Is it fair? Resource allocation for differentiated services on demands
With the rapid growth of service requirements, the rising concern of resource allocation
fairness (eg, the actual gained Quality of Service (QoS)) leads to the popularity of studies for …
fairness (eg, the actual gained Quality of Service (QoS)) leads to the popularity of studies for …
On-Demand Centralized Resource Allocation for IoT Applications: AI-Enabled Benchmark
The development of emerging information technologies, such as the Internet of Things (IoT),
edge computing, and blockchain, has triggered a significant increase in IoT application …
edge computing, and blockchain, has triggered a significant increase in IoT application …
Multi-resource generalized processor sharing for packet processing
Middleboxes have found widespread adoption in today's networks. They perform a variety of
network functions such as WAN optimization, intrusion detection, and network-level firewalls …
network functions such as WAN optimization, intrusion detection, and network-level firewalls …
Performance Evaluation of Self-similar GPS Scheduling: A Knowledge-Driven Dual-Task Deep Learning Approach
Generalized Processor Sharing (GPS) under self-similar traffic is widely used for guiding
resource allocation in modern communication networks where performance evaluation, ie …
resource allocation in modern communication networks where performance evaluation, ie …
Fass: A fairness-aware approach for concurrent service selection with constraints
The increasing momentum of service-oriented architecture has led to the emergence of
divergent delivered services, where service selection is meritedly required to obtain the …
divergent delivered services, where service selection is meritedly required to obtain the …
Beyond processor sharing
While the (Egalitarian) Processor-Sharing (PS) discipline offers crucial insights in the
performance of fair resource allocation mechanisms, it is inherently limited in analyzing and …
performance of fair resource allocation mechanisms, it is inherently limited in analyzing and …
DeepQSC: A GNN and attention mechanism-based framework for QoS-aware service composition
X Ren, W Zhang, L Bao, J Song, S Wang… - … on Service Science …, 2021 - ieeexplore.ieee.org
When several Web services with simple functions need to be combined to provide more
complex functions, how to choose from a large number of Web services with the same …
complex functions, how to choose from a large number of Web services with the same …
QoS-aware diversified service selection
C Guo, W Zhang, N Dong, Z Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In QoS-aware service selection, merely considering the prediction accuracy of QoS is prone
to redundant results, which hinders practical service composition and also undermines …
to redundant results, which hinders practical service composition and also undermines …
CTL-based adaptive service composition in edge networks
With the recent adoption of edge computing, I nternet of T hings (IoT) devices collaborate at
the network edge to facilitate edge-native applications. In this setting, IoT devices are …
the network edge to facilitate edge-native applications. In this setting, IoT devices are …
Deep reinforcement learning for QoS-constrained resource allocation in multiservice networks
In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-
convex optimization problem whose main aim is to maximize the spectral efficiency subject …
convex optimization problem whose main aim is to maximize the spectral efficiency subject …