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MANET Routing Protocols , a case study

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L. Yi, Y. Zhai, Y. Wang, J. Yuan and I. You , Impacts of Internal Network Contexts on Performance of MANET Routing Protocols: a Case Study, Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing,2012.

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MANET Routing Protocols , a case study

  1. 1. Impacts of Internal Network Contexts on Performance of MANET Routing Protocols: a Case Study Rayhan Hattab
  2. 2. Study Contents  What is MANET Network Contexts Mobility Models Routing Protocols Performance Metrics Simulation and results
  3. 3. What is MANET ? •The mobile ad hoc network is infrastructure less wireless network . • Ad hoc network do not rely on any fixed infrastructure. •There is no access points or base stations .
  4. 4. What is MANET ? •Topology of MANET is dynamic . •Each node is freedom movement . •Every mobile device in a network is autonomous. •Each node in the network acts as a router, forwarding data packets for other nodes.
  5. 5. Performance of Mobile Ad hoc NETwork (MANET) routing protocols is greatly affected by Network Contexts . The network contexts actually contain external and internal parts. External Contexts Internal Contexts Network Contexts
  6. 6. Network contexts • For external network contexts, many researches have been done. • However, there is relatively little research on the internal part.
  7. 7. External Network contexts External network contexts mean a series of external factors in practical applications which can hardly be configured but mainly adapted to, such as factors of scenarios, mobility models and traffic patterns. They are randomly determined by the environment, behaviors of users and the given business for MANET.
  8. 8. Internal Network contexts Internal network contexts mean a series of internalparameters in MANET protocol stack which can be configured in most cases, such as update interval of routing information in table-driven routing protocols and the transmission range of RREQ messages in on-demand routing protocols
  9. 9. Mobility Models The mobility model is external network context which plays a very important role in determining the protocol performance in MANET.
  10. 10. Mobility Model (Cont.) Group Mobility Mobility Model Freeway Random Waypoint Manhattan
  11. 11. Random Waypoint Mobility Model The random waypoint model has been widely used in most simulation studies and in performance comparison studies of routing protocols.
  12. 12. Random Waypoint In this model, nodes in a large ‘‘room’’ choose some destination, and move towards it at a random speed uniformly chosen from (0,V_max] . After reaching the destination, a node pauses for a constant time before moving towards the next chosen destination at a newly chosen speed.
  13. 13. Random Point Group Mobility (RPGM) Each group has a logical centre (group leader) that determines the group’s motion behavior. Given example scenario contains sixteen nodes with Node 1 and Node 9 as group leaders.
  14. 14. Freeway Mobility Model This model emulates the motion behavior of mobile nodes on a freeway.
  15. 15. Manhattan Mobility Model Manhattan model emulates the movement pattern of mobile nodes on streets. The scenario is composed of a number of horizontal and vertical streets.
  16. 16. Routing protocols Routing protocols are divided in two approaches: 1. Table Driven Routing Protocol or Proactive 2. On Demand Routing or Reactive Proactive (Table Driven ) Reactive (On Demand) Routing Protocols
  17. 17. Routing protocols (Cont.) OLSR , DBF, GSR , WRP , ZRP , STAR, DSDV In Proactive Routing Protocols means all nodes have tables with routing information which are updated at intervals. Example : OLSR (Optimized link state Routing protocol). Proactive (Table Driven)
  18. 18. Routing protocols (Cont.) In On Demand routing or reactive protocols, routes are created as and when required. When a transmission occurs from source to destination, it invokes the route discovery procedure. Example : AODV (Ad hoc On Demand Distance Vector). Reactive (On Demand) DSR , DDR , TORA , RDMAR , AODV
  19. 19. Routing protocols • We will used AODV routing protocol as case study , and • Used OLSR routing protocol as reference to comparison with AODV.
  20. 20. AODV • The AODV protocol is reactive protocol  AODV have 3 message types:  Route Requests (RREQs) (Prodcast from source to all other nodes )  Route Replies (RREPs) (Unicast from intermediate or destination node to source node )  Route Errors (RERRs) .
  21. 21. AODV (Cont.) • The range of dissemination of such RREQs is indicated by the TTL in the IP header .
  22. 22. AODV (Cont.) • To prevent unnecessary network-wide dissemination of RREQs, the originating node SHOULD use an expanding ring search technique. • In an expanding ring search, the originating node initially uses a TTL_START = TTL in RREQ packet IP header , and sets the timeout for receiving a RREP to RING_TRAVERSAL_TIME milliseconds.
  23. 23. AODV (Cont.) • If the RREQ times out without a corresponding RREP, the originator broadcasts the RREQ again with the TTL incremented by TTL_INCREMENT. • This continues until the TTL set in the RREQ reaches TTL_THRESHOLD. Each time, the timeout for receiving a RREP is RING_TRAVERSAL_TIME.
  24. 24. Performances Metrics  The following metrics are evaluated for the routing protocols: 1. Packet delivery ratio (PDR) – The ratio of the data packets delivered to the destinations over the data packets generated by the traffic sources; 2. Routing overhead – The number of control packets transmitted, with each hop-wise transmission of a control packet counted as one transmission;
  25. 25. Simulation Scenario  The basic simulation scenario in NS2 is Random waypoint.
  26. 26. Simulation Scenario The contents of external and internal network contexts in simulation are provided in Table 1 .
  27. 27. Simulation Scenario  we choose the following parameters : • External network contexts : Node density and Pause time . • Internal network contexts : TTL_ INCREMENT in AODV . • performance metrics : Packet Delivery Fraction (PDF) and Overhead. • For accuracy, each combination of external and internal network contexts is simulated five times and the average value is used.
  28. 28. Impact of PDF under Varied Node Density
  29. 29. There exist the following three phenomenon's: 1. The performance metric PDF of AODV shows better than that of OLSR when TTL _INCREMENT is set to 2, but worse in almost all cases when TTL_ INCREMENT is set to 8. 2. When node density increases to 8/km2, PDF of AODV with TTL _INCREMENT=2 reaches the maximum value. 3. The increase rate of PDF of TTL_INCREMENT=2 is higher than that of TTL_ INCREMENT=8 with node density increasing from 4/km2 to 8/km2; In addition, the decrease rate is also lower than that of TTL_ INCREMENT=8 with node density increasing from 8/km2 to 20/km2.
  30. 30.  We can get the following conclusions: 1. When the node density is increased properly, the routes can be established more quickly and stably because of the better connectivity. Quick and stable routes establishment is beneficial to deliver data packets timely and successfully, namely raise PDF. In this case, a higher TTL_ INCREMENT may sometimes make RREQ messages broadcasted with a long TTL value, but not many nodes will be affected by these control messages because the node density is not too high. So, the overhead is still low. 2. When the node density is increased too much, communication collisions will become ubiquitous. In this case, a higher TTL_ INCREMENT can increase the collisions further and cause higher overhead, which will lead PDF to decrease faster.
  31. 31. Impact of PDF under Varied Pause Time
  32. 32.  There exist the following three phenomenon's: 1. There is almost no differentiation of PDF for different TTL_ INCREMENT with pause time increasing. 2. PDF of AODV is much lower than that of OLSR when pause time is increasing from 0s to 15s. 3. When pause time increases to 20s, PDF of AODV is almost on the same level with that of OLSR, and both reach their maximal values. From the result, we can get the conclusion that TTL_INCREMENT almost brings no changes to the existing impacts of pause time on performance. From all the above, we can get the following solution that AODV with TTL_INCREMENT set to 2 tends to be well suited for accomplishing this mission under pause time = 17s, node density = 8/km2, this conclude relationship is qualitative .
  33. 33. Prove Impact of internal network contexts on performance metrics quantitatively The proof is based on the following three assumes: 1. Without using Hello mechanism, control overhead is mainly caused by RREQ messages, because RREP messages and Route ERRor (RERR) messages work on unicast mode. 2. Topology of MANET in practical application has certain characteristics and changing regularity. 3. Hops of established routes satisfy certain distribution law.
  34. 34. Let : k is number of hops routs . Bk is broadcast times of RREQ messages for establishing a k hops route . TS is TTL_START . T1 is TTL_INREMENT(T1min ≤ T1 ≤ T1max) . TTL_ THRESHOLD is ignored. Ideal case, Prove quantitatively Example TS = 1 , T1= 2,4,6,8
  35. 35. Prove quantitatively (Cont.) • If TTL value in the ith (i ≤ Bk) broadcast was TS + (i − 1)TI. • Then , TTL value in the last broadcast is TL .
  36. 36. Prove quantitatively (Cont.) The above is discussed based on an ideal case. In the real case, it is quite possible that a source node has still not received a RREP message from the destination when the value of TTL exceeds k hops. Then an extra broadcast of RREQ message is needed. This is usually caused by the joint impacts of node density and movement , the value of TTL exceeds k hops. We use Iα(x) to represent initiating an extra broadcast or not. So Bk is modified as follows:
  37. 37. Prove quantitatively (Cont.) In (5), x ∈ X and X ∼ U(0, 1).
  38. 38. Prove quantitatively (Cont.) The α is mainly related with the degrees of nodes involved in forwarding RREQ messages. Example d=2,3,4,5,6 dmin=2 dmax=6
  39. 39. Based on the above, we get the relationship between TTL_ INCREMENT and Overhead ―N is the total number of routes establishment times in MANET. ―Pk is the distribution law of hops : P {H = k} = pk , (k = 1, 2, . . . , K) ― IF dij was the average degree of nodes involved , ― So , d. Nij represents the total value of the degrees, And Nij = d · Ni(j−1). However, considering that not all the neighboring nodes are meaningful for the forwarding, Then Nij is revised to : Nij’ = d · Ni’(j−1) · β, in which β ∈ Y and Y ∼ U(a, b).
  40. 40. Prove quantitatively (Cont.) Table 2 : distribution law of hops H Table 3 : Parameters on the relationship When we set the distribution law of hops H as Table 2 , and The other parameters are provided in Table 3. We will get the simulation result in last Fig.
  41. 41. Impact of overhead under varied Node Degree
  42. 42.  We can get the following phenomenon's: • For TTL_ INCREMENT = 4, when average node degree increases from 2 to 5, overhead is relatively stable. This means that routes establishment is quick and stable , , and connectivity and PDF is improvement . • When average node degree increases from 5 to 6, overhead increases greatly, which means trouble with routes establishment. In this case, the increment of node degree can only cause more collisions and decrease PDF. So the point, where average node degree is set to 5, is an “turning point”. For different values of TTL _INCREMENT, the “turning points” are different.
  43. 43. Future Work 1. Make simulation to study impact of other internal network contexts such as proactive protocols update universal on performance metrics . 2. Make simulation to study impact of internal network contexts on overhead performance metrics that caused by Hello messages on reactive routing protocols. the result of all simulations we want to get stable and quick route establishment .
  44. 44. Reference • L. Yi, Y. Zhai, Y. Wang, J. Yuan and I. You , Impacts of Internal Network Contexts on Performance of MANET Routing Protocols: a Case Study, Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing,2012.

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