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Fast, reliable, and efficient data transmission across wide-area networks is a predominant bottleneck for data-intensive cloud applications. This paper introduces OneDataShare, which is designed to eliminate the issues plaguing effective…
After Amdahl's trailblazing work, many other authors proposed analytical speedup models but none have considered the limiting effect of the memory wall. These models exploited aspects such as problem-size variation, memory size,…
A VLAN is a logical connection that allows hosts to be grouped together in the same broadcast domain, so that packets are delivered only to ports that are combined to the same VLAN. We can improve wireless network performance and save…
In the past decade, blockchain has emerged as a promising solution for building secure distributed ledgers and has attracted significant attention. However, current blockchain systems suffer from limited throughput, poor scalability, and…
Fog computing has been advocated as an enabling technology for computationally intensive services in smart connected vehicles. Most existing works focus on analyzing the queueing and workload processing latencies associated with fog…
Switching, routing, and security functions are the backbone of packet processing networks. Fast and efficient processing of packets requires maintaining the state of a large number of transient network connections. In particular, modern…
Ad-hoc routing protocols use a number of algorithms for route discovery. Some use flooding in which a route request packet (RREQ) is broadcasted from a source node to other nodes in the network. This often leads to unnecessary…
Airborne platforms, such as drones, balloons, and aerostats, have recently gained considerable interest in the communication sector. Free-space optical communication (FSOC) systems can deliver information wirelessly at high data rates…
Powerful abstractions such as dataframes are only as efficient as their underlying runtime system. The de-facto distributed data processing framework, Apache Spark, is poorly suited for the modern cloud-based data-science workloads due to…
The design of transport protocols, embedded in end-systems, and the choice of buffer sizing strategies, within network routers, play an important role in performance analysis of the Internet. In this paper, we take a dynamical systems…
Distance Comparison Operations (DCOs), which decide whether the distance between a data vector and a query is within a threshold, are a critical performance bottleneck in vector similarity search. Recent DCO methods that avoid…
Large-scale graph processing has drawn great attention in recent years. Most of the modern-day datacenter workloads can be represented in the form of Graph Processing such as MapReduce etc. Consequently, a lot of designs for Domain-Specific…
Apache Hadoop and Spark are gaining prominence in Big Data processing and analytics. Both of them are widely deployed on Internet companies. On the other hand, high-performance data analysis requirements are causing academical and…
For wireless systems in which randomly arriving devices attempt to transmit a fixed payload to a central receiver, we develop a framework to characterize the system throughput as a function of arrival rate and per-user data rate. The…
We present a novel access protocol for crowd scenarios in massive MIMO (Multiple-input multiple-output) systems. Crowd scenarios are characterized by a large number of users with intermittent access behavior, whereby orthogonal scheduling…
The Internet of Things (IoT) bridges the gap between the physical and digital worlds, enabling seamless interaction with real-world objects via the Internet. However, IoT systems face significant challenges in ensuring efficient data…
Data analytic applications built upon big data processing frameworks such as Apache Spark are an important class of applications. Many of these applications are not latency-sensitive and thus can run as batch jobs in data centers. By…
Distributed dataflow systems such as Apache Spark or Apache Flink enable parallel, in-memory data processing on large clusters of commodity hardware. Consequently, the appropriate amount of memory to allocate to the cluster is a crucial…
Resource management is one of the most indispensable components of cluster-level infrastructure layers. Users of such systems should be able to specify their job requirements as a configuration parameter (CPU, RAM, disk I/O, network I/O)…
We present MeanCache, a training-free caching framework for efficient Flow Matching inference. Existing caching methods reduce redundant computation but typically rely on instantaneous velocity information (e.g., feature caching), which…