Controlled Mobility Wireless Networks

1. Controlled Mobility Wireless Networks Eytan Modiano Massachusetts Institute of Technology

2. Controlled Mobility Wireless Networks • Network of mobile nodes whose mobility can be controlled • E.g., miniature autonomous air-vehicles • Nodes’ mobility can be used to facilitate communication • Increase network throughput or reduce delays • Maintain network connectivity • Reduce energy consumption

3. Maintaining Network Connectivity Mobile Backbone Architecture Mobile Backbone Node (MBN) Regular Node (RN) • Arbitrary Node mobility can lead to network disconnection • Mobility dictated by mission • Use dedicated communication nodes to maintain network connectivity • The MBNs primary purpose is to facilitate communication • The MBN’s form a backbone over which communications takes place • Facilitates network management • MBN nodes are moved about to maintain connectivity requirements • Regular nodes (RNs) have unconstrained mobility dictated by their mission • Technical challenges: • Positioning of MBN’s to provide connectivity for RN’s • Various constraints on transmission power, node’s degrees, connectivity requirements • Algorithms for reconfiguring the network as the RN’s move • Real-time, distributed

4. MBN Placement Problem (MBP) • Disk communications model • RN can communicate up to a distance r • MBN’s can communicate with each other up to a distance R (R > r) • MBP problem can be decomposed into 2 sub-problems: • Geometric Disk Cover (GDC) Problem • Steiner Tree Problem w/ Minimum Number of Steiner Pts. (STP-MSP) • Decomposition Result:Using - and -approximation algorithms for GDC and STP-MSP, yields an (+)-approximation algorithm for the overall MBP • Results • Developed distributed approximation algorithms for GDC problem under arbitrary mobility • Developed a new approach for solving STP-MSP problem • Extended approach to SNR-based communications model • Data rate is a function of received power and interference A. Srinivas, G. Zussman and E. Modiano, “Mobile Backbone Networks – Construction and Maintenance,” ACM Mobihoc, May, 2006.

5. Incorporating trajectory information • In many scenarios nodes trajectories are known a-priori • E.g., due to pre-planned path or mobility model (e.g., sensors’ trajectory) • Develop algorithms that compute the MBN’s path by incorporating RN trajectory knowledge • Reduce the need for the MBN to move rapidly • MBN’s mobility is constrained (e.g., velocity) • Otherwise could simply find optimal solution in every time step • Problem: Find the optimal MBN path to maximize network connectivity or throughput • Preliminary results: Dynamic Programming algorithms based on discrete formulation (I.e., nodes’ are placed on “grid” points)

6. C B A C Trajectory Control • Most work on trajectory (path) planning traditionally focuses on physical/geographical constraints • When communication is important, it’s crucial to look at communication requirements in trajectory planning • Example: Maintaining communications connectivity • Vehicle must travel from point A to point B • Vehicle must remain connected to a network (e.g., base-stations) • Find the optimal (minimum time) trajectory from A to B subject to connectivity requirements • Connectivity requirement: hard or soft? • Base-stations static or mobile?

7. Trajectory-Aware Routing • Question: Can we use trajectory information to design better routing protocols? • Advantage: Reduce routing overhead associated with ad-hoc wireless networks when such overhead cannot be afforded • Issues: • Deterministic vs. stochastic trajectories • Determining the minimum trajectory information that must be exchanged between nodes • Time scales: How long does it take to transmit minimum trajectory information compared to how long it takes to discover which wireless “links” are up? • Trade-off between energy for mobility and energy for communications • For “tiny” air vehicles energy for mobility is of the same order as energy for communications • Communicate over a long distance vs. relocate

8. Throughput - Delay tradeoffs in mobile ad hoc networks • Cell partitioned network • Nodes move between cells according to an I.I.D mobility model • Nodes can only communicate when they are in the same cell (subject to interference) • Without mobility per user throughput is limited to [Gupta/Kumar] • With mobility[Grossglauser/Tse]: • Throughput-Delay tradeoff [Neely/Modiano] • Reduced delay through redundant transmissions • Question: can throughput/delay be improved if the mobility of certain nodes can be controlled? IEEE Transactions on Information Theory, June 2005