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Advanced Operating Systems

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Advanced Operating Systems Lecture 12: Naming in Distributed Systems University of Tehran Dept. of EE and Computer Engineering By: Dr. Nasser Yazdani – PowerPoint PPT presentation

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Title: Advanced Operating Systems


1
Advanced Operating Systems
Lecture 12 Naming in Distributed Systems
  • University of Tehran
  • Dept. of EE and Computer Engineering
  • By
  • Dr. Nasser Yazdani

2
Covered topic
  • Naming system in DS.
  • References
  • Chapter 5 of the text book
  • Chord

3
Outline
  • What is Naming
  • DNS
  • X.500
  • Mobility
  • Challenges.

4
Naming
  • Names are used to share resources, uniquely
    identify entities and refer to locations
  • Need to map from name to the entity it refers to
  • E.g., Browser access to www.cnn.com
  • Use name resolution
  • Differences in naming in distributed and
    non-distributed systems
  • Distributed systems naming systems is itself
    distributed
  • How to name mobile entities?

5
Learning objectives
  • To understand the need for naming systems in
    distributed systems
  • To be familiar with the design requirements for
    distributed name services
  • To understand the operation of the Internet
    naming service - DNS
  • To be familiar with the role of discovery
    services in mobile and ubiquitous computer systems


6
The role of names and name services
  • Resources are accessed using identifier or
    reference
  • An identifier can be stored in variables and
    retrieved from tables quickly
  • Identifier includes or can be transformed to an
    address for an object
  • E.g. NFS file handle, Corba remote object
    reference
  • A name is human-readable value (usually a string)
    that can be resolved to an identifier or address
  • Internet domain name, file pathname, process
    number
  • E.g ./etc/passwd, http//www.cdk3.net/
  • For many purposes, names are preferable to
    identifiers
  • because the binding of the named resource to a
    physical location is deferred and can be changed
  • because they are more meaningful to users
  • Resource names are resolved by name services
  • to give identifiers and other useful attributes


7
Requirements for name spaces
  • Allow simple but meaningful names to be used
  • Potentially infinite number of names
  • Structured
  • to allow similar subnames without clashes
  • to group related names
  • Allow re-structuring of name trees
  • for some types of change, old programs should
    continue to work
  • Management of trust


8
Naming Concepts
  • Name
  • What you call something
  • Address
  • Where it is located
  • Route
  • How one gets to it

What is http//www.isi.edu/dongho ?
  • But it is not that clear anymore, it depends on
    perspective. A name from one perspective may be
    an address from another.
  • Perspective means layer of abstraction

9
Things we name
  • Users
  • To direct, and to identify
  • Hosts (computers)
  • High level and low level
  • Services
  • Service and instance
  • Files and other objects
  • Content and repository
  • Groups
  • Of any of the above

10
How we name things
  • Host-Based Naming
  • Host-name is required part of object name
  • Global Naming
  • Must look-up name in global database to find
    address
  • Name transparency
  • User/Object Centered Naming
  • Namespace is centered around user or object
  • Attribute-Based Naming
  • Object identified by unique characteristics
  • Related to resource discovery / search / indexes

11
Namespace
  • A name space maps
  • S X e O
  • At a particular point in time.
  • The rest of the definition, and even some of the
    above, is open to discussion/debate.
  • What is a flat namespace
  • Implementation issue

12
Scalability of naming
  • Scalability
  • Ability to continue to operate efficiently as a
    system grows large, either numerically,
    geographically, or administratively.
  • Affected by
  • Frequency of update
  • Granularity
  • Evolution/reconfiguration
  • DNS characteristics
  • Multi-level implementation
  • Replication of root and other servers
  • Multi-level caching

13
Name Spaces (1)
  • Hierarchical directory structure (DAG)
  • Each file name is a unique path in the DAG
  • Resolution of /home/steen/mbox a traversal of the
    DAG
  • File names are human-friendly.

14
Linking and Mounting (1)
  • The concept of a symbolic link explained in a
    naming graph.

15
Linking and Mounting (2)
  • Mounting remote name spaces through a specific
    process protocol.

16
Linking and Mounting (3)
  • Organization of the DEC Global Name Service

17
Resolving File Names across Machines
  • Remote files are accessed using a node name, path
    name
  • NFS mount protocol map a remote node onto local
    DAG
  • Remote files are accessed using local names!
    (location independence)
  • OS maintains a mount table with the mappings

18
Name Space Distribution
  • Naming in large distributed systems
  • System may be global in scope (e.g., Internet,
    WWW)
  • Name space is organized hierarchically
  • Single root node (like naming files)
  • Name space is distributed and has three logical
    layers
  • Global layer highest level nodes (root and a few
    children)
  • Represent groups of organizations, rare changes
  • Administrational layer nodes managed by a single
    organization
  • Typically one node per department, infrequent
    changes
  • Managerial layer actual nodes
  • Frequent changes
  • Zone part of the name space managed by a
    separate name server

19
Name Space Distribution (1)
  • An example partitioning of the DNS name space,
    including Internet-accessible files, into three
    layers.

20
Name Space Distribution (2)
Item Global Administrational Administrational Managerial
Geographical scale of network Worldwide Worldwide Organization Department
Total number of nodes Few Few Many Vast numbers
Responsiveness to lookups Seconds Seconds Milliseconds Immediate
Update propagation Lazy Lazy Immediate Immediate
Number of replicas Many Many None or few None
Is client-side caching applied? Yes Yes Yes Sometimes
  • A comparison between name servers for
    implementing nodes from a large-scale name space
    partitioned into a global layer, as an
    administrational layer, and a managerial layer.
  • The more stable a layer, the longer are the
    lookups valid (and can be cached longer)

21
Implementation of Name Resolution (1)
  • Iterative name resolution
  • Start with the root
  • Each layer resolves as much as it can and returns
    address of next name server.

22
Implementation of Name Resolution (2)
  • Recursive name resolution
  • Start at the root
  • Each layer resolves as much as it can and hands
    the rest to the next layer

23
Which is better?
  • Recursive name resolution puts heavy burden on
    global layer nodes
  • Burden is heavy gt typically support only
    iterative resolution
  • Advantages of recursive name resolution
  • Caching possible at name servers (gradually learn
    about others)
  • Caching improves performance
  • Use time-to-live values to impose limits on
    caching duration
  • Results from higher layers can be cached for
    longer periods
  • Iterative only caching at client possible

24
Implementation of Name Resolution (3)
Server for node Should resolve Looks up Passes to child Receives and caches Returns to requester
cs ltftpgt ltftpgt -- -- ltftpgt
vu ltcs,ftpgt ltcsgt ltftpgt ltftpgt ltcsgtltcs, ftpgt
ni ltvu,cs,ftpgt ltvugt ltcs,ftpgt ltcsgtltcs,ftpgt ltvugtltvu,csgtltvu,cs,ftpgt
root ltni,vu,cs,ftpgt ltnlgt ltvu,cs,ftpgt ltvugtltvu,csgtltvu,cs,ftpgt ltnlgtltnl,vugtltnl,vu,csgtltnl,vu,cs,ftpgt
  • Recursive name resolution of ltnl, vu, cs, ftpgt.
    Name servers cache intermediate results for
    subsequent lookups.

25
Implementation of Name Resolution (4)
  • The comparison between recursive and iterative
    name resolution with respect to communication
    costs.
  • Recursive may be cheaper

26
DNS Name Space
  • The most important types of resource records
    forming the contents of nodes in the DNS name
    space.

Type of record Associated entity Description
SOA Zone Holds information on the represented zone
A Host Contains an IP address of the host this node represents
MX Domain Refers to a mail server to handle mail addressed to this node
SRV Domain Refers to a server handling a specific service
NS Zone Refers to a name server that implements the represented zone
CNAME Node Symbolic link with the primary name of the represented node
PTR Host Contains the canonical name of a host
HINFO Host Holds information on the host this node represents
TXT Any kind Contains any entity-specific information considered useful
27
DNS Implementation (1)
  • An excerpt from the DNS database for the zone
    cs.vu.nl.

28
DNS Implementation (2)
Name Record type Record value
cs.vu.nl NIS solo.cs.vu.nl
solo.cs.vu.nl A 130.37.21.1
  • Part of the description for the vu.nl domain
    which contains the cs.vu.nl domain.

29
X.500 Directory Service
  • OSI Standard
  • Directory service special kind of naming service
    where
  • Clients can lookup entities based on attributes
    instead of full name
  • Real-world example Yellow pages look for a
    plumber

30
The X.500 Name Space (1)
Attribute Abbr. Value
Country C NL
Locality L Amsterdam
Organization L Vrije Universiteit
OrganizationalUnit OU Math. Comp. Sc.
CommonName CN Main server
Mail_Servers -- 130.37.24.6, 192.31.231,192.31.231.66
FTP_Server -- 130.37.21.11
WWW_Server -- 130.37.21.11
  • A simple example of a X.500 directory entry using
    X.500 naming conventions.

31
The X.500 Name Space (2)
  • Part of the directory information tree.

32
The X.500 Name Space (3)
  • Two directory entries having Host_Name as RDN
    (Relative Distinguished Name).

Attribute Value Attribute Value
Country NL Country NL
Locality Amsterdam Locality Amsterdam
Organization Vrije Universiteit Organization Vrije Universiteit
OrganizationalUnit Math. Comp. Sc. OrganizationalUnit Math. Comp. Sc.
CommonName Main server CommonName Main server
Host_Name star Host_Name zephyr
Host_Address 192.31.231.42 Host_Address 192.31.231.66
33
Caching in the Domain Name System
34
Caching in the Domain Name System
35
Closure
  • Closure binds an object to the namespace within
    which names embedded in the object are to be
    resolved.
  • Namespace may be static or dynamic
  • Historical binding of names
  • Object may as small as the name itself
  • GNS binds the names to namespaces
  • Prospero binds enclosing object to multiple
    namespaces
  • Tilde and quicksilver bind users to namespaces
  • NFS mount table constructs system centered
    namespace
  • Movement of objects can cause problems
  • When closure is associated with wrong entity

36
Other implementations of naming
  • Broadcast
  • Limited scalability, but faster local response
  • Prefix tables
  • Essentially a form of caching
  • Capabilities
  • Combines security and naming
  • Traditional name service built over
    capabilitybased addresses

37
Advanced Name Systems
  • DECs Global Naming
  • Support for reorganization the key idea
  • Little coordination needed in advance
  • Half Closure
  • Names are all tagged with namespace identifiers
  • DID - Directory Identifier
  • Hidden part of name - makes it global
  • Upon reorganization, new DID assigned
  • Old names relative to old root
  • But the DIDs must be unique - how do we assign?

38
Prospero Directory Service
  • Multiple namespace centered around a root node
    that is specific to each namespace.
  • Closure binds objects to this root node.
  • Used today as an embedded directory service.
  • Layers of naming
  • User level names are object centered
  • Objects still have an address which is global
  • Namespaces also have global addresses
  • Customization in Prospero
  • Filters create user level derivednamespaces on
    the fly
  • Union links support merging of views

39
Resource Discovery
  • Similar to naming
  • Browsing related to directory services
  • Indexing and search similar to attribute based
    naming
  • Attribute based naming
  • Profile
  • Multi-structured naming
  • Search engines
  • Computing resource discovery

40
The Web
  • Object handles
  • Uniform Resource Locators (URLs)
  • Is it a name or an address?
  • Uniform Resource Names (URNs)
  • Is a directory service required
  • How URLs are misused
  • XML
  • Definitions provide a form of closure
  • Conceptual level rather than the namespace
    level.

41
LDAP and Active Directory
  • Manage information about users, services
  • Lighter weight than X.500 DAP
  • Heavier than DNS
  • Applications have conventions on where to look
  • Often data is duplicated because of multiple
    conventions
  • Performance enhancements not as well defined
  • Caching harder because of less constrained
    patterns of access
  • Referral mechanisms under development

42
LDAP
  • Lightweight Directory Access Protocol (LDAP)
  • X.500 too complex for many applications
  • LDAP Simplified version of X.500
  • Widely used for Internet services
  • Application-level protocol, uses TCP
  • Lookups and updates can use strings instead of
    OSI encoding
  • Use master servers and replicas servers for
    performance improvements
  • Example LDAP implementations
  • Active Directory (Windows 2000)
  • Novell Directory services
  • iPlanet directory services (Netscape)
  • Typical uses user profiles, access privileges,
    network resources

43
Naming versus Locating Entities
  1. Direct, single level mapping between names and
    addresses.
  2. T-level mapping using identities.

44
Forwarding Pointers (1)
  • The principle of forwarding pointers using
    (proxy, skeleton) pairs.

45
Forwarding Pointers (2)
  • Redirecting a forwarding pointer, by storing a
    shortcut in a proxy.

46
Home-Based Approaches
  • The principle of Mobile IP.

47
Hierarchical Approaches (1)
  • Hierarchical organization of a location service
    into domains, each having an associated directory
    node.

48
Hierarchical Approaches (2)
  • An example of storing information of an entity
    having two addresses in different leaf domains.

49
Hierarchical Approaches (3)
  • Looking up a location in a hierarchically
    organized location service.

50
Hierarchical Approaches (4)
  1. An insert request is forwarded to the first node
    that knows about entity E.
  2. A chain of forwarding pointers to the leaf node
    is created.

51
Pointer Caches (1)
  • Caching a reference to a directory node of the
    lowest-level domain in which an entity will
    reside most of the time.

52
Pointer Caches (2)
  • A cache entry that needs to be invalidated
    because it returns a nonlocal address, while such
    an address is available.

53
Scalability Issues
  • The scalability issues related to uniformly
    placing subnodes of a partitioned root node
    across the network covered by a location service.

54
The Problem of Unreferenced Objects
  • An example of a graph representing objects
    containing references to each other.

55
Reference Counting (1)
  • The problem of maintaining a proper reference
    count in the presence of unreliable communication.

56
Reference Counting (2)
  1. Copying a reference to another process and
    incrementing the counter too late
  2. A solution.

57
Advanced Referencing Counting (1)
  1. The initial assignment of weights in weighted
    reference counting
  2. Weight assignment when creating a new reference.

58
Advanced Referencing Counting (2)
  1. Weight assignment when copying a reference.

59
Advanced Referencing Counting (3)
  • Creating an indirection when the partial weight
    of a reference has reached 1.

60
Advanced Referencing Counting (4)
  • Creating and copying a remote reference in
    generation reference counting.

61
Tracing in Groups (1)
  • Initial marking of skeletons.

62
Tracing in Groups (2)
  • After local propagation in each process.

63
Tracing in Groups (3)
  • Final marking.

64
DHT Overview
  • Abstraction a distributed hash-table (DHT)
    data structure
  • put(id, item)
  • item get(id)
  • Implementation nodes in system form a
    distributed data structure
  • Can be Ring, Tree, Hypercube, Skip List,
    Butterfly Network, ...

65
DHT Overview (2)
  • Structured Overlay Routing
  • Join On startup, contact a bootstrap node and
    integrate yourself into the distributed data
    structure get a node id
  • Publish Route publication for file id toward a
    close node id along the data structure
  • Search Route a query for file id toward a close
    node id. Data structure guarantees that query
    will meet the publication.
  • Important difference get(key) is for an exact
    match on key!
  • search(spars) will not find file(briney
    spars)
  • We can exploit this to be more efficient

66
DHT Example - Chord
  • Associate to each node and file a unique id in an
    uni-dimensional space (a Ring)
  • E.g., pick from the range 0...2m
  • Usually the hash of the file or IP address
  • Properties
  • Routing table size is O(log N) , where N is the
    total number of nodes
  • Guarantees that a file is found in O(log N) hops

from MIT in 2001
67
DHT Consistent Hashing
Key 5
K5
Node 105
N105
K20
Circular ID space
N32
N90
K80
A key is stored at its successor node with next
higher ID
68
DHT Chord Basic Lookup
N120
N10
Where is key 80?
N105
N32
N90 has K80
N90
K80
N60
69
DHT Chord Finger Table
1/2
1/4
1/8
1/16
1/32
1/64
1/128
N80
  • Entry i in the finger table of node n is the
    first node that succeeds or equals n 2i
  • In other words, the ith finger points 1/2n-i way
    around the ring

70
Node Join
  • Compute ID
  • Use an existing node to route to that ID in the
    ring.
  • Finds s successor(id)
  • ask s for its predecessor, p
  • Splice self into ring just like a linked list
  • p-gtsuccessor me
  • me-gtsuccessor s
  • me-gtpredecessor p
  • s-gtpredecessor me

70
71
DHT Chord Join
  • Assume an identifier space 0..8
  • Node n1 joins

Succ. Table
0
i id2i succ 0 2 1 1 3 1 2 5
1
1
7
2
6
3
5
4
72
DHT Chord Join
  • Node n2 joins

Succ. Table
0
i id2i succ 0 2 2 1 3 1 2 5
1
1
7
2
6
Succ. Table
i id2i succ 0 3 1 1 4 1 2 6
1
3
5
4
73
DHT Chord Join
Succ. Table
i id2i succ 0 1 1 1 2 2 2 4
0
  • Nodes n0, n6 join

Succ. Table
0
i id2i succ 0 2 2 1 3 6 2 5
6
1
7
Succ. Table
i id2i succ 0 7 0 1 0 0 2 2
2
2
6
Succ. Table
i id2i succ 0 3 6 1 4 6 2 6
6
3
5
4
74
DHT Chord Join
Succ. Table
Items
7
i id2i succ 0 1 1 1 2 2 2 4
0
  • Nodes n1, n2, n0, n6
  • Items f7, f2

0
Succ. Table
Items
1
1
7
i id2i succ 0 2 2 1 3 6 2 5
6
2
6
Succ. Table
i id2i succ 0 7 0 1 0 0 2 2
2
Succ. Table
i id2i succ 0 3 6 1 4 6 2 6
6
3
5
4
75
DHT Chord Routing
Succ. Table
Items
7
i id2i succ 0 1 1 1 2 2 2 4
0
  • Upon receiving a query for item id, a node
  • Checks whether stores the item locally
  • If not, forwards the query to the largest node in
    its successor table that does not exceed id

0
Succ. Table
Items
1
1
7
i id2i succ 0 2 2 1 3 6 2 5
6
query(7)
2
6
Succ. Table
i id2i succ 0 7 0 1 0 0 2 2
2
Succ. Table
i id2i succ 0 3 6 1 4 6 2 6
6
3
5
4
76
DHT Chord Summary
  • Routing table size?
  • Log N fingers
  • Routing time?
  • Each hop expects to 1/2 the distance to the
    desired id gt expect O(log N) hops.

77
DHT Discussion
  • Pros
  • Guaranteed Lookup
  • O(log N) per node state and search scope
  • Cons
  • This line used to say not used. ButNow being
    used in a few apps, including BitTorrent.
  • Supporting non-exact match search is (quite!) hard

78
Next Lecture
  • Process migration
  • Chapter 3 of the book
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