DiversiFi: Robust Multi-Link Interactive Streaming

ABSTRACT Real-time, interactive streaming for applications such as audio-video conferencing (e.g., Skype) and cloud-based gaming depends critically on the network providing low latency, jitter, and packet loss, much more so than on-demand streaming (e.g., YouTube) does. However, WiFi networks pose a challenge; our analysis of data from a large VoIP provider and from our own measurements shows that the WiFi access link is a significant cause of poor streaming experience. To improve streaming quality over WiFi, we present DiversiFi, which takes advantage of the diversity of WiFi links available in the vicinity, even when the individual links are poor. Leveraging such cross-link spatial and channel diversity outperforms both traditional link selection and the temporal diversity arising from retransmissions on the same link. It also provides significant gains over and above the PHY-layer spatial diversity provided by MIMO. Our experimental evaluation shows that, for a client with two NICs, enabling replication across two WiFi links helps cut down the poor call rate (PCR) for VoIP by 2.24x. Finally, we present the design and implementation of DiversiFi, which enables it to operate with single-NIC clients, and with either minimally modified APs or unmodified APs augmented with a middlebox. Over 61 runs, where the baseline average PCR is 4.9%, DiversiFi running with a single NIC, switching between two links, helps cut the PCR down to 0%, while duplicating wastefully only 0.62% of the packets and impacting competing TCP throughput by only 2.5%. Thus, DiversiFi provides the benefit of multi-link diversity for real-time interactive streaming in a manner that is deployable and imposes little overhead, thereby ensuring coexistence with other applications

Reducing Performance Overhead of Direct Access NVM Storage Redundancy

Non-volatile memory (NVM) based storage is poised for mainstream deployment. DIMM form-factor NVM devices reside on the memory bus and offer DRAM-like access granularities and latencies along with non-volatility. NVM'sDirect Access (DAX) interface enables applications to map persistent data into their address space and access it with load and store instructions, eliminating system software overheads. Production deployment of DAX NVM storage would require that the storage system offer resilience against firmware-bug-induced data corruption, akin toconventional storage systems. Protection against firmware-bug-induced data corruptions requires the storage system to maintain system-level redundancy, which we refer to as system-redundancy. With DAX interfacing, the lack ofinterposed system software makes it challenging to identify data reads and writes that should trigger system-redundancy verification and updates, respectively. Further, the DAX granularities (e.g., 64-byte cache-lines) are incongruentwith typical system-redundancy granularities (e.g., 4K pages), leading to high performance overhead in maintaining system-redundancy. This dissertation demonstrates that DAX NVM storage systems can efficiently maintain system-redundancy by relaxing the data coverage guarantees or by leveraging a hardware offload. We support the thesis with two case studies: Vilamb and Tvarak. The Vilamb library maintains system-redundancy synchronously,avoiding critical path interpositioning and amortizes the overhead of system-redundancy updates across multiple writes to a page. As a result, Vilamb provides 3-5x the throughput of the state-of-the-art software solutionat high operation rates. For applications that need system-redundancy with high performance, and can tolerate some delaying of data redundancy, Vilamb provides a tunable knob between performance and time-to-coverage. Evenwith the delayed coverage, Vilamb increases the mean time to data loss due to firmware-induced corruptions by up to two orders of magnitude in comparison to maintaining no system-redundancy. Tvarak is a software-managed hardware offload to efficiently maintain system redundancyfor direct-access (DAX) NVM storage. Tvarak reconciles the mismatch between DAX granularities and typical system-redundancy granularities by introducing cache-line granular checksums (only) for DAX-mapped data. Tvarak also uses caching to reduce the number of extra NVM accesses formaintaining and verifying system-redundancy. Applications' data access locality leads to reuse of system-redundancy that Tvarak leverages with a small dedicated on-controller cache and configurable LLC partitions. Simulation-based evaluation demonstrates Tvarak's efficiency. For example, Tvarak reduces Redis set-only performance by only 3%.</div

Club-convergence and polarization of states: A nonparametric analysis of post-reform India

Purpose – The purpose of this paper is to study the dynamics of the distribution of per capita income of Indian states in the post-reform period, in order to identify trends towards convergence-club formation, polarization or stratification during this period. Design/methodology/approach – The authors adopt the “distribution dynamics” framework that involves estimating kernel density functions, stochastic kernels and ergodic distributions in order to identify these trends. Findings – The results show that there is polarization in India in the post-reform period and this is due to the contrary growth dynamics of the middle-income states resulting in the “vanishing middle” of the distribution. Originality/value – This is the first study that highlights the contrary growth dynamics among the middle-income states as the driving force behind the polarization of Indian states in the post-reform period.Distribution of wealth, India, National economy