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We present a unified analytical framework within which power control, rate allocation, routing, and congestion control for wireless networks can be optimized in a coherent and integrated manner. We consider a multi-commodity flow model with…
Asynchronous learning protocols have regained attention lately, especially in the Federated Learning (FL) setup, where slower clients can severely impede the learning process. Herein, we propose \texttt{AsyncDrop}, a novel asynchronous FL…
With more devices connected, delays and jitter at the WiFi hop become more prevalent, and correct functioning during network congestion becomes more important. However, two important performance issues prevent modern WiFi from reaching its…
A well-known technique for enhancing the performance and stability of content distribution is the use of multiple dissemination flows. Multipath TCP (MPTCP), the most popular multiflow protocol on the Internet, allows receivers to exploit…
The growing complexity of network traffic and demand for ultra-low latency communication require smarter packet traffic management. Existing Deep Learning-based queuing approaches struggle with dynamic network scenarios and demand high…
Currently, TCP is the most popular and widely used network transmission protocol. In actual fact, about 90% of connections on the internet use TCP to communicate. Through several upgrades and improvements, TCP became well optimized for the…
Active Queue Management (AQM) for mitigating Internet congestion has been addressed via various feedback control syntheses, among which P, PI, and PID regulators are quite popular and often associated to a Smith predictor. Here, to better…
In queueing networks, it is well known that the throughput-optimal backpressure routing algorithm results in poor delay performance for light and moderate traffic loads. To improve delay performance, state-of-the-art backpressure routing…
A new era in wireless sensor network technology has been ushered in through the introduction of multimedia sensor networks, which has a major bottleneck in the form of network congestion. Congestion occurs when resources are in high demand…
We consider the load-balancing design for forwarding incoming flows to access points (APs) in high-density wireless networks with both channel fading and flow-level dynamics, where each incoming flow has a certain amount of service demand…
Existing transport protocols, be it TCP, SCTP or DCCP, do not provide an efficient congestion control mechanism for heterogeneous wired-cum-wireless networks. Solutions involving implicit loss discrimination schemes have been proposed but…
Although federated learning has achieved many breakthroughs recently, the heterogeneous nature of the learning environment greatly limits its performance and hinders its real-world applications. The heterogeneous data, time-varying wireless…
Learning from multiple data streams in real-world scenarios is fundamentally challenging due to intrinsic heterogeneity and unpredictable concept drifts. Existing methods typically assume homogeneous streams and employ static architectures…
The basic idea behind an active queue management (AQM) is to sense the congestion level within the network and inform the packet sources about, so that they reduce their sending rate. In literature a lot off mechanisms of AQM are studied.…
In recent years, research efforts tried to exploit peer-to-peer (P2P) systems in order to provide Live Streaming (LS) and Video-on-Demand (VoD) services. Most of these research efforts focus on the development of distributed P2P block…
LTE/WiFi Aggregation (LWA) provides a promising approach to relieve data traffic congestion in licensed bands by leveraging unlicensed bands. Critical challenges arise from provisioning quality-of-service (QoS) through heterogenous…
In this paper, we reveal the relationship between entropy rate and the congestion in complex network and solve it analytically for special cases. Finding maximizing entropy rate will lead to an improvement of traffic efficiency, we propose…
Communication scheduling aims to reduce communication bottlenecks in data parallel training (DP) by maximizing the overlap between computation and communication. However, existing schemes fall short due to three main issues: (1) hard data…
There is an obvious trend that more and more data and computation are migrating into networks nowadays. Combining mature virtualization technologies with service-centric net- working, we are entering into an era where countless services…
As future networks aim to meet the ever-increasing requirements of high data rate applications, dense and heterogeneous networks (HetNets) will be deployed to provide better coverage and throughput. Besides the important implications for…