Limited Contribution of Self-Management in Chaotic Wireless Deployments Presented by Karl Deng.
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Transcript of Limited Contribution of Self-Management in Chaotic Wireless Deployments Presented by Karl Deng.
Limited Contribution ofSelf-Management in Chaotic Wireless Deployments
Presented by Karl Deng
Measurement
Devise self-managing algorithms:
Channel assignment algorithm
Rate adaptation algorithm
Power control algorithm
Limited Contribution
No
Yes (but problematic)
No
No
Channel assignment algorithm
In combination with careful channel assignment, our power control algorithms attempt to minimize the interference between neighboring APs by ...
Where is the channel assignment algorithm?
Effect of Optimal Static Channel Allocation (Section 4.3.1)Improves performance significantly
Rate adaptation algorithm
Bear little relationship with minimizing interference.
Fixed power Rate Selection Algorithms (Section 7.2) ARF (Auto Rate Fallback) ERF (Estimated Rate Fallback)
Two algorithms that combine power and rate control to try to minimize interference (Section 7.3)
PARF (Power-controlled Auto Rate Fallback) PERF (Power-controlled Estimated Rate Fallback)
Rate adaptation algorithm
How do you combine power and rate control?
ARF - Rate selection via in-band probingPARF - Power selection via in-band probingERF - Rate selection via SNR measurementPERF - Power selection via SNR measurement
The only “combine”:“If failures continue, the transmit power is raised until the maximum transmit power is reached after which rate fallback begins.” Rate control only happens when using maximum transmit power. Such rate control does not help to reduce interference.
Such relation is not “combine”, but only some “similarity”
Rate adaptation algorithm
In Section 9 (“Discussion”):
LPERF (Load-sensitive, Power-controlled Estimated Rate Fallback)
Reduce the power as long as the resulting transmissionrate is sufficient to support the actual traffic demands.
Conclusion: Using the LPERF technique is very difficult.
Power control algorithmProblematic:
Socially responsible power control algorithmsIndividual access points and clients behave in an altruistic manner
Not simply relying on the altruism of end users Equipment vendors implement the algorithms (From their point-of-view, reducing interference is beneficial.) Regulatory mandates New technology is quickly adopted in chaotic networks. Many users in chaotic networks do not change factory default settings
Power control algorithm(Continue) Backward compatibility
Heterogeneous transmit power levels cause problemsExample: “asymmetric carrier sense” (Section 8.1, Figure 13)“When using power control, care must be taken …, an AP-client link should not reduce power so much that it becomes overwhelmed by neighboring uncooperative high power nodes.” But how?
Barrier for future technology (forward compatibility)E.g., signal measurement could be even harder. (Recall why we use CSMA/CA not CSMA/CD.)
Power control algorithm(Continue) Backward compatibility
Heterogeneous transmit power levels cause problems Compatibility with old APs
Compatibility with clientsPERF requires receiver side cooperation:
• SNR is measured at receiver (client)• Receiver feeds back power decrease decision
Client side power control is ignored Assumption: Amount of upload traffic is small. What about p2p traffic? What about multiple clients, variant range?
Measurement
Devise self-managing algorithms:
Channel assignment algorithm
Rate adaptation algorithm
Power control algorithm
Limited Contribution
No
Yes (but problematic)
No
?
Measurement Contribution
Qualitative results are straightforward:
Lower transmission power lower interference Lower client or AP density lower interference Optimize channel allocation lower interference
Quantitative results are not representative:
Only one sample – a 20-node topology derived from the MetropolisWardrive data set.