Design and Analysis of an MST-Based Topology Control Algorithm Ning Li and Jennifer Hou Department of Computer Science University of Illinois at Urbana-Champaign

6/26/20152 Outline Motivation Topology Control LMST: Local Minimum Spanning Tree Simulation Study Future Work

6/26/20153 Motivations (1) No Topology Control (2) With Topology Control

6/26/20154 R&D Roadmap and Opportunities Application Layer Transport Layer Network Layer MAC Layer Physical Layer Power Adjustment Channels Selection (frequency/code) Directional Beam-Forming GPS Positioning & Synchronizing Scheduling Contention Resolution Topology Control Routing QoS Mapping (e.g. bounded delay)  Maintain connectivity using the minimum transmission power.  Maintain connectivity by moving some “router” nodes to fill in the“hole”.  Enable nodes to self-organize themselves into clusters.  Load balance with power consideration  Realize Service Differentiation  Provide bounded transmission delay Error Control Data Aggregation/Computation Admission Control Integrated real time scheduling and power control  Maximize information throughput but not data throughput

6/26/20155 TopologyControl Topology Control Observations Almost all ad-hoc routing algorithms rely on the cache to inexplicitly build an underlying topology. Many broadcast/multicast algorithms for ad-hoc wireless networks maintain some kind of underlying topology, upon which the multicast tree/mesh can be built. Routing MAC / Power-controlled MAC Topology Control Topology control can achieve: Global connectivity Low energy consumption Low interference High throughput

6/26/20156 Design Guidelines Network connectivity should be preserved. Bi-directional links are preferred. Algorithms should be distributed. To be immune to the impact of mobility, the algorithm should depend on local information.

6/26/20157 LMST: Local Minimum Spanning Tree Static wireless multihop networks. Transmission power can be adjusted. Each node knows its own position. Each node will build its own minimum spanning tree in its neighborhood and only retain those one-hop neighbors on the tree as its neighbors in the final topology.

6/26/20158 LMST Visible neighborhood: the set of nodes that node u can reach by using the maximum transmission power. Information collection: Each node broadcast periodically a Hello message using its maximal transmission power. Topology construction –Each node applies Prim’s algorithm independently to obtain its local minimum spanning tree. –Each node takes all the one-hop, on-tree nodes as its neighbors. –The network topology under LMST is all the nodes in V and their individually perceived neighbor relations. Determination of transmission power: a node transmits using the power that can reach its farthest neighbor.

6/26/20159 LMST Properties The resulting topology preserves the connectivity. After removal of asymmetric links, all links are bi-directional and the connectivity is still preserved. The degree of any node is bounded by 6.

6/26/ LMST: Example w5w5 w3w3 w1w1 w7w7 w6w6 u w4w4 w2w2

6/26/ Uni-directional Links u v w4w4 d d max w3w3 w2w2 w1w1

6/26/ Connectivity G 0 is connected with some uni- directional links. We can either add extra links into G 0 so that all uni-directional links become bi-directional or delete all uni-directional links in G 0. Both approaches give us connected graph with bi-directional links.

6/26/ Simulations

6/26/ Simulations (Cont.)

6/26/ Dealing with Mobility

6/26/ Future Work Extend LMST to mobile networks. Build the multicast/broadcast protocol upon LMST. Implement LMST on a Motes testbed at UIUC.