWF best response time when page request
  distributed by Zipf

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Hybrid data Broadcasting

• mixes both push and pull
• clients to send pull requests for misses on the
  backchannel
• server supports a Broadcast Disk plus interleaved
  responses to the pulls on the front channel
• alleviate the problem of excessively long waiting
  time for some data

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Indexing

• Clients can save battery power by turning into
  active mode only when interested data are
  broadcast
• (1, m) index method (Imielinski, et al. )
• Index is broadcast m times during the broadcast
  of one version of the file

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Related Research Indexing (cont.)
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Data Consistency

• Assumption Read and Write transactions
• Challenges in mobile environments
• Difficult to maintain sustained connection to
  server
• Database server typically is stateless,
  especially under broadcast systems
• Mobile clients often cannot maintain a sustained
  network connection
• How to ensure conflict serializability?

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Research in Data Consistency

• Assumptions
• Read and Write transactions
• MU has DBMS functionality
• Mobile unit may often experience
  voluntary/involuntary disconnections
• Then, it can only read and update data copied
  onto their local cache
• What if data cached updated during disconnection?