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Monday, 24 August 2009


Session 3: Network Architecture (Chair: Renata Teixeira, LIP6)

De-anonymizing the Internet Using Unreliable IDs

Yinglian Xie (Microsoft Research Silicon Valley), Fang Yu (Microsoft Research Silicon Valley), Martín Abadi (Microsoft Research Silicon Valley and UCSC)

· The Internet is open and anonymous. Therefore, attackers that generate malicious traffic cannot typically be held accountable.

· HostTracker is presented. It tracks dynamic bindings between hosts and IP addresses by leveraging application-level data with unreliable IDs.

· They use a month-long user login trace from a large email provider

· HostTracker can attribute most of the activities reliably to the responsible hosts, despite the existence of dynamic IP addresses, proxies, and NATs.

SmartRE: An Architecture for Coordinated Network-wide Redundancy Elimination

Ashok Anand (University of Wisconsin-Madison), Vyas Sekar (Carnegie Mellon University), Aditya Akella (University of Wisconsin-Madison)

· Application-independent Redundancy Elimination (RE) (identifying and removing repeated content from network transfers), is used to improve network performance.

· A network-wide RE service would be beneficial for ISPs (to reduce link loads, increase effective network capacity)

· The authors present SmartRE, a architecture for network-wide RE.

· SmartRE enables more effective utilization of the available resources at network devices.

· They used real and synthetic traces to evaluate.

Design and Implementation of High Performance Dual-radio Mesh Networks

Aditya Dhananjay (New York University), Jinyang Li (New York University), Lakshminarayanan Subramanian (New York University), Hui Zhang (Tsinghua University)

· How to realise the full potential of a multi-radio mesh network? 1) how to assign channels to radios at each node to minimize interference; 2) how to choose high throughput routing paths in the face of lossy links, variable channel conditions and external load?

· ROMA is a distributed channel assignment and routing protocol that achieves good multi-hop path performance.

· They assign non-overlapping channels to links along each gateway path to eliminate intra-path interference.

· They reduce inter-path interference by assigning different channels to paths destined for different gateways whenever possible.

· They evaluated on a 24-node dual-radio testbed.

Session 4: Novel Aspects to Networking (Chair: Jon Crowcroft, Cambridge University)

Pathlet Routing

P. Brighten Godfrey (University of Illinois at Urbana-Champaign), Igor Ganichev (UC Berkeley), Scott Shenker (ICSI and UC Berkeley), Ion Stoica (UC Berkeley)

· Pathlet is a new routing protocol.

· Networks advertise fragments of paths (pathlets) that sources concatenate into end-to-end source routes.

· Pathlet routing can emulate the policies of BGP, source routing, and several recent multipath proposals.

· When a router's routing policy has only local constraints, it can be represented using a small number of pathlets, leading to very small forwarding tables

· Pathlet does not impose a global requirement on what style of policy is used, but rather allows multiple styles to coexist.

Cutting the Electric Bill for Internet-Scale Systems

Asfandyar Qureshi (MIT), Hari Balakrishnan (MIT), John Guttag (MIT), Bruce Maggs (Akamai/CMU), Rick Weber (Akamai)

· Energy expenses are becoming an increasingly important fraction of data center operating costs.

· Energy expense per unit of computation can vary significantly between two different locations.

· The paper characterizes the variation due to fluctuating electricity prices.

· Existing distributed systems should be able to exploit this variation for significant economic gains.

· Electricity prices exhibit both temporal and geographic variation.

· They use simulation to quantify the possible economic gains for a realistic workload.

· Existing systems may be able to save millions of dollars a year in electricity costs.

Persona: An Online Social Network with User-Defined Privacy

Randolph Baden University of Maryland Adam Bender (University of Maryland), Daniel Starin (University of Maryland), Neil Spring (University of Maryland), Bobby Bhattacharjee (University of Maryland)

· In OSNs users share private content, and trust the OSN service.

· Persona is an OSN where users dictate who may access their information.

· They hide user data with attribute-based encryption (ABE), allowing users to apply fine-grained policies over who may view their data

· They describe an implementation of Persona that replicates Facebook applications and show that Persona provides acceptable performance.

Session 5: Wireless Networking 2 (Chair: Suman Banerjee, University of Wisconsin at Madison)

In Defense of Wireless Carrier Sense

Micah Z. Brodsky (MIT), Robert T. Morris (MIT)

· The wireless medium is semi shared

· Carrier Sense: “Can I talk now?”. Interference protection and space reuse. Very simple.

· Is it too simple? If networks are far apart, concurrency is the best option. If they are close, time mux. What about in the middle?

· Main question: How well does CS work?

· When does CS works well? When interferer is very far away, or when it is very close to the sender. Intermediate distance is the hard case. What about shadows and obstacles?

· They start with a simple model, only 2 contending tx, with same power, omni antennas

· The effect of varying sender-sender distance is investigated.

· They use a standard model for radio propagation that include path loss and environmental shadowing. They ignore multipath fading because wideband channels average this away.

· They use Shannon capacity as a model for throughput (Adaptive bit rate)

· Answer for intermediate problem: Adaptive Bit Rate.

· Obstacles aren’t fatal. Usually you have alternate propagation paths.

· By analysing average throughput, they realise Carrier Sense works.

· Intuitions summary: Distant interferers affect receivers uniformly; nearby interferes don’t but they’re loud so everybody prefers mux anyway; rate adaptation helps in intermediate situation; and shadowing is not such a big problem.

· Implications for future research: adaptive bit rate is essential.; hidden terminals can be a problem in terms of reliability, but they don’t matter much for average performance; exposed terminals don’t cost very much, if ABR is working.

· Carrier sense does work. There is room for improvement, but not much in overall performance.

Interference Alignment and Cancellation

Shyamnath Gollakota (MIT), Samuel D. Perli (MIT), Dina Katabi (MIT)

· MIMO LANs increase throughput by sending more concurrent packets.

· In this paper the authors present a technique that doubles concurrent packets in MIMO LAN

· Concurrent MIMO decodes as many concurrent packets as there are antennas per AP. Can we do better?

· With 2 antennas, current MIMO LANs can decode only 2 packets. All current MIMO LANs are limited by number of antennas per AP.

· What if the APS coordinate over the Ethernet? 2 APs with 2 antennas each could communicate via Ethernet, and then decode more than 2 packets. But there is an impractical overhead in this solution. Can we leverage the Ethernet with minimal overhead?

· Their solution: Interference Alignment and Cancelation (IAC)

· IAC overcomes the antennas per AP throughput limit. A packet is decoded then broadcasted once on the Ethernet, with minimal overhead.

· Contributions of the work: first MIMO LAN to overcome the antennas per AP limit; IAM synthesises interference alignment and cancelation; IAM doubles MIMO throughput; implementation of the scheme in software radios to prove this.

· For a large number of antennas, IAC doubles MIMO throughput

· They tested with a 20 node testbed. Uplink gain: IACs median gain is 2.1x better than current MIMOs. Gain is partially due to diversity but even more to concurrency. Downlink: IAC median gain is 1.5x. IAC is beneficial across the operational range of SNRs.

DIRC: Increasing Indoor Wireless Capacity Using Directional Antennas

Xi Liu (Carnegie Mellon University), Anmol Sheth (Intel Research Seattle), Michael Kaminsky (Intel Research Pittsburgh), Konstantina Papagiannaki (Intel Research Pittsburgh), Srinivasan Seshan (Carnegie Mellon University), Peter Steenkiste (Carnegie Mellon University)

· Driving demand for wireless capacity. Interference can be a big issue.

· Goal: use directional antennas to improve wireless capacity by increasing spatial reuse.

· They use phased array antennas – they electronically steer the signal to a specific direction, hence having small reconfiguration time. They assume that only APs use these antennas – they are too bulky for clients.~

· Limitations in indoor environment: LOS may be blocked, indoor space is rich scattered. The conventional wisdom is that directional antennas are not effective in indoors environment.

· Key idea: leverage multiple paths and obstacles to improve spatial reuse

· How to find antenna orientations? 1) Naive solution, max cap, is too slow. The objective is to find optimal antenna orientations quickly.

· How to coordinate between antennas? They use a centralised controller, and TDMA scheduling MAC. They also separate directional and omni-directional antennas.

· They made measurements in 2 indoor environments: 3 directional APs and 6 omni clients in each testbed.

· 2x improvement over OMNI CSMA and 1.6x over MAX SNR.

· Conclusion: coordination is required to use directional antennas effectively in indoors environments

Wednesday, 19 August 2009


Keynote Speech

Great keynote speech by the winner of the SIGCOMM award (well deserved!): Jon Crowcroft. Here are the slides:


Session 1: Wireless Networking 1 (Chair: Brad Karp, University College London)

Cross-Layer Wireless Bit Rate Adaptation

Mythili Vutukuru (MIT), Hari Balakrishnan (MIT), Kyle Jamieson (UCL)

· We have time varying wireless channels: due to large scale attenuation, small scale fading and interference

· So we need online bit rate adaptation: varying modulation and coding.

· Currently we have frame-based and SNR based algorithms for this.

· They have problems: slow, need look up tables, so they propose SoftRate. Use per-bit confidences, no need for look up tables – they get interference free BER.

· SoftPHY design more general than earlier work.

· Adapts to channel accurately and quickly, robust to collision losses, 2x gains over existing protocols.

· They propose using a soft output decoder (instead of the normal decoder) in the receiver, and use a different protocol, SoftRate.

· They created a GNU radio with USERP. Physical layer was from real traces, but then used ns-3 for TCP. They used a channel simulator for some scenarios (like train travelling).

· Good results predicting the BER of the channel.

· The comparison was made with other protocols: static best (best for each packet), SNR-based and Frame based.

· Compared to the optimum (static best): was within 10% of the optimal.

· Compared to the frame based: up to 2x over best frame based (these are very slow).

· Compared to SNR based: 4x over untrained SNT based algorithms

SMACK - A SMart ACKnowledgment Scheme for Broadcast Messages in Wireless Networks

Aveek Dutta (University of Colorado at Boulder), Dola Saha (University of Colorado at Boulder), Dirk Grunwald (University of Colorado at Boulder), Douglas Sicker (University of Colorado at Boulder)

· Question: Can we reduce the ACK time for broadcast/multicast scenarios?

· Instead of each user answering at its time, multiple users response at the same time to reduce the ACK time – using OFDM.

· The objective is to speed up group communication, like route discovery, neighbour info, etc.

· Nodes are assigned unique sub carriers. They send a tone to say “yes”.

· No packet transmission + concurrent response = faster ACK

· They have made an implementation of the system.

· In summary, main idea: PHY layer signalling can be used to innovate new protocols for wireless networks.

White Space Networking with Wi-Fi like Connectivity – Best paper award

Paramvir Bahl (Microsoft Research), Ranveer Chandra (Microsoft Research), Thomas Moscibroda (Microsoft Research), Rohan Murty (Harvard University), Matt Welsh (Harvard University)

· Main objective: How to build a wireless network using the white spaces?

· Spectrum allocation: there is more spectrum for broadcast TV than to WiFi.

· Moving from analog TV to digital TV.

· White spaces: unoccupied TV channels. Let's use them!

· We must not interfere with TV and mikes that are using that part of the spectrum: so we can use it iff no one else is using it.

· So we have more spectrum (3x that of 802.11g) and longer range (at least 3 to 4x WiFi)

· Goal: deploy infrastructure wireless – give good throughput without interfering with incumbents (TV and mike)

· Problems: fragmentation of spectrum (so we have variable channel widths), location impacts spectrum availability (spectrum exhibits spatial variation), and there is also temporal variation (incumbents appear/disappear over time).

· They’ve built the WhiteFi system – to evaluate by deployment of prototypes and by simulations.

· How do the new clients know which channels to use (discovery time)? They infer by analysing for how long the amplitude of a received signal is increased. They achieve a 2x reduction of discovery time for 30MHz width.

· Spectrum assignment algorithm: they implement MCHAM – a multi channel airtime metric. They consider not only if the channel has room, but also how much it has.

Session 2: Datacenter Network Design (Chair: Stefan Saroiu, Microsoft Research)

PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric

Radhika Niranjan Mysore (University of California San Diego), Andreas Pamboris (University of California San Diego), Nathan Farrington (University of California San Diego), Nelson Huang (University of California San Diego), Pardis Miri (University of California San Diego), Sivasankar Radhakrishnan (University of California San Diego), Vikram Subramanya (University of California San Diego), Amin Vahdat (University of California San Diego)

· Portland is a single logical layer 2 data centre network fabric. It separates host identity (IP) with host location (a “PMAC”).

· Data centres are growing in scale

· Goals for data centre network fabrics: plug and play, scalability, small switch state, seamless VM migration

· Layer 2 data centre fabrics. Advantages: plug and play, and seamless VM migration.

· Layer 3 data centre fabrics. Advantages: scalability, small switch state.

· With flat address you need about 100MB of chip memory (150 times what we put in a chip today).

· Other network fabrics: SEATTLE (SIGCOMM08) – problems: large switch table and broadcast based routing protocol. VL2 (SIGCOMM09).

· Portland: Plug and Play + Small Switch state.

· Main assumption: Hierarchical structure of data centre networks; they are multilevel, multi-routed tree.

· They impose a hierarchy on a multi-rooted tree.

VL2: A Scalable and Flexible Data Center Network

Albert Greenberg (Microsoft Research), Navendu Jain (Microsoft Research), Srikanth Kandula (Microsoft Research), Changhoon Kim (Princeton), Parantap Lahiri (Microsoft Research), David A. Maltz (Microsoft Research), Parveen Patel (Microsoft Research), Sudipta Sengupta (Microsoft Research)

· Cloud service data centre need to be agile (assign any servers to any services) and must scale out.

· VL2: First DC network that enables agility in a scaled out fashion.

· They analysed a large cluster, and realised that traffic patterns are highly volatile and unpredictable – so optimisation should be made frequently and rapidly

· We need a huge L2 switch, or an abstraction of one

· VL2 achieves agility at scale via 1) L2 semantics, 2) uniform high capacity between server, and 3) performance isolation between services

· Lessons: 1) randomisation can tame volatility, 2) add functionality where you have control, 3) there’s no need to wait.

BCube: A High Performance, Server-centric Network Architecture for Modular Data Centers

Chuanxiong Guo (Microsoft Research Asia), Guohan Lu (Microsoft Research Asia), Dan Li (Microsoft Research Asia), Haitao Wu (Microsoft Research Asia), Xuan Zhang (Tsinghua University), Yunfeng Shi (Peking University), Chen Tian (Huazhong Universtiy of Science and Technology), Yongguang Zhang (Microsoft Research Asia), Songwu Lu (UCLA)

· Novel network architecture for container based, modular data centres.

· BCube design goals: high network capacity for various traffic patterns (one to one unicast, one to all and one to several groupcast, and all to all data shuffling); only use low-end commodity switches, graceful performance degradation

· BCube is a server centric network.

· They compare their system with Tree, Fat-Tree, and DCell+, achieving higher performances.

Tuesday, 18 August 2009


MobiHeld Session III: Services

Chair: Lakshminarayanan Subramanian (New York University)

Virtual Individual Servers as Privacy-Preserving Proxies for Mobile Devices

Ramón Cáceres (AT&T Labs), Landon Cox (Duke University), Harold Lim (Duke University), Amre Shakimov (Duke University), Alexander Varshavsky (AT&T Labs)

· Main goal: keeping ownership and control of your data

· Idea: each person has its own virtual machine

· People increasingly upload content from their mobile devices to 3rd party services (facebook, twitter, etc.)

· This leads to privacy issues. They focus on 2 issues: 1) these services are centralised (vulnerable to large scale privacy breaches), 2) terms of service often grant provider rights to user data

· Virtual Individual Servers: instead of uploading our info to 3rd party services, upload data to a VIS (a machine the user owns). Individuals maintain rights to their data. Data is distributed across many administrative domains.

· Advantages: privacy, flexibility (my own machine, I can install whatever I like), long term availability, cost scalability

· Disadvantages: management burden (users are bad to manage their machines at home, so managing a virtual machine will be complicated), cost to the individual

· VISs vs. serving data from devices – advantages: resource richness, high availability; disadvantages: requires access to wired infrastructure, need network connection

D^3N: Programming Distributed Computation in Pocket Switched Networks

Eiko Yoneki (University of Cambridge), Ioannis Baltopoulos (University of Cambridge), Jon Crowcroft (University of Cambridge)

· Evolution of mobile networks: a more disconnected network: a path from A to B may exist, but only over time.

· Looking at human to human connectivity

· Use of declarative networking

Apprehending Joule Thieves with Cinder

Stephen M. Rumble (Stanford University), Ryan Stutsman (Stanford University), Phil Levis (Stanford University), David Mazieres (Stanford University), Nickolai Zeldovich (MIT)

· Desktop resource management: if it’s slow, add more resources

· State of mobile devices: complex... and users care about energy and network

· Future of mobile devices: need new OS mechanisms for resource management

· Consider energy as a first class resource: track it, ration it, delegate it.

· They define a “capacitor abstraction” to explain the way they manage the mobile phone energy usage –kind of a leaky bucket concept.

· Capacitors can offer fine grained tracking, rationing and delegation. They easily express real world policies.

Game Action Based Power Management for Multiplayer Online Game

Bhojan Anand (National University of Singapore), A.L. Ananda (National University of Singapore), Mun Choon Chan (National University of Singapore), Rajesh Krishna Balan (Singapore Management University), Le Thanh Long (National University of Singapore)

· Main contribution: game action based resource management

· Black box approach: Lose some packets to save energy; White box approach: reduce number of packets, use some AI to remove redundancy – both baseline approaches failed.

· Application assisted approaches: go to off or deep sleep mode, without reducing quality

· Check Player Activity Level (PAL) – if it’s low, go to sleep mode.

· Can we predict current PAL with the previous PALs? Yep.

· How long can we put the WNIC to sleep? Must find optimum.

· They also looked at the frequency of game actions (shooting, walking, etc.)

About me

e-mail: fvramos at gmail dot com