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Gateway Selection in Rural Wireless Mesh Networks Team: Lara Deek, Arvin Faruque, David Johnson. http://www.octavetech.com/blog/wp-content/uploads/2008/03/long-range-wireless.jpg. Introduction: Rural Wireless Mesh Networks (WMNs) .
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Gateway Selection in Rural Wireless Mesh Networks Team: Lara Deek, Arvin Faruque, David Johnson http://www.octavetech.com/blog/wp-content/uploads/2008/03/long-range-wireless.jpg
Introduction: Rural Wireless Mesh Networks (WMNs) • A mesh network comprised of multiple, commodity devices that provides Internet access to rural areas • Topology differs from hub-and-spoke wireless networks • Applications: Education, health care • Benefits: cost, robustness, infrastructure requirement
Introduction: Rural WMN Examples • Digital Gangetic Plains (India) • OLPC Project: Each XO-1 will operate as a WMN node Image from http://www.cse.iitk.ac.in/users/braman/dgp.html Image from http://laptop.org/en/laptop/hardware/specs.shtml
Introduction: Mesh Network Gateway Selection • Mesh networks connect to the rest of the Internet via gateways • Rural and municipal WMNs have different bandwidth constraints • Municipal: bottleneck is wireless links • Rural: bottleneck is at gateways • Problem: Inefficiently utilized gateways WMN can have severe consequences in rural areas • Our goal: modify an existing mesh routing protocol attempt to optimally select gateways
B.A.T.M.A.N.(1) A B F D G C X E A wants to reach X
B.A.T.M.A.N. (2) Nodes broadcast originator messages (OGM's) every second OGM's are rebroadcast Other nodes measure how many OGM's are received in a fixed time window A:10 A B F D A:9 G C X E
B.A.T.M.A.N. (3) A B F A:8 D G C A:7 X E A:7 D BATMAN routing table TO VIA Q A B 8 A C 7 D Final routing table TO VIA A B
B.A.T.M.A.N. (4) A B F A:0 A:6 D G C A:4 X A:7 E G BATMAN routing table TO VIA Q A D 6 A E 7 G Final routing table TO VIA A E
B.A.T.M.A.N. (5) A B F D G A:5 C X A:6 E X BATMAN routing table TO VIA Q A G 5 A E 6 X Final routing table TO VIA A E
B.A.T.M.A.N. (6) A B F D G C X E X BATMAN routing table TO VIA Q A G 5 A E 6 E BATMAN routing table TO VIA Q A C 7 A D 4 C BATMAN routing table TO VIA Q A A 9
Current GW selection techniques Minimum hop count to gateways Used by routing protocols like AODV Creates single over congested gateways GW2 A B F D G C X E GW1
Current GW selection techniques Best link quality to GW Used by source routing protocols like MIT Srcr Link state protocols like OLSR Prevents congested links to GW Not global optimum of GW BW usage GW2 2 2.2 A B F 1.5 1 1 3 D G C 1 X 1 1 E GW1
Current GW selection techniques BATMAN has advanced a little further GW can advertise downlink speed User can choose GW selection based on GW with best BW Stable GW (need history) GWBW x LQ Can't trust advertised GW BW Doesn't achieve fairness 256 kbps GW2 9 10 A B F 7 4 7 3 D G C 8 7 X E 10 512 kbps GW1
Proposed Solution: Introducing intelligence to the core of the WMN • Introduce information about gateway performance into the network • Nodes at “intelligence boundary” have gateway performance information, need to transfer this information to the other nodes • Transfer this information via: “Batsignal” packets that are flooded through the network
Proposed Solution: What does the boundary node measure? • When nodes will select gateways, they will need to estimate the amount of bandwidth they will get: • Example: • Hence, boundary nodes must transmit current total gateway bandwidth and current # of VPNs • Total gateway capacity is the sum of • Measured extra bandwidth (measured through active probes) • The sum of the current bandwidths of the VPNs
Field Description GWID Gateway ID (0-255) TS Time stamp DB Total download bandwidth VPNs Number of VPNs on gateway TTL Packet time to live Proposed Solution: Batsignals • A node at the intelligence boundary periodically • Record gateway measurement • If the measurement is not drastically different than a previous value, then transmit a Batsignal packet only if we have not recently transmitted a batsignal packet • If the measurement is drastically different from a previous value, immediately transmit a Batsignal packet • All other nodes • Forward a received bat-signal to its neighbors (if it has not expired) • Update their own gateway preference tables Batsignal Packet Node Gateway Preference Table
Proposed Solution: Using Batsignal data to pick a gateway Gateway Preference Table • To choose a gateway, the following metric based on table data and link quality (computed only when current_time - timestamp is below a threshold) is used • Gateway flapping: When a gateway comes up and goes down frequently, a large number of conflicting Batsignal's will be broadcasted to the WMN nodes. • The VPN will not switch to another gateway until all the flows within it have terminated (Srcr)
Evaluation: The massive mesh in South Africa 7x7 grid of 49 wireless nodes using 802.11 a/b/g radios Each node network boots off a central server Makes use of 30dB attenuators on radios to achieve multiple hops in small space Has been used for extensive mesh network protocol benchmarking Complete remote control of experiments possible
Evaluation Environment I Parameters at the Gateway and Mesh Nodes Technologies Used • Load: traffic/congestion. • Loss: signal weakness, obstacles. • Delay: . • Bandwidth: of the available communication channels between mesh nodes or between mesh nodes and gateways. • Throughput: between mesh nodes and a test server outside the mesh network. • tc: linux traffic control. • iperf: TCP/UDP bandwidth measurement tool. • iptables: defines packet processing schemes.
Evaluation Environment II Metrics Measurement Methodology • Gateway efficiency: measures how effectively we match the throughput generated by the VPNs to the capacities of the gateways. • Gateway fairness: measures how fairly the aggregate gateway throughput is distributed among VPN flows. • Gateway Flapping: measures the frequency a mesh node switches between utilization of multiple gateways. • Measure VPN flows at each GW • Have capacity of all GW’s. • Measure VPN flows. What is the time window? Average over time. • Parse BatSignals for each node and record the timestamp for each GW usage. How much hysteresis?
How are we using technologies to determine fundamental parameters? Active Probing to determine GW throughput using a decentralized, distributed approach via trusted internet mesh nodes that form the intelligence boundary {B1, B2}.
Current Progress (from Proposal) We are in Week 4. Formulate a set of preliminary evaluation metrics for the protocol. (Week 1 - Week 3). Done Formulate a measurement procedure to test the efficacy of the protocol. (Week 1 - Week 2) Done Emulate a gateway on a UCSB MeshNet node using Linux tools such as tc and iptables. (Week 2 - Week 3)Have developed scripts to control TC and iptables. Need to develop remote control for this script. Run and evaluate the latest developers release of B.A.T.M.A.N. on the UCSB MeshNet. (Week 1 - Week 4) Have evaluated BATMAN on 3 mesh UCSB MeshNet nodes. Need to transition massive mesh (has been done before). Implement solutions to Goals 1, 2, 3, and 4 and measure performance using the measurement process described in (2) and evaluation metrics described in (1) (Week 3 – Week 6) In progress, analyzing code.