S Master’s thesis seminar 8th August 2006 QUALITY OF SERVICE AWARE ROUTING PROTOCOLS IN MOBILE AD HOC NETWORKS Thesis Author: Shan Gong Supervisor:Sven-Gustav Häggman

Outlines Ad Hoc Networks QoS (Challenge of implementing QoS in ad hoc networks, QoS metrics, QoS metric calculation) AODV Access admission control in QAODV QAODV Simulation Environment and Results

Mobile Ad hoc networks The application of mobile ad hoc networks becomes more and more popular. Applications of Mobile Ad Hoc Networks (Military Applications, Emergency Operations, Wireless Mesh networks, Wireless sensor networks).

QoS “Quality of Service is the performance level of a service offered by the network to the user”. QoS considered in this thesis work: low end to end delay (e.g. real time traffics)

Challenge of QoS in ad hoc networks Dynamically varying network topology Lack of precise state information Shared radio channel The resources such as data rate, battery life, and storage space are all very limited in ad hoc networks.

QoS metrics Additive metrics (end to end delay) Concave metrics (data rate) Multiplicative metrics. (link outage probability) The generally used metrics for real time applications are data rate, delay, delay variance (jitter), and packet loss.

Calculation for locally available data rate Method 1: Transmission range = Carrier sensing range Case 1 is the data rate used by node i for receiving data. Case 2 is the data rate consumed by neighbors who are receiving. Case 3 is the data rate consumed by neighbors who are sending.

Calculation for local available data rate Method 2: Carrier sensing range is more than twice of the transmission range (more realistic) Data Rate =(N*S*8)/T The used data rate is the sum of the sent, received and sensed data rate

AODV routing protocol Reactive RREQ (broadcast) and RREP (unicast) RERR

Access Admission Control Available bandwidth ? Required bandwidth

Required data rate at each node Method 1 carrier sensing range = transmission range With a N-hop route, the source and destination nodes should satisfy ABi>=2r, the second and N-1 nodes ABi >=3r and the intermediate nodes ABi >=4r. Here, r is the required data rate requirement and ABi is the available data rate at node i. N-1 node is the node on the path which is next to the destination node. EDCB A

Required data rate at each node Method 2 carrier sensing range >= 2* transmission range The contention count is calculated as follows If hreq > 2  hreq = 2 otherwise hreq=hreq If hrep > 3  hrep = 3 otherwise hrep=hrep CC = hreq + hrep

Required data rate at each node Method 2 carrier sensing range >= 2* transmission range Example

Maximum data rate Vs. Hops of a route

QAODV routing protocol-draft Session ID Maximum delay extension field Minimum data rate extension field Node satisfying these requests could broadcast the RREQ further List of sources requesting QoS guarantees

AODV vs. QAODV Recv RREQ Recv RREP Enough Data rate? Broadcast RREQ Forward RREP Enough Data rate? Drop RREQ Drop RREP Periodically check Available Data rate Available data rate >0 Do nothing Send ICMP_QoS_Lost Recv ICMP_QoS_ Lost Whether I am the source node Forward ICMP_QoS Lost Stop traffic

Example for QAODV—periodic check for available data rate m 150 m 33 Move direction of Node m (Interference range) Traffic stopped

Scenario

Simulations with both AODV and QAODV

Performance metrics Average end to end delay Packet Delivery Ratio (PDR) Normalized Overhead Load (NOL) Route finding time of the first route

Simulation Environment The channel type is “wireless channel” radio propagation model is “two ray ground”. MAC layer based on CSMA/CA as in IEEE is used with RTS/CTS mechanism. The data rate at physical layer is 11 Mbps. Queue type is “drop tail” the maximum queue length is 50. Routing protocols are the AODV and the QAODV. The transmission range and carrier sensing range are 250 m and 550 m respectively.

Specific Scenarios for Simulations. The area size is 700 m * 700 m 20 nodes in this area. Every experiment will be run 1000 s in total. (500 s is added at the beginning of each simulation to stabilize the mobility model.) Each data point in the results represents an average of 10 trails with same traffic model but different randomly mobility scenarios. For fairness comparisons, same mobility and traffic scenarios are used in both the AODV and the QAODV routing protocols. In the following set of simulations, a group of data rates ranging from 50 kbps to 1800 kbps is applied. The mobility scenario is with a pause time of 10 seconds and the maximum node speed of nodes is 1 m/s.

Traffic pattern

Average end to end delay

Packet Delivery Ratio

Normalized Overhead Load

Time used to find the first route The first traffic flow 553 s ~ 774 s. The second traffic flow 680 s ~ 780 s.

Summary and Conclusions QAODV outperforms AODV in terms of end to end delay Constrain the packets which might be useless to the network More routing packets are sent (brings problem when node density is high) More QoS metrics could be added to the routing protocol (delay, packet loss)

Thank you