Smart Routers for Cross-Layer Integrated Mobility and Service Management in Mobile IPv6 Systems

Authors: Ding-Chau Wang . Weiping He . Ing-Ray Chen

Presented by: Dong Chen . Zhiqian Chen . Brad Herald

Overview1. Introduction• Internet Protocols (IP); IPv4, and IPv6• Mobile IP; MIPv6 and HMIPv6

2. DMAPwSR with Smart Routers; Dynamic Mobility Anchor Points with Smart Routers

3. Performance Model

4. Numerical Results with Simulation Validation1. Comparison of DMAPwSR and HMIPv6

2. Simulation Validation

5. Conclusion

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1. IP protocols• Internet Protocol version 4 (IPv4) is a connectionless protocol

for use in packet-switched networks. It delivers packets often out of order and usually duplicated. IPv4 carries more than 96% of the worldwide Internet traffic.

• Internet Protocol version 6 (IPv6) is the latest IP version, RFC 2460, December 1998. Improves addressing networks, part of an IPv6 address contains a host configurable address. Improves network-layer security. Data portion of packet can be as large as 232-1 octets.

• IPv4 addresses are 32 bits long and number about 4.3×109 (4.3 billion)

• IPv6 addresses are 128 bits long and number about 3.4×1038 (340 undecillion)

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Mobile IP Usage• MIPv6 – with advances in wireless IP-based networks

and increased numbers of wireless devices, it is speculated MIPv6 will become more prevalent in the next generation of all-IP networks. This will allow users to have continuous service while on the go.

• HMIPv6 – The hierarchical version of MIPv6 is designed to reduce the network signaling cost for mobility management based on the observation that statistically local mobility accounts for more than 60% of movements made by a MN.

• MIPv6: Mobile IPv6

• HMIPv6: Hierarchical MIPv6

• MN: mobile node

• CoA: care-of-address

• RCoA: regional CoA

• CN: corresponding nodes

• AR: access routers

• SMR: service to mobility ratio

• HA: home agent

• SPN: stochastic Petri net

Terminology

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2. DMAPwSR With Smart Routers

•What is DMAPwSR?•Basic Idea•Rationale

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Mobility and Service Management Scenarios under DMAPwSR

He, Weiping, Ing-Ray Chen, and Ding-Chau Wang. "Cross-layer integrated mobility and service management utilizing smart routers in mobile IPv6 systems." Proceedings of the 8th International Conference on Advances in Mobile Computing and Multimedia. ACM, 2010.

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Issue• DMAP size

• Small area: DMAP will change more often• Service delivery cost is low for communication between CN and MN

• Location management cost is high, more frequent updates for RCoA

• Large area: DMAP will not change as often• Service delivery cost is high for communication between CN and MN

• Location management cost is low, infrequent updates for RCoA

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3. Performance Model• Use SPN to model a MN’s mobility behavior in HMIPv6 and

DMAP to find the optimal DMAP service area size.

• SPN can model the extensive number of states and a MN’s behavior migrating from one state to another state in response to events occurring in the system.

• The goal is to find the minimal mobility and service operations cost per time unit.

• Communication Cost includes• Mobility management overhead

• Update DMAP with CoA changes

• Informing HA and CNs of RCoA changes

• Service management overhead to deliver data packets between MN and CNs

l Data packet rate between the MN and CNs

s Mobility rate at which the MN moves across boundaries

SMR Service to mobility ratio (l/s)

N Number of server engaged by the MN

K Number of subnets in a DMAP service area

t 1-hop communication delay per packet in wired networks

a Average distance between HA and DMAP

b Average distance between CN and DMAP

g Cost ratio, wireless versus wired

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Performance Model

based on SPN• Transitions

• Timed - Moves, MN2DMAP, and NewDMAP

• Immediate – A and B

• Tokens – represents an event occurrence

• Places – Moves,Intra,and Xs

• Arcs

• Transition Move occurs at rate s, mobility rate for MN crossing boundaries.

• Place Moves holds a token when a subnet crossing event happens.

• MN2DMAP transition represents the MN registering with DMAP the new CoA received from a new AR.

• For K - ARs:• Intra-domain (K-1) - each token represents a MN moving to each AR within the

domain

• Inter-domain (Kth move) – last MN move in domain triggers transition to NewDMAP

• Place Xs holds number of subnet crossing events since last DMAP registration.

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Communication Cost• The stochastic model underlying the SPN model is a continuous-

time Markov chain, with exponentially distributed events.

• The state representation of (a, b) where a is the number of tokens in place Moves, b is the number of tokens in place Xs.

• Let Pi be the steady state probability the system contains i tokens in place Xs, with 1 ≤ i ≤ K.

• Let Ci,service be the communication cost for the network to service a data packet given that the MN has moved across i subnets since the last DMAP registration.

• bt - Communication delay between DMAP and a CN in the fixed network

• it – delay from DMAP to the MN’s current AR

• gt – delay in the wireless link from AR to MN

• Cservice – average communication cost to service a data packet weighted by Pi

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Communication Cost• Let Ci,location be the network signaling overhead to service a location

handoff operation given MN has moved across i subnets since the last DMAP registration.• If i<K, minimum signaling cost incurred for MN to inform DMAP of CoA

address change

• If i=K, the location handoff triggers a DMAP service handoff, which incurs higher communication signaling cost to inform the HA and N CNs of the RCoA address change.

• gt – communication delay in the MN to AR wireless link

• at + Nbt – communication delay from AR to the HA and N CNs

• Clocation – average communication cost to service a move operation by the MN weighted by the respective Pi probabilities.

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Communication Cost

is data packet rate between the MN and CNs, and is the MN’s mobility rate.

• Using these equations, we can calculate the CDMAPwSR as a function of K and determine the optimal K.

• The optimal DMAP size is movement-based.

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4. Numerical Results with Simulation Validation

• Tools

• SPN Model for Analysis

• SMPL for Simulation

• DMAPwSR is movement-based

• DMAP service area size determined by the # of movements the MN

• DMAP service area size could be distance-based, and it is the distance between the DMAP and the current subnet

• Compare simulation result of movement-based versus distance-based to see if it is sensitive to definition of DMAP service area

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Network Coverage Models• Compare simulation result of the network coverage model used to

see if it is sensitive.• 2D Hexagonal-shape network coverage

• Mesh network coverage

• Based on real trace data

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2D Hexagonal-shape Network Coverage Model

• Moves from current AR to one of the 6 neighbor ARs randomly with equal probability of ⅙

• Can be used for both movement/distance based

• Subnet area is represented by radius r

• Distance-based DMAP area service will have (2K-1) r

• K is the DMAP service area size

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Mesh Network Coverage Model• moves from current AR to one of the 6 neighbor ARs randomly with

equal probability of ¼

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Trace-Data Based Network Coverage Model

• two AP are neighbor APs if they are separated in distance in the range of [100,200m]. (AP signal coverage range is about 91.4m)

• MN randomly choose a neighbor AP when leaves the current AP.

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4.1 Comparison of DMAPwSR with MIPv6 and HMIPv6

• The communication cost CMIPv6 service for servicing a packet delivery in basic MIPv6• bt - Communication delay from CN to AR of current subnet

• gt - Delay in wireless link from AR to the MN

CMIPv6 service = bt + gt

• The communication cost CMIPv6 location for servicing a location handoff in basic MIPv6• gt - Delay in wireless link from MN to the AR of subnet

• at – Delay from AR to the HA to inform the HA of CoA change

• Nbt - Communication delay from AR to CNs to inform of the CoA change

CMIPv6 location = + + gt at Nbt

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Comparison of DMAPwSR with MIPv6 and HMIPv6

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• For HMIPv6, there are pre-determined ARs serving as MAPs for MNs.

• Using DMAPwSR with an implementation of two-level HMIPv6, with each MAP covering a fixed-size area, KH subnets.

• Higher SMR means the MN’s packet arrival rate is much higher than the mobility rate.

• Comparing cost: MIPv6 and DMAPwSR• Low SMR, DMAPwSR dominates over

MIPv6.

• As SMR increases, in the case 64, Kopt approaches 1 which DMAPwSR is essentially the same as basic MIPv6.

• Comparing cost: HMIPv6 and DMAPwSR• As SMR increases, HMIPv6 cost decreases

compared to DMAPwSR until Kopt coincides with KH.

• After KH HMIPv6 cost increases sharply.

• DMAPwSR performs better than HMIPv6 with low or high SMR.

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Comparison of DMAPwSR with MIPv6 and HMIPv6

• Low SMR, the cost gain of DMAPwSR over HMIPv6 can go as high as 40%.

• High SMR, the cost gain is less than 5%.

• The cost gain is per-MN per time unit. Over time, a 5% cumulative gain over all MNs will still be significant.

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Comparison of DMAPwSR and HMIPv6

(with different a and b values)

• The cost differences are more pronounced as the distance between the HA (or CN) and the MN increases.

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4.2 Simulation Validation• Batch Means Analysis Technique

• Simulation period is divided into batch runs

• Each consists of 2,000 observations

• Minimum batch size is 10

• Target metric: grand mean of overall network cost

• Additional batches are needed if grand mean is within 95% confidence level and 10% accuracy from the true mean.

• To achieve confidence level of 95% and accuracy of 5%, normally takes more than 20,000 observations.

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Service Area Size K vs Total Cost

• This figure shows there exists K that can balance the trade-off between large service delivery cost using large service area versus large location management cost of informing HA and CNs using small service area.

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Cost Difference vs SMR(by simulation versus analytical results)

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Cost Difference vs SMR (by movement-based versus distance-based)

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Cost Difference vs SMR(under various time distributions)

• Normal, uniform, and exponential distribution the results trend remain the same no matter which time distribution is.

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K vs SMR(under various time distributions)

• Normal, uniform, and exponential distribution the results trend remain the same no matter which time distribution is.

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Cost Difference vs SMR(under various network coverage models)

• Hexagonal, mesh, trace-data based remarkably consistent with each other.

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Summarizing Results• The result is insensitive:• analytical vs. simulation•movement vs. distance based• various time distributions• various network coverage models

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5. Conclusion• DMAPwSR

• SPN DMAPwSR Model

• Simulation Validation

• Future work