Hi from all of us here in Prague -- this is day 1 of Eurosys and we'll be running the live blog as usual!
I am at the Doctoral Workshp at EuroSys in Prague today, ahead of the main conference. Below are some notes on the 5 minutes presentations in the workshop. There are no notes on the first quarter of the workshop because I talked about my work as well.
Various people from Cambridge are currently in Bern für EuroSys 2012, and will be reporting live from the conference here, as well as summarizing the trends and highlights afterwards.
The second day has kicked off, and we will be providing the usual live update service below the fold -- click "continue reading" to get there!
3rd and final day... mainly about PHY/MAC layer and theory works
The day started with a Keynote by Farnan Jahanian (University of Michigan, NSF). Jahanian talked about some opportunities behind cloud computing research. In his opinion, cloud computing can enable new solutions in fields such as health-care and also environmental issues. As an example, it can help to enforce a greener and more sustainable world and to predict natural disasters (e.g. the recent japanese tsunami) with the suport of a wider sensor network. His talk concluded with a discussion about some of the challenges regarding computer science research in the US (which seem to be endemic in other countries). He highlighted that despite the fact that the market demands more computer science graduates, few students are joining related programs at every level, including high school.
Session 7. MAC/PHY Advances.
No Time to Countdown: Migrating Backoff to the Frequency Domain, Souvik Sen and Romit Roy Choudhury (Duke University, USA); and Srihari Nelakuditi (University of South Carolina, USA)
Conventional WiFi networks perform channel contention in time domain. Such approach imposes a high channel wastage due to time back-off. Back2F is a new way of enabling channel contention in the frequency domain by considering OFDM subcarriers as randomised integer numbers (e.g. instead of picking up a randomised backoff length, they choose a randomly chosen subcarrier). This technique requires incorporating an additional listening antenna to allow WiFi APs to learn about the backoff value chosen by nearby access points and decide if their value is the smallest among all others generated by close-proximity APs. This knowledge is used individually by each AP to schedule transmissions after every round of contention. Nevertheless, by incorporating a second round of contention, the APs colliding in the first one will be able to compete again in addition to a few more APs. The performance evaluation was done on a real environment. The results show that the collision probability decreases considerable with Back2F with two contention rounds. Real time traffic such as Skype experiences a throughput gain but Back2F is more sensitive to channel fluctuation.
Harnessing Frequency Diversity in Multicarrier Wireless Networks, Apurv Bhartia, Yi-Chao Chen, Swati Rallapalli, and Lili Qiu (University of Texas at Austin, USA)
Wireless multicarrier communication systems are based on spreading data over multiple subcarriers but SNR varies in each subcarrier. In this presentation, the authors propose a join integration of three solutions to reduce the side-effects:
- Map symbols to subcarriers according to their importance.
- Effectively recover partially corrupted FEC groups and facilitate FEC decoding.
- MAC-layer FEC to offer different degrees of protection to the symbols according to their error rates at the PHY layer
Their simulation and testbed results corroborate that a joint combination of all those techniques can increase the throughput in the order of 1.6x to 6.6x.
Beamforming on Mobile Devices: A first Study, Hang Yu, Lin Zhong, Ashutosh Sabharwal, David Kao (Rice University, USA)
Wireless links present two invariants: spectrum is scarce while hardware is cheap. The fundamental waste in cellular base stations is because of the antenna design. Lin Zhong proposed passive directional antennas to minimize this issue. They used directional antennas to generate a very narrow beam with a larger spatial coverage. They have proved that this solution is practical despite small form factor of smartphone's antenna, resistent to nodes rotation (only 2-3 dB lost if compared to a static node), and does not affect the battery life of the handsets, specially in the uplink as the antenna's beam is narrower. This technique allows calculating the optimal number of antennas for efficiency. The system was evaluated both indoors and outdoors in stationary/mobile scenarios. The results show that it is possible to save a lot of power in the client by bringing down the power consumption as the number of antennas increases with this technique.
SESSION 8. Physical Layer
FlexCast: Graceful Wireless Video Streaming, S T Aditya and Sachin Katti (Stanford University, USA)
This is a scheme to adapt video streaming to wireless communications. Mobile video traffic is growing exponentially and users' experience is very poor because of channel conditions. MPEG-4 estimates the quality over long timescales but channel conditions change rapidly thus it has an impact on the video quality. However, current video codecs are not equipped to handle such variations since they exhibit an all or nothing behavior. They propose that quality is proportional to instantaneous wireless quality, so a receiver can reconstruct a video encoded at a constant bit rate by taking into account information about the instantaneous network quality.
A Cross-Layer Design for Scalable Mobile Video, Szymon Jakubczak and Dina Katabi (Massachusetts Institute of Technology, USA)
One of the best papers in Mobicom'11. Mobile video is limited by the bandwidth available in cellular networks, and lack of robustness to changing channel conditions. As a result, video quality must be adapted to the channel conditions of different receivers. They propose a cross-layer design for video that addresses both limitations. In their opinion the problem is that the compression an error protection convert real-valued pixels to bits and as a consequence, they destroy the numerical properties of original pixels. In analog TV this was not a problem since there is a linear relationship between the transmitted values and the pixels so a small perturbation in the channel was also transformed on a small perturbation on the pixel value (however, this was not efficient as this did not compress data).
SoftCast is as efficient as digital TV whilst also compressing data linearly (note that current compression schemes are not linear so this is why the numerical properties are lost). SoftCast transforms the video in the frequency domain with a transform called 3D DCT. In the frequency domain, most temporal and spatial frequencies are zeros so the compression sends only the non-zero frequencies. As it is a linear transform, the output presents the same properties. They ended the presentation with a demo that demonstrated the real gains of SoftCast compared to MPEG-4 when the SNR of the channel drops.
Practical, Real-time Full Duplex Wireless, Mayank Jain, Jung II Choi, Tae Min Kim, Dinesh Bharadia, Kanna Srinivasan, Philip Levis andSachin Katti (Stanford University, USA); Prasun Sinha (Ohio State University, USA); and Siddharth Seth (Stanford University, USA)
This paper presents a full duplex radio design using signal inversion (based on a balanced/unbalanced (Balun) transformer)and adaptive cancellation. The state of the art in RF full-duplex solutions is based on techniques such as antenna cancellation and they present several limitations (e.g. manual tuning, channel-dependent). This new design supports wideband and high power systems without imposing any limitation on bandwidth or power. The authors also presented a full duplex medium access control (MAC) design and they evaluated the system using a testbed of 5 prototype full duplex nodes. The results look promising so... now it's the time to re-design the protocol stack!
Session 9. Theory
Understanding Stateful vs Stateless Communication Strategies for Ad hoc Networks, Victoria Manfredi and Mark Crovella (Boston University, USA); and Jim Kurose (University of Massachusetts Amherst, USA)
There are many communication strategies depending on the network properties. This paper explores adapting forwarding strategies that decides when/what state communication strategy should be used based on network unpredictability and network connectivity. Three network properties (connectivity, unpredictability, and resource contention) determine when state is useful. Data state is information about data packets, it is valuable when network is not well-connected whilst control-state is preferred when the network is well connected. Their analytic results (based on simulations on Haggle traces and DieselNet) show that routing is the right strategy for control state, DTN forwarding for data-state (e.g. Haggle Cambridge traces) and packet forwarding for those which are in the data and control state simultaneously (e.g. Haggle Infocom traces).
Optimal Gateway Selection in Multi-domain Wireless Networks: A Potential Game Perspective, Yang Song, H. Y. Wong, and Kang-Won Lee (IBM Research, USA)
This paper tries to leverage a coalition of networks with multiple domains with heterogeneous groups. They consider a coalition network where multiple groups are interconnected via wireless links. Gateway nodes are designated by each domain to achieve a network-wide interoperability. The challenge is minimising the intra-domain cost and the sum of backbone cost. They used a game-perspective approach to solve this problem to analyse the equilibrium inefficiency. They consider that this solution can be also used in other applications such as power control, channel allocation, spectrum sharing or even content distribution.
Fundamental Relationship between Node Density and Delay in Wireless Ad Hoc Networks with Unreliable Links, Shizhen Zhao, Luoyi Fu, and Xinbing Wang (Shanghai JiaoTong University, China); and Qian Zhang (Hong Kong University of Science and Technology, China)
Maths, percolation theory ... quite complex to put into words
Keynote - Mobile Computing: the Next Decade and Beyond
The keynote was given by Prof. Mahadev Satyanarayanan, "Satya", (Carnegie Mellon University, MobiSys Outstanding Contributor Award). A quick look at the abstract of his talk, can be enough to see his merits.
He thinks that research on mobile computing is socially demanded. New systems and apps are motivated by the fact that the number of sales of mobile devices in 2011 overtook the sales of PCs for the first time. In his opinion, mobile computing is a common ground between distributed systems, wireless networking, context-awareness, energy awareness and adaptive systems. He highlighted the enduring challenges in this area in the last years:
- - Weight, power, size constraints (e.g. tiny I/O devices).
- - Communication uncertainty: bandwidth, latency and money. We still struggle with intermittent connectivity.
- - Finite energy. Computing, sensing and transmitting data cost energy.
- - Scarce user attention: low human performance. Users are prone to make errors and they are becoming less patient.
- - Lower privacy, security and robustness. Mobile handsets have more attack vectors and can suffer physical damage more easily.
After that, he mentioned three future emerging themes, some of them related to several ongoing projects in Cambridge:
- Mobile devices are rich sensors. They support a wide range of rich sensors and they access nearby data opportunistically (content-based search can be more energy-efficient, so looks like there's some ground for CCN here). In fact, applications can be context and energy-aware. He mentioned some of the applications from yesterday's first session as examples.
- Cloud-mobile convergence. Mobile computing allows freedom. It enables access to anything, anytime, anywehere. However, this increases complexity. On the other hand, Cloud computing provides simplicity by centralization (one source has it all). The question is: can we combine the freedom of mobility with the simplicity of cloud computing? Cloud computing evolved a lot since its first conception in 1986 (he mentioned Andrew File System as the first cloud service ever). He also highlighted that the key technology/enabler is virtualization and an example is his research about Cloudlets. Virtual Machines allow ubiquity of state and behavior so they can perfectly re-create the state anywhere, anytime. Moreover, moving clouds closer to the end-user can minimise the impact of network latency. He also talked about an still quite unexplored space: the importance of offloading computation from the cloud to local devices (the other way has been quite well explored already).
- Resource-rich mobile apps. From my perspective, this is very related to the first example. He talked about applications incorporating face recognition or the role of mobile handsets to enable applications for mobile cognitive assistance.
Session 4. When and Where
This session was more about indoors localisation. The first presentation was: Indoor location sensing using geo-magnetism (J. Chung (MIT), M. Donahoe (MIT), I. Kim (MIT), C. Schmandt (MIT), P. Razavi (MIT), M. Wiseman (MIT)). In this paper, the authors try to provide an interesting approach to the classic problem of indoors location. In their project, they use magnetic field distortion fingerprints to identify the location of the user. They used their own gadget: a rotating tower with a magnetic sensor to obtain the magnetic fingerprint on a building (sampled every 2 feet). They proved that the magnetic field on their building hasn't changed in 6 months (they haven't checked whether there are changes at different times of the day or not) so the fingerprint doesn't have to be updated frequently. They implemented their own portable gadget with 4 magnetic sensors for the evaluation. The error is <1m in 65% of the cases so it's more precise (but more costly) than WiFi solutions. The main source of errors are moving objects (e.g. elevator).
The next paper is similar but in this case it leverages audio fingerprints: Indoor Localization without Infrastructure using the Acoustic Background Spectrum(S. Tarzia (Northwestern Univ.), P. Dinda (Northwestern Univ.), R. Dick (Univ. of Michigan), G. Memik (Northwestern Univ.)) -NOTE: This app is available in Apple's app store: BatPhone. The benefit of this system is that this does not require specialized hardware and it passively listens to background sounds and after it analyses the spectrum. It doesn't require any infrastructure support. They achieved a 69% accuracy for 33 rooms using sound alone. As many other fingerprint-based localization mechanism, it requires supervised learning techniques. To guess the current location, they find the "closest" fingerprint in a database of labeled fingerprints. In the future work list, they plan to use a Markov movement model to improve the accuracy and also they plan to add other sensors to increase accuracy as in SurroundSense.
Exploiting FM Radio Data System for Adaptive Clock Calibration in Sensor Networks was a quite impressive and neat piece of work. Time synchronization is important for various applications (event ordering, coordination, and there are new wireless interfaces such as Qualcomm's Flashlink that take advantage of a central clock to synchronise devices). In fact, time synchronization is usually based on message passing between devices. They exploit FM radio data system (RDS) for clock calibration. Some of its advantages are its excellent coverage and it's availability all over the world. They implemented their own FM hardware receiver, that was integrated with sensor network platforms on TinyOS. It also solves some of the coverage limitations of GSM networks. Their results show that RDS clock is highly stable and city-wide available and the power consumption is very low (so the cost, 2-3$). The calibration error is also ridiculously low even if the length of the calibration period is in the order of hours. Very neat.
The last presentation was a joint work between Univeristy of Michigan and AT&T Labs: AccuLoc: Practical Localization of Performance Measurements in 3G Networks. Cellular operators need to distinguish the performance of each geographic area in their 3G networks to detect and resolve local network problems. They claim that the “last mile” radio link between 3G base stations and end-user devices is essential for the user experiences. They take advantage of some previous papers that demonstrate that users' mobility is predictable and they exploit this fact to cluster cell sectors that accurately report network performance at the IP level. Those techniques allow them to characterize and identify problems in network performance: clustering cells allows capturing RTT spikes better.
Session 5. Security and Privacy
Caché: Caching Location-Enhanced Content to Improve User Privacy
S. Amini (CMU), J. Lindqvist (CMU), J. Hong (CMU), J. Lin (CMU), E. Toch (Tel Aviv Univ.), N. Sadeh (CMU). The idea is to periodically pre-fetch potentially useful location content so applications can retrieve content from a local cache on the mobile device when it is needed. Location content will be only revealed to third-party providers like "a region" instead of a precise location. Somehow similar to SpotMe.
The second presentation was ProxiMate: Proximity-based Secure Pairing using Ambient Wireless Signals by S. Mathur (AT&T Labs), R. Miller (Rutgers Univ.), A. Varshavsky (AT&T Labs), W. Trappe (Rutgers Univ.), N. Mandayam (Rutgers Univ.). This is about enabling security between devices in wireless environments that do not have a trusted relationship between them based on proximity. It tries to reduce the security issues of low power communications (susceptible to eavesdropping, or even to be sniffed from a mile away as Bluetooth). This takes advantage of code-offsets to generate a common cryptographic key directly from their shared time wireless environment. Quite complex to understand in the presentation. It provides security against computationally unbounded adversary. Complexity is O(n) while Diffie-Hellman is O(n^3).
Security versus Energy Tradeoffs in Host-Based Mobile Malware Detection
J. Bickford (Rutgers Univ.), H. Lagar-Cavilla (AT&T Labs), A. Varshavsky (AT&T Labs), V. Ganapathy (Rutgers Univ), L. Iftode (Rutgers Univ.). This interesting paper explores the security-energy tradeoffs in mobile malware detection. It requires periodically scanning the attack target but it can decrease the battery life two times faster. This work is a energy-optimized version of two security tools. The way it conserves energy is by adapting the frequency of checks and by defining what to check (scan fewer code/data objects). They are trying to provide a high-level security with a low power consumption. They are specially looking a rootkits (sophisticated malware requiring complex detection algorithms). In order to be detected, it's necessary to run the user OS on a hypervisor to check all the kernel data changes. This technique can provide a 100% security but a poor energy efficiency. In order to find the tradeoff, they target what they call the sweet-spot to generate a balanced security. With this technique they can detect 96% of the rootkit attacks.
Analyzing Inter-Application Communication in Android by E. Chin (UC Berkeley), A. Felt (UC Berkeley), K. Greenwood (UC Berkeley), D. Wagner (UC Berkeley). Malicious Apps can take advantage of Android's resources by registering a listener to an specific provider (This abstraction is called Intent in Android). An application can register implicit intents so they not for an specific receiver (i.e. application or service). They described several attacks that can be possible because sending implicit intents in android makes communication public: both the intent and the public receiver can be public for an attacker. Consequently, there are several attacks such as spoofing, man-in-the-middle, etc. A malicious app can also inject fake data to applications or collect information about the system. They evaluated the system called ComDroid with 20 applications. They claim that this can be fixed by either developers or by the platform.
Session 6. Wireless Protocols
This session tries to cover some optimisations for wireless protocols. The first presentation was Avoiding the Rush Hours: WiFi Energy Management via Traffic Isolation by J. Manweiler (Duke Univ.), R. Choudhury (Duke Univ.). This paper measured the power consumption of WiFi interfaces on Nexus One handsets and they found that the WiFi energy cost grows linearly with the number of access points available (dense neighborhoods). This system tries to force APs to collaborate and to coordinate their beacons. This approach only requires changing the APs firmware. Mobile clients can reduce the energy wasted in idle/overhear mode. This system (called SleepWell) forces APs to maintain a map of their neighboring peers (APs) to re-schedule efficiently their beacon timings. However, clients are synchronized to AP clocks. To solve this issue, the AP notifies the client that a beacon is going to be deferred so the client knows when it must wake up. As a result, the client can extend the period of time that it remains in deep sleep mode.
The next paper was Opportunistic Alignment of Advertisement Delivery with Cellular Basestation Overloads, by R. Kokku (NEC Labs), R. Mahindra (NEC Labs), S. Rangarajan (NEC Labs) and H. Zhang (NEC Labs). This paper tries to align cellular base-stations overload with the delivery of advertising content to the clients. The goal is to do not compromise the user-perceived quality of experience while making cellular network operations profitable with advertisements (e.g. embedded in videos). The overload can lead to reduce the available bandwidth per user. Their assumption is that cellular operators can control advertisement delivery, so it's possible to adapt the quality (lower rate) of some advertisements to an specific set of users. Their system called Opal considers two groups of users: regular users that receive their traffic share, and targeted users that receive advertisements during base station overloads. Opal initially maps all users to the regular group and it dynamically decides which users will be migrated between groups based on a long term fairness metric. The system is evaluated on WiMax and with simulations. In the future they're trying to target location-based advertising.
The final presentation was Revisiting Partial Packet Recovery in 802.11 Wireless LANs by J. Xie (Florida State Univ.), W. Hu (Florida State Univ.), Z. Zhang (Florida State Univ.). Packets in WiFi links can be partially received. In order to be recovered, all the packet has to be retransmitted so it has an energy and computational overhead. One solution is based on dividing the packets in smaller blocks so only the missed ones are retransmitted (like keeping a TCP window). Other technique is based on error-correction (e.g. ZipTx). Those techniques can have an important overhead on the CPU and they can be complementary. The novelty of their approach is including Target Error Correction and dynamically selecting the optimal repair method that minimizes the number of bytes sent and the CPU overhead.
.... and now the conference banquet :-)