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Passive optical networks are the most promising solution for access networks. Nowadays, Gigabit passive optical networks are very popular for Internet services providers. These networks have currently been limited by transmission speeds (up to 2.5 Gbit/s in downstream) which is not sufficient for all services (such as 4k video transfer etc.) because this speed is shared with all users in the network...
For task completion in distributed environments, a set of resources is required and a group of agents must cooperate in deciding the share each should provide to maximize the system performance. We address the problem from an evolutionary game-theoretic perspective and present a fully distributed algorithm based on local replicator dynamics. By using the optimality condition, we prove the convergence...
The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of interest, especially in large scale settings with hundreds of nodes and thousands of flows. In this context,...
Massive multiple input multiple output (MIMO) technology plays an important role in next generation wireless communication systems. Modified Brent-Luk-Van Loan array and other parallel hardware implementations were developed for channel matrix factorization. For a large matrix size as of massive MIMO, however, previous implementations would require a large amount of hardware resource. This paper presents...
Motivated by broad applications in various fields of engineering, we study network resource allocation problems where the goal is to optimally allocate a fixed portion of resources over a network of nodes. In these problems, due to the large scale of the network and complicated interconnections between nodes, any solution must be implemented in parallel and based only on local data resulting in a...
This paper focuses on the resource allocation problem with equality and inequality constraints in a fixed weight-balanced directed or undirected network. Moreover, we propose a fully decentralized subgradient algorithm with event-triggered for solving above resource allocation problem based on first-order discrete-time multi-agent systems. Where each agent only communicates with its neighbors and...
This paper investigates distributed resource allocation in next-generation underlay Device-to-Device (D2D) networks. The joint channel and power allocation for a D2D network underlaying a cellular network is formulated as a non-cooperative game. A utility-based learning algorithm which does not require information exchange between device pairs is proposed to determine the channel index and power level...
Latent Dirichlet Allocation has been developed as topic-based method which uses reasoning to determine the topics of a document. There are many methods of reasoning used for Latent Dirichlet Allocation, including the Gibbs Sampling and Mean Variational Inference, the most widely used in research. However, there have not been many studies that discuss the implementation of these methods on the Indonesian...
Integration of the distributed energy resources in power distribution network has emerged as a significant method to optimize the operation and planning of the power distribution network. The optimal distributed generation placement comprises of obtaining the optimal size and location of the DGs to be placed. Various methods and techniques have been used to obtain the best possible results for optimal...
We study the resource allocation problem in RAN-level integrated HetNets. This emerging HetNets paradigm allows for dynamic traffic splitting across radio access technologies for each client, and then for aggregating the traffic inside the network to improve the overall resource utilization. We focus on the max-min fair service rate allocation across the clients, and study the properties of the optimal...
Efficiently of spectrum allocation is the key for dynamic spectrum access in the Cognitive Radio Network (CRNs). Based on graph coloring model, this paper proposes a random drift particle swarm optimization (RDPSO) algorithm to allocate the spectrum, with the purpose of improving the reward and fairness of network. The RDPSO algorithm introduces the thermal coefficient and drift coefficient, and it...
In small-cell wireless networks where users are connected to multiple base stations (BSs), it is often advantageous to opportunistically switch off a subset of BSs to minimize energy costs. We consider two types of energy cost: (i) the cost of maintaining a BS in the active state, and (ii) the cost of switching a BS from the active state to inactive state. The problem is to operate the network at...
The paper relates to multi-resource sharing between flows with heterogeneous requirements as arises in networks with wireless links or software routers implementing network function virtualization. Bottleneck max fairness (BMF) is a sharing objective in this context with good performance. The paper shows that BMF results when local fairness is imposed at each resource while flow rates are controlled...
The concatenation of the multiple-input multiple-output (MIMO) linear precoder with an outer forward error correction (FEC) code at the transmitter is investigated in this paper. At the receiver side, the turbo detection is taken into account. It iteratively exchanges the extrinsic information between a soft-demapper and a FEC soft-decoder. We firstly propose a new precoder named FI1 designed from...
We study the multi-user and multi-carrier power allocation (spectrum balancing) problem in digital subscriber line (DSL) networks under inter-carrier and inter-user interference as well as self-interference. The key assumption of this work is that we do not have knowledge of the interference coefficients, but only have access to the total per-line interference noise power. Furthermore, lines may support...
This paper studies distributed solutions for an optimal resource allocation problem over networked systems with connected graph communication topologies. The problem setting consists of a group of agents in a network cooperatively meeting a demand by supplying a resource whose commitment incurs a cost on them. The objective in the optimal resource allocation problem is to obtain a commitment value...
Many proposed network resource allocation algorithms in existing literature, especially those in practical networking, are designed based on heuristics and then validated by (limited) prototyping and experimentation or numerical simulations. These algorithms usually perform poorly in either responsiveness or convergence, and lack a principled way to trade off between the convergence and the optimality...
This paper proposes an individual representation for optimizing allocation of static var compensators (SVCs). Generally, the individuals indicate the capacities of the devices in the optimal allocation of SVCs. In the proposed representation, capacities and installation places of SVCs are expressed in separate variables. The effectiveness of the proposed representation is verified by computer simulation...
Energy trading is a key feature of the emerging smart grid system. In this paper, we propose an energy allocation mechanism for energy trading among competing consumers and prosumers, i.e. agents, in a microgrid. The proposed mechanism is modeled for rational agents with hidden private information, aiming to optimize self-utility and payoff. We achieve this goal through the presence of a central impartial...
Cognitive radio networks will play an important role in the future wireless networks. In this paper, an improved ant colony optimization algorithm is proposed to increase the spectrum utilization. In the algorithm, not only the individual benefit but also overall benefit of system are considered, and the attenuation coefficient of the historical pheromone is updated dynamically. It accelerates the...
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