Related papers: Computationally Aware Sum-Rate Optimal Scheduling …
Centralized radio access network architectures consolidate the baseband operation towards a cloud-based platform, thereby allowing for efficient utilization of computing assets, effective inter-cell coordination, and exploitation of global…
We formulate throughput maximizing, max-min fair, weighted max-min fair, and proportionally fair scheduling problems for cognitive radio networks managed by a centralized cognitive base station. We propose a very general scheduling model…
Recently, Cloud-based Radio Access Network (C-RAN) has been proposed as a potential solution to reduce energy cost in cellular networks. C-RAN centralizes the baseband processing capabilities of Base Stations (BSs) in a cloud computing…
This paper studies cooperative spectrum sensing in cognitive radio networks where secondary users collect local energy statistics and report their findings to a secondary base station, i.e., a fusion center. First, the average error…
This work studies centralized radio resource management in metropolitan area networks with a very large number of access points and user devices. A central controller collects time-averaged traffic and channel conditions from all access…
Centralized Radio Access Network (C-RAN) is a new paradigm for wireless networks that centralizes the signal processing in a computing cloud, allowing commodity computational resources to be pooled. While C-RAN improves utilization and…
In a centralized RAN, the signals from multiple RAPs are processed centrally in a data center. Centralized RAN enables advanced interference coordination strategies while leveraging the elastic provisioning of data processing resources. It…
In a cloud radio access network (C-RAN), distributed remote radio heads (RRHs) are coordinated by baseband units (BBUs) in the cloud. The centralization of signal processing provides flexibility for coordinated multi-point transmission…
The operating system's role in a computer system is to manage the various resources. One of these resources is the Central Processing Unit. It is managed by a component of the operating system called the CPU scheduler. Schedulers are…
In mobile edge computing systems, mobile devices can offload compute-intensive tasks to a nearby cloudlet,so as to save energy and extend battery life. Unlike a fully-fledged cloud, a cloudlet is a small-scale datacenter deployed at a…
In this paper we analyze the problem of optimal task scheduling for data centers. Given the available resources and tasks, we propose a fast distributed iterative algorithm which operates over a large scale network of nodes and allows each…
A centralized wireless system is considered that is serving a fixed set of users with time varying channel capacities. An opportunistic scheduling rule in this context selects a user (or users) to serve based on the current channel state…
In this paper I focused on resource scheduling in the downlink of LTE-Advanced with aggregation of multiple Component Carriers (CCs). When Carrier Aggregation (CA) is applied, a well-designed resource scheduling scheme is essential to the…
Powerful spectrum sensing schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to the primary users. In this paper, maximizing the average throughput of a secondary user by…
Consider a Compute and Forward (CF) relay network with $L$ users and a single relay. The relay tries to decode a linear function of the transmitted signals. For such a network, letting all $L$ users transmit simultaneously, especially when…
In part I of this paper, a distributed and a centralized architecture for an optimal radio resource allocation aware of the traffic delay-tolerance nature, user subscription type, and application usage variations were developed. In the…
The essence of distributed computing systems is how to schedule incoming requests and how to allocate all computing nodes to minimize both time and computation costs. In this paper, we propose a cost-aware optimal scheduling and allocation…
In the rapidly evolving research on artificial intelligence (AI) the demand for fast, computationally efficient, and scalable solutions has increased in recent years. The problem of optimizing the computing resources for distributed machine…
Distributed cloud environments hosting data-intensive applications often experience slowdowns due to network congestion, asymmetric bandwidth, and inter-node data shuffling. These factors are typically not captured by traditional host-level…
Modern-day cars are equipped with numerous cameras and sensors, typically integrated with advanced decision-control systems that enable the vehicle to perceive its surroundings and navigate autonomously. Efficient processing of data from…