Minimal cost deployment of mesh networks with QoS requirements for indoor environment

1. Minimal cost deployment of mesh networks with QoS requirements for indoor environment Xiaohua Jia Dept of Computer Science City University of Hong Kong City Univ of Hong Kong

2. Mesh Network Architecture • Multihop WLAN (single hop) • Gateway connection MANET (no gateway) City Univ of Hong Kong

3. Mesh Network Planning Problem Problem: Given a set of users, each with QoS requirements (bandwidth and delay), find the optimal placement of AP, MP, and gateway nodes in the area such that the users QoS requirements are met and the total cost of the AP, MP, and gateway nodes is minimized. Output: 1) locations of nodes; 2) transmission power of nodes; 3) number of radios per AP. City Univ of Hong Kong

4. Related Work AP Placement in WLAN [BCC07] S. Bosio, A. Capone, and M. Cesana, “Radio Planning of Wireless Local Area Networks,” IEEE/ACM Trans on Networking, vol. 15, no. 6, pp.1414 –1427, Dec 2007. 1) Min-set cover: place Min # of APs in CSs, such each client is covered by at least one AP; 2) Min overlap problem (MoP) / Max efficiency (total throughput) plan (MeP): given N of APs (or budget), place them such MoP or MeP is optimized. [EGS07] A. Eisenblatter, H-F Geerdes and I Siomina, “Integrated Access Point Placement and Channel Assignment for Wireless LANs in an Indoor Office Environment”, IEEE Symp. on World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2007. 1) Max avg throughput of all users for placing N APs. Each user’s throughput is f(dv,AP) under fixed power of APs; 2) Min overlap APs (in terms of number of clients) using the same channel; 3) LP formulation and computed by using CPLEX. No multi-radio and rate adaption & power control. City Univ of Hong Kong

5. Related Work (cont’d) AP&MP Placement in Mesh Networks [SL06] A. So and B. Liang, “Optimal Placement of Relay Infrastructure in Heterogeneous Wireless Mesh Networks by Bender’s Decomposition,” QShine’06. 1) place min # of relays in N users positions (served & connected); 2) Mathematical Programming formulation. [WXC07] J. Wang, B. Xie, K. Cai, and D. Agrawal, “Efficient Mesh Router Placement in Wireless Mesh Networks”, IEEE MASS’07. 1) place min # MR among N candidate sites, cover service area and interconnect relay nodes. 2) two steps: a) coverage; b) connectivity No interference was considered. City Univ of Hong Kong

6. Related Work (cont’d) QoS Gateway Placement [B04] Y. Bejerano, “Efficient Integration of Multihop Wireless and Wired Networks with QoS Constraints”, IEEE/ACM Trans on Networking, Vol. 12, No. 6, Dec 2004. 1) Transformed to: clustering of graph into min number of clusters; 2) QoS: cluster size and radius; 3) TDMA for intra-cluster and use of orthogonal channels for neighbor clusters. [ABI06] B. Aoun, R. Boutaba, Y. Iraqi, and G. Kenward, “Gateway placement optimization in wireless mesh networks with QoS constraints,” IEEE Journal on Selected Areas in Communications, vol. 24, no. 11, pp. 2127 – 2136, Nov. 2006. 1) Graph partitioning based on k-hop Dominating-Set No consideration of interference for link capacity / throughput City Univ of Hong Kong

7. Unique challenges • Placement of different types of mesh nodes (AP, MP and gateway) and aiming at minimizing the total cost. • APs can be equipped with different number of access radios. • Each node (AP or MP) can adjust its transmission power and data rate is adaptive to transmission power. City Univ of Hong Kong

8. Decomposition of the problem Subproblem 1: Optimal placement of APs to serve all clients. Subproblem 2: Configure minimal number of Gateway nodes for a large cluster under QoS constraint. Subproblem 3: Merge small clusters by adding minimal number of MPs City Univ of Hong Kong

9. AP Placement with multi-radios and power control Problem: given a set of clients in an area, each client has bandwidth requirement γ. Place a set of APs W, determine number of radios for each node, and adjust power to meet γ, and the total cost is minimized: City Univ of Hong Kong

10. AP placement in indoor environment • Divide the region into grids; • Traffic demands (Clients) originate from grids; • APs are placed at the center of grids. City Univ of Hong Kong

11. Transmission power, data rate and interference • AM×M: signal attenuation array • Node v can receive data from w if: A(w,v)Pw ≥ α • Node v can be interfered by w if: A(w,v)Pw ≥ β • Data rate from v to w is (similarly for R(w,v)): R(v,w) = f(A(v,w)Pv) City Univ of Hong Kong

12. A table of transmission range, data rate and interference range City Univ of Hong Kong

13. Interference model Node interference I(w) = {v| A(w,v)Pw ≥ β} Link interference link l’ is interfered by l if one of the end-node of l’ is in the interference range of l. City Univ of Hong Kong

14. Interference and Bandwidth Constraint Network G(V, E): V set of clients and APs. A link l in E is between a client and an AP. I(l): Interference set of link l is a set of links that either interfere with l or are interfered by l, including l itself. City Univ of Hong Kong

15. Bandwidth constraint under interference • : up link and down link traffics of v • Channel bandwidth is shared by all links in the collision set I(l). That is: City Univ of Hong Kong

16. A performance metric for greedy algorithms • S(w): clients served by AP w • Max collision load: • Client to Interference Ratio CIR(w): City Univ of Hong Kong

17. Top-down method • Initialization. Each client is placed with an AP. • Choose two neighboring APs to merge to a new AP w, such that: • AP w can serve all clients of two old APs (w’s power is set to cover all clients), and meet the bandwidth constraint; • CIR(w) is maximal (locate w’s new location); • Determine the number of radios w and do channel assignment. • Repeat step (2) until no more merge can be done (i.e., CIR(w) cannot be increased by merging any two APs). City Univ of Hong Kong

18. B C A Merging with neighboring APs • The merge of APs should be between neighboring APs • We use Delaunay graph of APs to ensure the merge between neighboring APs City Univ of Hong Kong

19. Number of Radios of an AP and Channel Assignment Input: G(V, E), V: a set of APs and clients Output: k(w) and channels for radios in w, w in W • Initialization: |k(w)| = 1 for all w; • Sort all links l = (v, w) in descending order by |I(l)|; • For each link l = (v, w), assign the least used channel among links in I(l) to it. If the bandwidth constraint cannot be met (i.e., TI(l) > 1) and |k(w)| doesn’t exceed the upper bound, • Add a new radio to w; • Assign a channel to the new radio in w; City Univ of Hong Kong

20. Bottom-up method • Initially all clients are not served. • Place an AP at a grid and adjust it power such that the bandwidth constraint is met and: CIR(w) is the maximal. • Repeat the above step until all clients are served. City Univ of Hong Kong

21. Simulation results • 100m×100m region divided into 20×20 grids • pR: pB (price of radio / box) = 0.4 : 1 and γup : γdn = 1 : 9 City Univ of Hong Kong

22. Simulation results (Cont’d) City Univ of Hong Kong

23. On-going research problems… • QoS AP placement and topology control by using physical interference model (SINR model). • Capacity analysis of using multiple access radios against use of single radio. What is the performance gain compared with the cost? • k-coverage (k = 2) AP placement. Given per client’s bandwidth requirement γ1 if served by its primary AP, and γ2 if its primary AP failed, place minimal number of APs (and adjust power) such that each client is covered by at least k APs and γ1 and γ2 are met for fault tolerance. City Univ of Hong Kong

24. Thanks! Q & A City Univ of Hong Kong