Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers' access to the medium. Although the scheduler delivers opportunistic gains, it misses some of the inherent features of the 802.11 MAC. For example, it prevents spatial reuse and thus may underutilize the wireless medium. It also eliminates the layering abstraction, making the protocol less amenable to extensions to alternate traffic types such as multicast.This paper presents MORE, a MAC-independent opportunistic routing protocol. MORE randomly mixes packets before forwarding them. This randomness ensures that routers that hear the same transmission do not forward the same packets. Thus, MORE needs no special scheduler to coordinate routers and can run directly on top of 802.11. Experimental results from a 20-node wireless testbed show that MORE's median unicast throughput is 22% higher than ExOR, and the gains rise to 45% over ExOR when there is a chance of spatial reuse. For multicast, MORE's gains increase with the number of destinations, and are 35-200% greater than ExOR.

/pdf/trading-structure-for-randomness-in-wireless-opportunistic-284e2q0xeo.pdf

Trading structure for randomness in wireless opportunistic routing

A super-peer is a node in a peer-to-peer network that operates both as a server to a set of clients, and as an equal in a network of super-peers. Super-peer networks strike a balance between the efficiency of centralized search, and the autonomy, load balancing and robustness to attacks provided by distributed search. Furthermore, they take advantage of the heterogeneity of capabilities (e.g., bandwidth, processing power) across peers, which recent studies have shown to be enormous. Hence, new and old P2P systems like KaZaA and Gnutella are adopting super-peers in their design. Despite their growing popularity, the behavior of super-peer networks is not well understood. For example, what are the potential drawbacks of super-peer networks? How can super-peers be made more reliable? How many clients should a super-peer take on to maximize efficiency? we examine super-peer networks in detail, gaming an understanding of their fundamental characteristics and performance tradeoffs. We also present practical guidelines and a general procedure for the design of an efficient super-peer network.

Designing an Super-Peer Network

RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (

/pdf/predictable-802-11-packet-delivery-from-wireless-channel-2r2rb9i2xd.pdf

Predictable 802.11 packet delivery from wireless channel measurements

This paper presents ZigZag, an 802.11 receiver design that combats hidden terminals. ZigZag's core contribution is a new form of interference cancellation that exploits asynchrony across successive collisions. Specifically, 802.11 retransmissions, in the case of hidden terminals, cause successive collisions. These collisions have different interference-free stretches at their start, which ZigZag exploits to bootstrap its decoding.ZigZag makes no changes to the 802.11 MAC and introduces no overhead when there are no collisions. But, when senders collide, ZigZag attains the same throughput as if the colliding packets were a priori scheduled in separate time slots. We build a prototype of ZigZag in GNU Radio. In a testbed of 14 USRP nodes, ZigZag reduces the average packet loss rate at hidden terminals from 72.6% to about 0.7%.

/pdf/zigzag-decoding-combating-hidden-terminals-in-wireless-282gpsraz4.pdf

Zigzag decoding: combating hidden terminals in wireless networks

We design truthful double spectrum auctions where multiple parties can trade spectrum based on their individual needs. Open, market-based spectrum trading motivates existing spectrum owners (as sellers) to lease their selected idle spectrum to new spectrum users, and provides new users (as buyers) the spectrum they desperately need. The most significant challenge is how to make the auction economic-robust (truthful in particular) while enabling spectrum reuse to improve spectrum utilization. Unfortunately, existing designs either do not consider spectrum reuse or become untruthful when applied to double spectrum auctions. We address this challenge by proposing TRUST, a general framework for truthful double spectrum auctions. TRUST takes as input any reusability-driven spectrum allocation algorithm, and applies a novel winner determination and pricing mechanism to achieve truthfulness and other economic properties while significantly improving spectrum utilization. To our best knowledge, TRUST is the first solution for truthful double spectrum auctions that enable spectrum reuse. Our results show that economic factors introduce a tradeoff between spectrum efficiency and economic robustness. TRUST makes an important contribution on enabling spectrum reuse to minimize such tradeoff.

https://www.cs.dartmouth.edu/~xia/papers/infocom09-slides.pdf

TRUST: A General Framework for Truthful Double Spectrum Auctions

We present practical models for the physical layer behaviors of packet reception and carrier sense with interference in static wireless networks. These models use measurements of a real network rather than abstract RF propagation models as the basis for accuracy in complex environments. Seeding our models requires N trials in an N node network, in which each sender transmits in turn and receivers measure RSSI values and packet counts, both of which are easily obtainable. The models then predict packet delivery and throughput in the same network for different sets of transmitters with the same node placements. We evaluate our models for the base case of two senders that broadcast packets simultaneously. We find that they are effective at predicting when there will be significant interference effects. Across many predictions, we obtain an RMS error for 802.11a and 802.11b of a half and a third, respectively, of a measurement-based model that ignores interference.

/pdf/measurement-based-models-of-delivery-and-interference-in-2isex14t7p.pdf

Measurement-based models of delivery and interference in static wireless networks

We analyze wireless measurements taken during the SIGCOMM 2004 conference to understand how well 802.11 operates in real deployments. We find that the overhead of 802.11 is high, with only 40% of the transmission time spent in sending original data. Most of the remaining time is consumed by retransmissions due to packet losses that are caused by both contention and transmission errors. Our analysis also shows that wireless nodes adapt their transmission rates with an extremely high frequency. We comment on the difficulties and opportunities of working with wireless traces, rather than the wired traces of wireless activity that are presently more common.

/pdf/measurement-based-characterization-of-802-11-in-a-hotspot-404z0839bn.pdf

Measurement-based characterization of 802.11 in a hotspot setting

We present Wit, a non-intrusive tool that builds on passive monitoring to analyze the detailed MAC-level behavior of operational wireless networks. Wit uses three processing steps to construct an enhanced trace of system activity. First, a robust merging procedure combines the necessarily incomplete views from multiple, independent monitors into a single, more complete trace of wireless activity. Next, a novel inference engine based on formal language methods reconstructs packets that were not captured by any monitor and determines whether each packet was received by its destination. Finally, Wit derives network performance measures from this enhanced trace; we show how to estimate the number of stations competing for the medium. We assess Wit with a mix of real traces and simulation tests. We find that merging and inference both significantly enhance the originally captured trace. We apply Wit to multi-monitor traces from a live network to show how it facilitates 802.11 MAC analyses that would otherwise be difficult or rely on less accurate heuristics.

/pdf/analyzing-the-mac-level-behavior-of-wireless-networks-in-the-1jp5vhg0xa.pdf

Analyzing the MAC-level behavior of wireless networks in the wild

Multi-hop wireless networks are vulnerable to free-riders because they require nodes to forward packets for each other. Deployed routing protocols ignore this issue while proposed solutions incorporate complicated mechanisms with the intent of making free-riding impossible. We present Catch, a protocol that falls between these extremes. It achieves nearly the low mechanism requirements of the former while imposing nearly as effective barriers to free-riding as the latter. Catch is made possible by novel techniques based on anonymous messages. These techniques enable cooperative nodes to detect nearby free-riders and disconnect them from the rest of the network. Catch has low overhead and is broadly applicable across routing protocols and traffic workloads. We evaluate it on an 802.11 wireless testbed as well as through simulation.

/pdf/sustaining-cooperation-in-multi-hop-wireless-networks-tay5pgkafy.pdf

Sustaining cooperation in multi-hop wireless networks

We applied techniques from game theory to help formulate and analyze solutions to two systems problems: discouraging selfishness in multi-hop wireless networks and enabling cooperation among ISPs in the Internet. It proved difficult to do so. This paper reports on our experiences and explains the issues that we encountered. It describes the ways in which the straightforward use of results from traditional game theory did not fit well with the requirements of our problems. It also identifies an important characteristic of the solutions we did eventually adopt that distinguishes them from those available using game theoretic approaches. We hope that this discussion will help to highlight formulations of game theory which are well-suited for problems involving computer systems.

/pdf/experiences-applying-game-theory-to-system-design-4wgvju4vll.pdf

Maya Rodrig

Papers

Measurement-based models of delivery and interference in static wireless networks

Measurement-based characterization of 802.11 in a hotspot setting

Analyzing the MAC-level behavior of wireless networks in the wild

Sustaining cooperation in multi-hop wireless networks

Experiences applying game theory to system design