Download presentation
Published byRandell Lindsey Modified over 9 years ago
1
Mobile Ad hoc Networks COE 549 Routing Protocols I
Tarek Sheltami KFUPM CCSE COE 4/19/2017
2
Outline Routing Algorithms Classifications Proactive Routing:
Table Driven Protocols Cluster-based Protocols 4/19/2017
3
Routing Algorithm Classifications
Routing Algorithms Proactive Reactive Hybrid Table Driven Cluster-based On-Demand Cluster-based 15/4/2003
4
Table Driven Protocols
Distance Vector Protocols such as: Wireless Routing Protocol (WRP) [MUR96] Destination Sequenced Distance Vector (DSDV) routing protocol [PER94] Least Resistance Routing (LRR) [PUR93] The protocol by Lin and Liu [LIN99]. Link State Protocols such as: Global State Routing (GSR) [CHE98] Fisheye State Routing (FSR) [PEI00a] Adaptive Link-State Protocol (ALP) [PEI00a] Source Tree Adaptive Routing (STAR) [ACE99] Optimized Link State Routing (OLSR) protocol [SHE03b] Landmark Ad Hoc Routing (LANMAR) [PEI00b] However the most prominent protocol is DSDV 4/19/2017
5
Table Driven Protocols
Try to match the link state and distance vector ideas to the wireless environment Each node only needs to know the next hop to the destination, and how many hops away the destination is: This information stored in each node is often arranged in a table, hence the term “table-driven routing” Such algorithm are often called distance vector algorithms, because nodes exchange vectors of their known distances to all other nodes An example is the Bellman-Ford algorithm, one of the first ones to be used for routing in the Internet 4/19/2017
6
Bellman-Ford Algorithm
Consider a collection of nodes, connected over bi-directional wired links of given delays. We want to find the fastest route from each node to any other node. An example network: Initially, each node knows the distances to its direct neighbors, and stores them to its routing table. Nodes other than their direct neighbors are assumed to be at an infinite distance. Then, nodes start exchanging their routing tables. 4/19/2017
7
Stage 1 4/19/2017
8
Stage 2 4/19/2017
9
Stage 3 4/19/2017
10
Table Driven Protocols
As the number of nodes n increases, the routing overhead increases very fast, like O(n2). When the topology changes, routing loops may form: 4/19/2017
11
Destination Sequenced Distance Vector (DSDV)
One of the earlier ad hoc routing protocols developed Its advantage over traditional distance vector protocols is that it guarantees loop freedom Extends the classical DBF by tagging each distance entry dik(j) by a sequence number (SN) that is originated by the destination node j. Each routing table, at each node, contains a list of the addresses of every other node in the network Along with each node’s address, the table contains the address of the next hop for a packet to take in order to reach the node In addition to the destination address and next hop address, routing tables maintain the route metric and the route sequence number. 4/19/2017
12
Destination Sequenced Distance Vector (DSDV)..
The update packet starts out with a metric of one The neighbors will increment this metric and then retransmit the update packet. This process repeats itself until every node in the network has received a copy of the update packet with a corresponding metric If a node receives duplicate update packets, the node will only pay attention to the update packet with the smallest metric and ignore the rest 4/19/2017
13
Destination Sequenced Distance Vector (DSDV)..
To distinguish stale update packets from valid ones, the original node tags each update packet with a sequence number The sequence number is a monotonically increasing number, which uniquely identifies each update packet from a given node If a node receives an update packet from another node, the sequence number must be equal to or greater than the sequence number already in the routing table; otherwise the update packet is stale and ignored If the sequence number matches the sequence number in the routing table, then the metric is compared and updated as previously discussed 4/19/2017
14
DSDV Routing Protocol 15/4/2003
15
DSDV Routing Protocol 15/4/2003
16
Disadvantages of DSDV Protocol
Routing is achieved by using routing tables maintained by each node The bulk of the complexity in generating and maintaining these routing tables If the topological changes are very frequent, incremental updates will grow in size This overhead is DSDV’s main weakness, as Broch et al. [BRO98] found in their simulations of 50-node networks 15/4/2003
17
Virtual Base Station (VBS)
All nodes are eligible to become clusterhead / VBS Each node is at one hop from its clusterhead Clusterhead / VBS is selected based on the smallest ID Gateways / Boarder Mobile Terminals (BMTs) Clsuterheads and Gateways form the virtual backbone of the network
18
VBS.. Every MT has an ID number, sequence number and my_VBS variable
Every MT increases its sequence number after every change in its situation An MT my_VBS variable is set to the ID number of its VBS; however, if that MT is itself a VBS, then the my_VBS variable will be set to 0, otherwise it will be set to –1, indicating that it is a VBS of itself
19
VBS..
20
VBS..
21
VBS..
22
VBS Illustrated
23
VBS Illustrated..
24
CGSR infrastructure Creation
CGSR uses the Least Cluster Change (LCC) clustering algorithm No clusterheads in the same transmission range Each Cluster has a different code to eliminate the interference, typically the suggest 4 Walsh codes
25
CGSR Illustrated
26
CGSR Illustrated ..
27
CGSR Illustrated..
28
Simulation Results
29
Simulation Results
30
Simulation Results..
31
Simulation Results..
32
Some issues about pure Cluster-based Routing (VBS)
Range of node #1 Routing in VBS 15/4/2003
33
Some issues about pure Cluster-based Routing (VBS)
15/4/2003
34
Some issues about pure Cluster-based Routing (VBS)
Routing in VBS 15/4/2003
35
Drawback of VBS All the nodes require the aid of their VBS(s) all the time, so this results a very high MAC contention on the VBSs the periodic hello message updates are not efficiently utilized by MTs (other than VBSs and BMTs) The power of the nodes with small IDs drain down much faster than that with large IDs 4/19/2017
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.