This thesis investigates the effective scheduling of TCP stacks alongside applications on multicore architectures, focusing on the trade-offs in allocating workers for both TCP and application processing. It explores the interplay between stateful network protocols with strong guarantees and the challenges of scheduling such protocols alongside multicore applications. To allow fair comparisons, we design and implement Demieagle, a benchmark framework that allows the execution of “apples-to-apples” experiments to uncover the trade-offs of different multicore scheduling policies and architectures. We also address the complexity of scaling stateful network functions, which require per-packet state updates. During a scaling operation, workers need to synchronize access to a shared state to avoid race conditions and to guarantee that network functions process packets in arrival order. Unfortunately, the classic approach to control concurrent access to a shared state with locks does not scale to today's throughput and latency requirements. To address these challenges, we design, implement, and evaluate Dyssect, a system that enables dynamic scaling of stateful network functions by disaggregating their states. Dyssect's state disaggregation allows the offloading of stateful network functions to programmable NICs and makes it easier to explore hardware-software trade-offs that better suit specific network functions and traffic loads. Our experimental evaluation shows that Dyssect reduces tail latency up to 32.04% and increases throughput up to 19.36% compared to state-of-the-art competing solutions.

Network Function Virtualization promises better utilization of computational resources by dynamically scaling resources on demand. However, most network functions (NFs) are stateful and require state updates on a per-packet basis. During a scaling operation, cores need to synchronize access to a shared state to avoid race conditions and to guarantee that NFs process packets in arrival order. Unfortunately, the classic approach to control concurrent access to a shared state with locks does not scale to today’s throughput and latency requirements. Moreover, network traffic is highly skewed, leading to load imbalances in systems that use only sharding to partition the NF states. To address these challenges, we present Dyssect, a system that enables dynamic scaling of stateful NFs by disaggregating the states of network functions. By carefully coordinating actions between cores and a central controller, Dyssect migrates shards and flows between cores for load balancing or traffic prioritization without resorting to locks or reordering packets. Also, Dyssect’s state disaggregation allows the offloading of stateful network functions to programmable NICs and makes it easier for exploring hardware-software tradeoffs that better suit specific service chains and traffic loads. Our experimental evaluation shows that Dyssect reduces tail latency up to 32.04% and increases throughput up to 19.36% when compared to state-of-the-art competing solutions.

This paper presents a P4 implementation of the (1-D) Discrete Wavelet Transform (DWT) method. As a mathe-matical tool for analyzing signals such as packet-level traces, the DWT divides a given signal into different frequency components and analyzes each component with a resolution matched to its scale. We develop an efficient online algorithm that circumvents various limitations of existing P4-programmable data plane devices and performs the DWT decomposition entirely in the data plane. Our evaluation of a hardware implementation (i.e., Netronome NFP-4000 SmartNIC) of the algorithm shows that it results in only minimal throughput overhead (less than 1% for average-sized packets) and operates within constraints imposed by the limited available data plane resources. As an application, we use our lightweight P4 implementation of the DWT and describe a novel threshold-based approach for detecting periodic behavior in a signal in real-time, at line rate in the data plane (40 Gbps). We illustrate our approach with different examples of synthetic and real-world packet-level traffic traces that exhibit periodic patterns of either benign or malicious origins.

Network Function Virtualization promises better utilization of computational resources by dynamically scaling resources on demand. However, most network functions (NFs) are stateful and require state updates on a per-packet basis. During a scaling operation, cores need to synchronize access to a shared state to avoid race conditions and to guarantee that NFs process packets in arrival order. Unfortunately, the classic approach to control concurrent access to a shared state with locks does not scale to today’s throughput and latency requirements. Moreover, network traffic is highly skewed, leading to load imbalances in systems that use only sharding to partition the NF states. To address these challenges, we present Dyssect, a system that enables dynamic scaling of stateful NFs by disaggregating the states of network functions. By carefully coordinating actions between cores and a central controller, Dyssect migrates shards and flows between cores for load balancing or traffic prioritization without resorting to locks or reordering packets. Our experimental evaluation shows that Dyssect reduces tail latency up to 32% and increases throughput up to 19.36% when compared to state-of-the-art competing solutions.

Middleboxes are crucial for improving network security and performance, but only if the right traffic goes through the right middleboxes at the right time. Existing traffic-steering techniques rely on a central controller to install fine-grained forwarding rules in network elements-at the expense of a large number of rules, a central point of failure, challenges in ensuring all packets of a session traverse the same middleboxes, and difficulties with middleboxes that modify the “five tuple.” We argue that a session-level protocol is a fundamentally better approach to traffic steering, while naturally supporting host mobility and multihoming in an integrated fashion. In addition, a session-level protocol can enable new capabilities like dynamic service chaining, where the sequence of middleboxes can change during the life of a session, e.g., to remove a load-balancer that is no longer needed, replace a middlebox undergoing maintenance, or add a packet scrubber when traffic looks suspicious. Our Dysco protocol steers the packets of a TCP session through a service chain, and can dynamically reconfigure the chain for an ongoing session. Dysco requires no changes to end-host and middlebox applications, host TCP stacks, or IP routing. Dysco's distributed reconfiguration protocol handles the removal of proxies that terminate TCP connections, middleboxes that change the size of a byte stream, and concurrent requests to reconfigure different parts of a chain. Through formal verification using Spin and experiments with our prototype, we show that Dysco is provably correct, highly scalable, and able to reconfigure service chains across a range of middleboxes.