Related papers: Optimal Control Selection over the Edge-Cloud Cont…
This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies…
Widespread use of computer networks and the use of varied technology for the interconnection of computers has made congestion a significant problem. In this report, we summarize our research on congestion avoidance. We compare the concept…
IoT edge computing positions computing resources closer to the data sources to reduce the latency, relieve the bandwidth pressure on the cloud, and enhance data security. Nevertheless, data security in IoT edge computing still faces…
A vast and growing number of IoT applications connect physical devices, such as scientific instruments, technical equipment, machines, and cameras, across heterogenous infrastructure from the edge to the cloud to provide responsive,…
We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the problem by applying a…
The advent of Edge Computing (EC) as a promising paradigm that provides multiple computation and analytics capabilities close to data sources opens new pathways for novel applications. Nonetheless, the limited computational capabilities of…
We consider the problem of designing a packet-level congestion control and scheduling policy for datacenter networks. Current datacenter networks primarily inherit the principles that went into the design of Internet, where congestion…
In recent years, the need for resources for handling processes with high computational complexity for mobile robots is becoming increasingly urgent. More specifically, robots need to autonomously operate in a robust and continuous manner,…
Edge computing has evolved to be a promising avenue to enhance the system computing capability by offloading processing tasks from the cloud to edge devices. In this paper, we propose a multi-layer edge computing framework called EdgeFlow.…
The allocation of computing tasks for networked distributed services poses a question to service providers on whether centralized allocation management be worth its cost. Existing analytical models were conceived for users accessing…
With the mass deployment of computing-intensive applications and delay-sensitive applications on end devices, only adequate computing resources can meet differentiated services' delay requirements. By offloading tasks to cloud servers or…
We consider a controlled double-ended queue consisting of two classes of customers, labeled sellers and buyers. The sellers and buyers arrive in a trading market according to two independent renewal processes. Whenever there is a seller and…
Distributed optimization finds applications in large-scale machine learning, data processing and classification over multi-agent networks. In real-world scenarios, the communication network of agents may encounter latency that may affect…
This paper presents a distributed resource selection mechanism for diverse cloud-edge environments, enabling dynamic and context-aware allocation of resources to meet the demands of complex distributed applications. By distributing the…
The ever-increasing growth in the number of connected smart devices and various Internet of Things (IoT) verticals is leading to a crucial challenge of handling massive amount of raw data generated from distributed IoT systems and providing…
Distributed optimization algorithms are used in a wide variety of problems involving complex network systems where the goal is for a set of agents in the network to solve a network-wide optimization problem via distributed update rules. In…
Low-Latency IoT applications such as autonomous vehicles, augmented/virtual reality devices and security applications require high computation resources to make decisions on the fly. However, these kinds of applications cannot tolerate…
Cloud Computing is the delivery of computing resources which includes servers, storage, databases, networking, software, analytics, and intelligence over the internet to offer faster innovation, flexible resources, and economies of scale.…
The edge-cloud continuum has emerged as a transformative paradigm that meets the growing demand for low-latency, scalable, end-to-end service delivery by integrating decentralized edge resources with centralized cloud infrastructures.…
Virtualisation first and cloud computing later has led to a consolidation of workload in data centres that also comprises latency-sensitive application domains such as High Performance Computing and telecommunication. These types of…