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Server Message Block: History, Features & Third-party implementations
Server Message Block (SMB) is a communication protocol used to share files, printers, serial ports, and miscellaneous communications between nodes on a network. On Windows, the SMB implementation consists of two vaguely named Windows services: "Server" (ID: LanmanServer) and "Workstation" (ID: LanmanWorkstation). It uses NTLM or Kerberos protocols for…
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Server Message Block topic overview
The analysis highlights History, Features and Third-party implementations as prominent areas in the source structure around Server Message Block.
Related topics
154
Source areas
6
Connected nodes
160
Extracted relationships
62
Concept neighborhoods
53
Bridge connections
160
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
History · 52 topics
Features · 43 topics
Overview · 27 topics
Third-party implementations · 22 topics
Security · 7 topics
Specifications · 3 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Server Message Block connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Server Message Block shows recurring relationship patterns in the source. For example, Server Message Block → Access, Benefits, CIFS, Common Internet File System, CPU, DDP, December, Infiniband, June, Microsoft, MS-CIFS, MS-SMB, MS-SMB2, MS-SMBD, October, Open Specifications, Protocol, Protocol Versions, RDMA, RDMA-capable Another extracted example is Server Message Block → IEEE, Internet, IP, IPX/SPX, Microsoft, Microsoft's Distributed File System, NBF, NetBIOS, NETBIOS Datagram Service, NetBIOS Frames, NETBIOS Name Service, NETBIOS Session Service, NetBT, On NetBT, SMB, TCP, TCP/IP, The SMB, This, UDP. Use these groups to spot repeated connection types before inspecting the individual relationships.
Server Message Block
Top relations
related to SMB specifications· 26
Server Message Block → Access, Benefits, CIFS, Common Internet File System, CPU, DDP, December, Infiniband, June, Microsoft, MS-CIFS, MS-SMB, MS-SMB2, MS-SMBD, October, Open Specifications, Protocol, Protocol Versions, RDMA, RDMA-capable
related to Features· 20
Server Message Block → IEEE, Internet, IP, IPX/SPX, Microsoft, Microsoft's Distributed File System, NBF, NetBIOS, NETBIOS Datagram Service, NetBIOS Frames, NETBIOS Name Service, NETBIOS Session Service, NetBT, On NetBT, SMB, TCP, TCP/IP, The SMB, This, UDP
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Server Message Block relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 62 structured relationships around Server Message Block. Examples in this analysis include those provided by Riverbed → instance of → One approach to mitigating the inefficiencies in the protocol is to use WAN optimization products and Xenix → instance of → and later became part of a wide variety of non-Windows operating systems. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
those provided by Riverbed
instance of
One approach to mitigating the inefficiencies in the protocol is to use WAN optimization products
0.80
text
Silver Peak
instance of
One approach to mitigating the inefficiencies in the protocol is to use WAN optimization products
0.80
text
or Cisco
instance of
One approach to mitigating the inefficiencies in the protocol is to use WAN optimization products
0.80
text
Xenix
instance of
and later became part of a wide variety of non-Windows operating systems
0.80
text
OS/2
instance of
and later became part of a wide variety of non-Windows operating systems
0.80
text
VMS
instance of
and later became part of a wide variety of non-Windows operating systems
0.80
text
Unicode support were retro-fitted at a later date
instance of
because features
0.80
text
the internet
instance of
providing a secure alternative to VPN for remote file access over untrusted networks
0.80
text
ext4
instance of
MoSMB also supports Amazon S3 object storage as storage backend in addition to POSIX file systems
0.80
text
ZFS
instance of
MoSMB also supports Amazon S3 object storage as storage backend in addition to POSIX file systems
0.80
text
Lustre
instance of
MoSMB also supports Amazon S3 object storage as storage backend in addition to POSIX file systems
0.80
text
Ceph
instance of
MoSMB also supports Amazon S3 object storage as storage backend in addition to POSIX file systems
0.80
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Server Message Block bring nearby vocabulary together. In this analysis, examples include Block, Message and Windows. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Server Message Block
Block
Message
Windows
Smb
File
Introduced
Server
System
Client
Use
Protocol
Quic
server message block
Block
Message
Windows
Smb
File
Cifs
Protocol
Introduced
Server
Internet
Performance
System
communication protocol
Smb
Microsoft
Network
Smb2
Server
Access
Use
File
Cifs
Systems
Windows
Direct
network
Latency
Protocol
Used
Access
Cifs
File
Smb
Performance
Internet
System
Use
Smb1
windows
Server
Smb
Introduced
Microsoft
Use
Later
Version
Systems
Also
Protocol
Quic
Implementation
windows services
Server
Smb
Introduced
Microsoft
Use
Later
Version
Systems
Also
Protocol
Quic
Implementation
share access
Direct
Files
Smb2
Network
Protocol
Cifs
File
Quic
Introduced
Used
Client
Smb
microsoft
Protocol
Windows
Smb
System
Since
File
Internet
Version
Cifs
Use
Server
Netbios
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Server Message Block, one of the stronger structural bridges in this analysis connects Server Message Block with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Server Message Block
Nodes161
Edges160
Triples62
Avg. degree1.99
Density0.012422
Components1
Source & methodology
TTTA analyzes the structure around Server Message Block to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Features & Third-party implementations, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
