A Hybrid Spatial Reuse MAC Protocol for Ad-Hoc Underwater Acoustic Communication Networks By : Roee Diamant, Lutz Lampe University of British Columbia.

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Presentation transcript:

A Hybrid Spatial Reuse MAC Protocol for Ad-Hoc Underwater Acoustic Communication Networks By : Roee Diamant, Lutz Lampe University of British Columbia (UBC) 1 1

Outline The broadcast scheduling problem (BSP) in Underwater Acoustic Communication Networks (UWAC) Related work Scheduling using graph coloring Sub-optimal Hybrid TDMA-CDMA scheduling protocol Sea trial results 2 2

Motivation Most underwater applications requires networks supporting broadcast communication: In most cases topological structure of the network is unknown Other modems Relay nodes Undersea navigation Underwater acoustic modem Oceanography data collection Control over autonomous underwater vehicles Relay, AUV collaboration Centralized solution is difficult. Ad-hoc scheduling is more natural 3 3

Broadcast Scheduling Problem (BSP) Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Broadcast Scheduling Problem (BSP) We require both high throughput and low transmission delay: Throughput – average number of successful transmissions Transmission delay – average waiting time between transmissions Throughput Transmission delay This is the BSP: How to schedule transmissions such that: optimal tradeoff between throughput and transmission delay is achieved

Scheduling in UWAC – related work BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Scheduling in UWAC – related work Most scheduling protocols involves hand-shaking techniques adopted from the CA/CSMA protocol [Molins:2006] Hybrid Aloha-CDMA: Transmitter adapts code length and transmission power [Pompili:2009] Cluster based – TDMA inside cluster, CDMA between clusters [Salva-Garau:2003] Advantages: increased availability; scalable TDMA Disadvantages: Cluster management; spatial reuse between clustered is not managed Disadvantage (for high traffic) low throughput high transmission delay Advantages spatial reuse high reliability CTS RTS RTS Aloha based Header packet CDMA based Information packet For small scale high-traffic networks, TDMA outperforms most existing protocols 5

Formalization of BSP Network is represented by a directed graph G(V,E) Consider Spatial TDMA (STDMA) scheduling. The solution is a matrix, M such that: Node i transmits in slot t only if Node i and j are not scheduled in the same time slot if General formalization [Menon:2009]: Channel utilization X Flow constraints X X X Feasible solution X Not a convex problem! 6 6

BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Coloring the network Time-slot in BSP can be generalized as graph-coloring [Ephremides:1990] Colors are assigned according to the connection between nodes Performance increase the more sparse the network is General BSP is non-convex and Graph coloring is NP-complete Minimize number of colors while adjacent vertices (half-duplex) gets different colors Fully connected network Start topology spatial reuse Sub-optimal approach is required 7 7 7

Topology variations Consider the following topology: When topology changes, nodes can “see” the network differently, resulting packet collisions Time slot Tx nodes 1 2 2,3,4 3 2 4 1 Time slot Tx nodes 1 2 2,4 3 3,4 1 2 4 3 Robustness to topology changes is required 8 8 8

Overview Till now we introduced the BSP for UWAC networks and its relation to graph coloring We observed that the optimal solution for BSP is non-convex and thus computationally difficult We also realized the importance of robustness to topology changes in MAC scheduling We now move on to introduce our Hybrid TDMA-CDMA solution, (HSR- TDMA), based on STDMA scheduling 9 9

BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results The HSR-TDMA protocol The protocol is based on a TDMA skeleton schedule Each node is getting a unique DSSS polynomial (CDMA) In each time slot, the pre-assign node is denoted as the “slot node” The rest of the nodes are divided to “receiving nodes” and “joining nodes” and are given a unique priority per time slot: Receiving nodes: nodes connected to the slot node Joining nodes: nodes not connected to the slot node and has higher priority than their neighbors which are not receiving nodes 1 2 4 3 Time slot X X nodes Robustness, minimal flow assurance X X 10 10

The HSR-TDMA protocol Scheduling algorithm: 1 2 4 3 BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results The HSR-TDMA protocol 3 2 4 1 Hop-distance matrix, H Broadcast packets Scheduling matrix construction Topology matrix construction Shortest path algorithm Pre-defined skeleton; Weight vector Scheduling algorithm: For each possible joining node, n, set a group such that If then n is a joining node If then n is a joining node i.i.d random variables, sampled afresh with same seed for all nodes Only nodes at even odd distance to the slot node are candidate to join its transmissions 11 11

The near-far problem Overcoming the near-far problem: BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results The near-far problem The near-far phenomenon occurs when close node transmissions interrupts transmissions from distance nodes The result is a non-symmetric network connectivity matrix Overcoming the near-far problem: Set a group of all joining nodes in current time slot For every set and every node ,check if both m,n are either both connected or both not-connected to p If not (a non-symmetric connection exists) : only one of them is chosen as a joining node, based on their current priority 12 12

HSR-TDMA: example 13 13 BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results HSR-TDMA: example 13 13

Sea Trial results 1(full connectivity) 2 (mixed) 3 (star) 4 (chain) BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Sea Trial results Since accurate propagation model are hard to acquire, we preformed a sea trial at the Haifa harbor in May2009 to validate our assumptions: Slow time varying topology structure Ability to decode packets transmitted simultaneously from different users Symmetric channel (at the long run) 1(full connectivity) 2 (mixed) 3 (star) 4 3 1 2 4 3 1 2 4 3 1 2 4 (chain) 5 (near-far) 6 (island) 4 3 1 2 4 3 1 2 4 3 1 2 14 14

Sea Trial results Average throughput Per node availability BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Sea Trial results Average throughput Per node availability Corresponds to transmission delay TDMA availability and throughput fixed on 25% for four nodes 15 15

Sea Trial results Average availability vs. time 16 16 BSP Related work Graph coloring Hybrid TDMA-CDMA Sea trial results Sea Trial results Average availability vs. time 16 16

Summery Required by most underwater applications High traffic broadcast network communication Majority of existing protocols deals with low-traffic communication Maximize throughput, Minimize transmission delay In general, non-convex BSP Robust scheduling is requires Topology variations resulting packet collisions Colors = time slots Edges = interferences Graph coloring is NP-complete Graph coloring generalize BSP Polynomial time Robustness to topology variations Sub-optimal solution; Hybrid STDMA-CDMA protocol Introducing HSR-TDMA protocol Sea trials confirmed assumptions Considerable improvement in both throughput and transmission delay 17 17

Reference list [1] W. Burdic, “Underwater Acoustic System Analysis,” Los Altos, CA, USA: Peninsula Publishing, 2002 [2] J. Partan, J. Kurose, and B. Levine, “A survey of practical issues in underwater networks,” in International Conference on Mobile Computing and Networking (MobiCom), Los Angeles, CA, USA, Sept. 2006. [3] M. Stojanovic, “On the relationship between capacity and distance in an underwater acoustic communication channel,” in ACM Intaternational Workshop on UnderWater Networks (WUWNet), Los Angeles, CA, USA,Sept. 2006. [4] C. Sherman and J. Butler, “Transducers and Array for Underwater Sound,” Springer Science + Business Media, LLC,2007 [5] J. Heidemann, W. Ye, J. Wills, A. Syed, and Y. Li, “Research challenges and applications for underwater sensor networking,” in IEEE Wireless Communications and Networking Conference (WCNC),Las-Vegas,NV,USA,Apr. 2006. [6] I. Akyildiz, D. Pompili, and T. Melodia, “State of the art in protocol research for underwater acoustic sensor networks,” in ACM International Workshop on UnderWater Networks (WUWNet), Los Angeles, CA, USA, Sept. 2006. [7] M. Molins and M. Stojanovic, “Slotted FAMA: a MAC protocol for underwater acoustic networks,” in IEEE Oceans Conference, Singapore, May 2006, pp. 1–7. [8] D. Pompili, T. Melodia, and I. Akyildiz, “A CDMA-based medium access control for underwater acoustic sensor networks,” IEEE Trans. Wireless Commun., vol. 8, no. 4, pp. 1899–1909, Apr. 2009. [9] F. Salva-Garau and M.Stojanovic, “Multi-cluster protocol for ad hocmobile underwater acoustic networks,” in IEEE Oceans Conference, San Diego, CA, USA, Sept. 2003. [10] T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms, 2nd ed. MIT Press and McGraw-Hill, 2001. [11] R. Diamant and A. Sinai, “A novel architecture for multi-hops ad-hoc underwater acoustic sensor networking,” in Acoustics 2008, Paris, France, June-July 2008. 18 18

Thank you Questions? 19 19