Page 1. Overview : Wireless Networks Lecture 15: WiFi Self-Organization. Client throughput. What determines client performance?

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1 Overview : Wireless Networks Lecture 15: WiFi Self-Organization Dina Papagiannaki & Peter Steenkiste Departments of Computer Science and Electrical and Computer Engineering Spring Semester Self-organization/Management of WiFi networks Urban, cooperative environments (unmanaged)» Frequency selection» User association» Power control Enteprise WLANs (managed) New application domains (unmanaged +managed) 2 Design of the Wired Overprovisioning the solution of choice! From a managed core to an unmanaged edge A large fraction of the s clients are going wireless (WiFi, 3G, WiMax) Client performance primarily determined by the edge network networks challenge our traditional thinking in network design and management The need for measurement paramount due to the unreliability and dynamics of the medium, the notion of contention domains and mobility 3 4 What determines client performance? Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) Transmitter senses the medium, uses Clear Channel Assessment (CCA) threshold to determine state If medium idle, randomize access When backoff counter=0, transmit Upon ACK, reset backoff counter If no ACK, double contention window, adjust transmission rate and try again Performance = f(access probability, retransmissions, link quality, hidden terminals) Client throughput 11 Mbps 54 Mbps 1 Mbps Effective throughput~ 30 Mbps Effective throughput< 10 Mbps Effective throughput ~Kbps 5 6 Page 1

2 Solutions and operations Minimize the number of transmitters in the same contention domain Frequency selection Power Control Minimize the number of transmitters in the same contention domain Ensure high quality links between clients and APs Frequency selection Power Control User Association Self-Organization in Urban, Collaborative Environments Frequency Selection Minimize the effect of hidden terminals RTS/CTS Scheduling 7 8 WiFi frequency selection Cellular analogue 2.4 GHz band (802.11b/g) 11 channels, 3 orthogonal 5 GHz band (802.11a) 11/12 channels depending on continent Question: Which frequency should each AP operate on for optimal performance? b/g frequencies not enough WiFi scanning tools: NetStumbler Page 2

3 Frequency Selection Effect of Frequency Selection Mbps/11g Client1 Client2 Client3 Before After (*3) 30 (*5) (*2) AP client Alternatives Partially overlapping channels Interference is the outcome of transmissions! Frequency selection could take workload into account» Requires additional measurements» Could lead to instability if based on variable measurements Using partially overlapping channels Minimize the number of transmitters in the same contention domain Frequency selection Power Control Self-Organization in Urban, Collaborative Environments Power Control Partially overlapped channels not considered harmful, In ACM Sigmetrics Page 3

4 Power Control in What is the benefit of power control? Heterogeneous transmit powers across nodes can lead to node starvation! 1 st order starvation Reducing transmission power can reduce interference in the network Increasing transmission power can improve client SINR thus allowing for higher transmission rates There is a tradeoff between the amount of interference we introduce in the network and the additional throughput benefit at the client We need to ensure that there is symmetry in the nodes contention domains Condition for starvation free power control Effect of Power Control We need to ensure network symmetry We have proven that for starvation-free power control we need to keep the product of CCA threshold and transmission power constant CCA * P = C The louder you are going to shout the more carefully you should listen for the nodes that whisper Mbps/11g Client1 Client2 Client3 Interference Mitigation through Power Control in High Density WLANs, IEEE Infocom 2007 Before After (*3) (*4) (*2) AP client Ensure high quality links between clients and APs User Association Self-Organization in Urban, Collaborative Environments User Association User throughput 1. Channel access time 2. Aggregated transmission delay 3. Wireless channel quality State of the art can lead to unnecessarily low throughput! Page 4

5 Overall network fairness improved User association Mean:1428, variance: Mean:1559, variance: Mbps/11g Client1 Before Balance the user associations~ 5for minimal potential delay ~ 8 the personal and social fairness. UsersAfter take into account cost of different association rules. 25 Implementation and Experimental set-up 26 Impact of different algorithms The 3 algorithms are implemented» for both APs and clients» on Intel 2915 prototype driver and firmware Testbed A : U Cambridge, UK» 21 APs, 30 client Technical Characteristics» Nodes: Soekris net4826,» Wireless cards: Intel 2915 a/b/g 5-dBi omnidirectional antennae 27 Minimize the effect of hidden terminals The transformation of enterprise WLANs RTS/CTS Scheduling Self-Organization in Enterprise WLANs: From Collaboration to Coordination 28 Centralization of the control increased security, opportunity for optimal configuration 29 Page 5 30

6 Hidden and Exposed Terminals WLANs HP Labs Seoul National University Exposed Terminals Hidden Terminals 39% 9% 39% 43% 70% 35% Our Testbed Conflict Graph and its measurement Micro-probing can measure the conflict graph of a 20 node network in 20 seconds! In 30% of the hidden terminals (300 cases) performance degradation was greater than 90%! Carrier-sense Interference No client modifications As accurate as state of the art with ~400 times less overhead Centralized Scheduling Implementation Issues C4 X C1 Y C3 (X,C1) (Y,C2) (Y,C3) (X,C4) Need for a conflict graph Tight synchronization among APs Precise knowledge of when a transmission will be over (not easy due to retransmission and changes in transmission rate) C2 Speculation is required! Scheduler DCF performs better in the general case! Hybrid Scheduling The network design space Use speculative centralized scheduling only for hidden terminals management power control, user association Frequency selection, power control Centralized control and scheduling More devices on the same frequency overhearing PHY coding conscious choice reachability, minimal handoff time 35 Network density No single design will fit-all understanding constraints and solution space is essential. Applications will be the main drivers 36 Page 6

7 The FON model large scale WiFi collaboration When collaboration meets coordination The Neighborhood Network Management degree home Neighborhood Network Enterprise Next-generation community networks Community WiFi Community networks today seen as infrastructure for access and services on the move [Cabernet, ViFi, Dome] What if such networks formed the new edge with the ability to provide better and new types of services? New Types of Services in Neighborhood WiFi Today s home use Reliability through broadband provider diversity Higher uplink capacity through wireless-assisted broadband link aggregation Services beyond the limitations of one home s resources Most broadband connections underutilized Wireless speeds far exceed last mile broadband Page 7

8 Large uploads are very slow! Burstable broadband service zzz.. zzz..!?! Burstable broadband service Burstable broadband service Aggregation through wireless What is the best strategy to get efficient aggregation of bandwidth? Wireless unicast Opportunistic wireless reception Wireless unicast Opportunistic broadcast??? Problem: Individual losses can significantly harm performance. 47 Solution needs to minimize redundancy in wired transmissions while making optimal use of the wireless medium 48 Page 8

9 Link-alike offers significant gains through opportunism Open Questions 49 How could such a mechanism be adjusted for real-time content, such as high resolution video conferencing? Automated frequency selection restricts the number of APs in the same frequency, limiting the potential for overhearing What are the mechanisms needed for optimal performance of neighborhood networks? 50 US Spectrum Allocation 700 MHz and white spaces Beyond the ISM bands WiFi 51 References Partially-overlapped Channels not considered harmful, Arunesh Mishra, Vivek Shrivastava, Suman Banerjee, William Arbaugh. In ACM Sigmetrics, St. Malo, France, June MDG: Measurement-Driven Guidelines for WLAN Design, I. Broustis, K. Papagiannaki, S. Krishnamurthy, M. Faloutsos, and V. Mhatre. In ACM Mobicom, Montreal, Canada, September Interference Mitigation through Power Control in High Density WLANs, V. Mhatre, K. Papagiannaki and F. Baccelli. In IEEE Infocom, Anchorage, Alaska, May, Measurement-Based Self Organization of Interfering Wireless Access Networks, B. Kaufmann, F. Baccelli, A. Chaintreau, V. Mhatre, K. Papagiannaki and C. Diot. In IEEE Infocom, Anchorage, Alaska, May, Link-alike: Using Wireless to Share Network Resources in a Neighborhood, S. Jakubczak, D. Andersen, M. Kaminsky, K. Papagiannaki, and S. Seshan. To appear in ACM Sigmobile Mobile Computing and Communications Review (MC2R) 53 Page 9 52