Mobile applications rely on persistent connections for push notifications, but network middleboxes silently drop idle connections to reclaim resources. To keep these connections alive, clients transmit periodic heartbeats, which in turn trigger frequent radio wake-ups and drain battery. To address the problem, we present Strand, a server-driven zero-wakeup keep-alive architecture that crafts server-side heartbeats with a precisely calibrated Time-To-Live. These packets intentionally “strand” (expire) at the final middlebox, successfully refreshing the mapping state without traversing the energy-expensive last-hop wireless link, keeping the mobile radio completely asleep. Furthermore, to minimize probing overhead, Strand employs a cost-aware weighted Dynamic Programming (DP) algorithm that incorporates timeout distribution priors to find search boundaries and overcome the severe temporal latency penalties of the traditional exponential approach. Real-world experiments show that Strand reduces active push energy overhead by ∼ 40%. Additionally, our weighted DP-based probing algorithm accelerates timeout convergence by ∼ 28% for TCP and ∼ 26% for UDP over state-of-the-art baselines.

SparkLink Low Energy (SLE) is a new short-range wireless communication technology designed to satisfy the increasing demands of future short-range scenarios. While SLE promises fundamental improvements over traditional Bluetooth, a thorough real-world evaluation is lacking. This article provides a detailed evaluation framework that includes access layer benchmarking and end-to-end application validation, presenting the first comprehensive comparison between SLE and traditional Bluetooth technologies. Benchmarking reveals SLE offers a 4× increase in data rate, a 3.84× reduction in latency, and a 10 dB improvement in sensitivity. To evaluate SLE against actual application QoS requirements, we implement an end-to-end evaluation system for validation across three practical application scenarios. Based on experimentation and parameter analysis, we propose a design for QoS-centered optimization. These results underscore SLE’s fundamental advancements over Bluetooth and its potential in real-world applications, offering insights for further optimization of this communication technology.

WiFi networks, widely utilized by wireless devices, have become increasingly complex and congested environments, leading to noticeable delays, jitter, and throughput degradation for end-to-end network flows in today’s Internet. Through detailed experimental observations, we identified the TCP victim problem in WiFi, where TCP erroneously detects congestion and interacts with WiFi routers, resulting in a significant throughput decrease for certain hosts. In this paper, we introduce Cupid, a novel congestion control algorithm that relies on receiver-side WiFi physical layer measurements. Cupid accurately assesses congestion by measuring parameters such as airtime utilization, concurrency, and rates, allowing for precise rate adjustments. Our results demonstrate that whether employed alone or alongside other congestion controls, Cupid effectively mitigates the TCP victim problem. Furthermore, when used independently, Cupid can also reduce latency.

TCP was designed to provide stream-oriented communication service for bulk data transfer applications (e.g., FTP and Email). With four-decade development, Internet applications have undergone significant changes, which now involve highly dynamic traffic pattern and message-oriented communication paradigm. However, the impact of this substantial evolution on congestion control (CC) has not been fully studied. Most of the network transports today still make the long-held assumption about application traffic, i.e., a byte stream with an unlimited data arrival rate.

Polling and interrupt has long been a trade-off in RDMA systems. Polling has lower latency but each CPU core can only run one thread. Interrupt enables time sharing among multiple threads but has higher latency. Many applications such as databases have hundreds of threads, which is much larger than the number of cores. So, they have to use interrupt mode to share cores among threads, and the resulting RDMA latency is much higher than the hardware limits. In this paper, we analyze the root cause of high costs in RDMA interrupt delivery, and present FastWake, a practical redesign of interrupt-mode RDMA host network stack using commodity RDMA hardware, Linux OS, and unmodified applications. Our first approach to fast thread wake-up completely removes interrupts. We design a per-core dispatcher thread to poll all the completion queues of the application threads on the same core, and utilize a kernel fast path to context switch to the thread with an incoming completion event. The approach above would keep CPUs running at 100% utilization, so we design an interrupt-based approach for scenarios with power constraints. Observing that waking up a thread on the same core as the interrupt is much faster than threads on other cores, we dynamically adjust RDMA event queue mappings to improve interrupt core affinity. In addition, we revisit the kernel path of thread wake-up, and remove the overheads in virtual file system (VFS), locking, and process scheduling. Experiments show that FastWake can reduce RDMA latency by 80% on x86 and 77% on ARM at the cost of < 30% higher power utilization than traditional interrupts, and the latency is only 0.3 ∼ 0.4 μ s higher than the limits of underlying hardware. When power saving is desired, our interrupt-based approach can still reduce interrupt-mode RDMA latency by 59% on x86 and 52% on ARM.