Raciocínio Baseado em Casos para a Configuração de Modelos de Alocação de Banda

The extensive adoption of computer networks, especially the Internet, using services that require extensive data flows, has generated a growing demand for computational resources, mainly bandwidth. Bandwidth Allocation Models (BAM) have proven to be a viable alternative to network management where the bandwidth resource is shared to meet the high demand for the network. However, managing these networks has become an increasingly complex task, and solutions that allow for nearly autonomous configuration with less intervention of the network manager are highly demanded. The use of Case-Based Reasoning (CBR) techniques for network management has proven satisfactory for decision making and network management. This work presents a proposal for network reconfiguration based on the CBR cycle, intelligence, and cognitive module for MPLS (Multi-Protocol Label Switching) networks. The results show that CBR is a feasible solution for auto-configuration with autonomic characteristics in the MPLS using bandwidth allocation models (BAMs). The proposal improved the general network performance.

Advanced Optimization Models For Bandwidth Provisioning And Routing In Fixed Microwave Backhaul Networks

This paper addresses the problem of determining bandwidth allocation and traffic routes in fixed microwave networks such that overall bandwidth cost is minimized while traffic demands are satisfied with a required reliability level. These networks exhibit high variability in link throughput as modulations schemes are adapted dynamically to ensure acceptable bit-error rate at the receivers according to external conditions such as the weather. First, we formulate an optimal optimization approach based on mixed-integer linear programming, which is subsequently reinforced by inserting problem-specific valid inequalities based on global network capacity and feasible bandwidth/modulation combinations. Then, we introduce a Lagrangian-based heuristic that provides near optimal solutions while reducing drastically the computation time. In comparison to previous work, our experimental results show that our approaches are capable to solve large real-world network instances in an effective manner. Furthermore, the results evaluate the impact of reliability and transported traffic demands on bandwidth cost.

Path Load Adaptive Migration for Routing and Bandwidth Allocation in Mobile-Aware Service Function Chain

With network function virtualization (NFV) expanding from network center to edge, the service function chain (SFC) will gradually approach users to provide lower delay and higher-quality services. User mobility seriously affects the quality of service (QoS) provided by the mobile-aware SFC. Therefore, we must migrate the SFC to provide continuous services. In the user estimable movement scenario with a known mobile path and estimable arrival time, we establish the estimation model of user arrival time to obtain the estimated arrival time. Then, to reduce the time that the user is waiting for the migration completion, we propose a softer migration strategy migrating mobile-aware SFC before the user arrives at the corresponding access node. Moreover, for the problem of routing and bandwidth allocation (RBA), to reduce the migration failure rate, the paper proposes a path load adaptive routing and bandwidth allocation (PLARBA) algorithm adjusting the migration bandwidth according to the path load. The experimental results show that the proposed algorithm has significant advantages in reducing the user’s waiting time by more than 90%, decreasing migration failure rate by up to 75%, and improving QoS compared to the soft migration strategy and two RBA algorithms.

An Experimental Study of the Server-based Unfairness Solutions for the Cross-Protocol Scenario of Adaptive Streaming over HTTP/3 and HTTP/2

Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the server-based unfairness solutions for the cross-protocol scenario of the HAS/3 and HAS/2 is conducted. The results show that, while the bitrate guidance solution fails to help the clients achieve fairness, the bandwidth allocation solution provides superior performance.

Resource Management and 3D Deployment in Power-Efficient Multi-UAV Networks

In this paper, the scenario in which multiple unmanned aerial vehicles (UAVs) provide service to ground users is considered. Under the condition of satisfying the minimum rate per user and system load balance, the user association, bandwidth allocation and three dimensional (3D) deployment of multi-UAV networks are optimized jointly to minimize the total downlink transmit power of UAVs. Since the problem is hard to solve directly, it is decomposed into three sub-problems, and then the problem is solved by alternating iteration algorithm. First, when the UAV’s location is determined, a modified K-means algorithm is used to obtain balanced user clustering. Then, when the user association and UAV’s 3D deployment are determined, the convex optimization method is used to obtain the optimal bandwidth allocation. Finally, when the user association and optimal bandwidth allocation are determined, a modified differential evolution algorithm is proposed to optimize the 3D location of the UAVs. Simulation results show that the proposed algorithm can effectively reduce the transmit power of UAVs compared with the existing algorithms under the conditions of satisfying the minimum rate of ground users and system load balance.

Cell on Wheels-Unmanned Aerial Vehicle System for Providing Wireless Coverage in Emergency Situations

Due to natural disasters, unmanned aerial vehicles (UAVs) can be deployed as aerial wireless base stations when conventional cellular networks are out of service. They can also supplement the mobile ground station to provide wireless devices with improved coverage and faster data rates. Cells on wheels (CoWs) can also be utilized to provide enhanced wireless coverage for short-term demands. In this paper, a single CoW cooperates with a single UAV in order to provide maximum wireless coverage to ground users. The optimization problem is formulated to find the following: (1) the optimal 2D placement of the CoW, (2) the optimal 3D placement of the UAV, (3) the optimal bandwidth allocation, (4) the percentage of the available bandwidth that must be provided to the CoW and UAV, and (5) the priority of wireless coverage; which maximizes the number of covered users. We utilize the exhaustive search (ES) and particle swarm optimization (PSO) algorithms to solve the optimization problem. The effectiveness of the proposed algorithms is validated using simulation results.