Seyed Kaveh Fayaz

Trace-Driven Analysis of ICN Caching Algorithms on Video-on-Demand Workloads

Even though a key driver for Information-Centric Networking (ICN) has been the rise in Internet video traffic, there has been surprisingly little work on analyzing the interplay between ICN and video ? which ICN caching strategies work well on video work- loads and how ICN helps improve video-centric quality of experience (QoE). In this work, we bridge this disconnect with a trace- driven study using 196M video requests from over 16M users on a country-wide topology with 80K routers. We evaluate a broad space of content replacement (e.g., LRU, LFU, FIFO) and content placement (e.g., leave a copy everywhere, probabilistic) strategies over a range of cache sizes. We highlight four key findings: (1) the best placement and re- placement strategies depend on the cache size and vary across improvement metrics; that said, LFU+probabilistic caching [37] is a close-to-optimal strategy overall; (2) video workloads show considerable caching-related benefits (e.g., -- 10% traffic reduction) only with very large cache sizes (≥ 100GB); (3) the improvement in video QoE is low (≥ 12%) if the content provider already has a substantial geographical presence; and (4) caches in the middle and the edge of the network, requests from highly populated regions and without content servers, and requests for popular content contribute most to the overall ICN-induced improvements in video QoE.

Testing stateful and dynamic data planes with FlowTest

Many recent efforts have leveraged Software-Defined Networking (SDN capabilities to enable new and more efficient ways of testing the correctness of a networks forwarding behaviors. However, realistic network settings induce two additional sources of complexity that fall outside the scope of existing SDN testing frameworks: (1) complex nature of real-world data planes (e.g., stateful firewalls, dynamic behaviors of proxy caches), and (2) complexity of intended network policies (e.g., service chaining). In this paper, we outline FlowTest, a high-level vision for testing such stateful and dynamic network policies. FlowTest systematically explores the state space of the network data plane to verify its behavior w.r.t. policy goals. We show the early promise of our approach and discuss open challenges in realizing this vision in practice.

Ez-Channel

There is a significant interest in new wireless multiple access protocols that adaptively split a wide frequency channel into multiple sub-channels-perhaps of varying widths-and assign these sub-channels to competing transmissions. Existing protocols suffer from various limitations such as considerable protocol overhead, dependence on a centralized controller, and use of fixed-size channels. We introduce Ez-Channel, a novel MAC protocol that parsimoniously utilizes the OFDM sub-carriers to perform channelization and assignment of sub-channels to competing links. In addition to circumventing hidden and exposed terminal problems, Ez-Channel adapts channel assignments to the network topology. To eliminate the need for a centralized controller and to avoid an overwhelming amount of information exchange, the protocol uses a randomization technique enabling provably efficient localized decision making. Our extensive analytical and simulation studies show that Ez-Channel yields significant throughput improvements as compared to the state-of-the-art protocols.

SNIPS: A software-defined approach for scaling intrusion prevention systems via offloading

Growing traffic volumes and the increasing complexity of attacks pose a constant scaling challenge for network intrusion prevention systems (NIPS). In this respect, offloading NIPS processing to compute clusters offers an immediately deployable alternative to expensive hardware upgrades. In practice, however, NIPS offloading is challenging on three fronts in contrast to passive network security functions: (1) NIPS offloading can impact other traffic engineering objectives; (2) NIPS offloading impacts user perceived latency; and (3) NIPS actively change traffic volumes by dropping unwanted traffic. To address these challenges, we present the SNIPS system. We design a formal optimization framework that captures tradeoffs across scalability, network load, and latency. We provide a practical implementation using recent advances in software-defined networking without requiring modifications to NIPS hardware. Our evaluations on realistic topologies show that SNIPS can reduce the maximum load by up to 10× while only increasing the latency by 2%.