Jorge Crichigno

Protocols and architectures for channel assignment in wireless mesh networks

The use of multiple channels can substantially improve the performance of wireless mesh networks. Considering that the IEEE PHY specification permits the simultaneous operation of three non-overlapping channels in the 2.4GHz band and 12 non-overlapping channels in the 5GHz band, a major challenge in wireless mesh networks is how to efficiently assign these available channels in order to optimize the network performance. We survey and classify the current techniques proposed to solve this problem in both single-radio and multi-radio wireless mesh networks. This paper also discusses the issues in the design of multi-channel protocols and architectures.

Multiobjective multicast routing algorithm for traffic engineering

This paper presents a new version of a multiobjective multicast routing algorithm (MMA) for traffic-engineering, based on the strength Pareto evolutionary algorithm (SPEA), which simultaneously optimizes the maximum link utilization, the cost of the tree, the maximum end-to-end delay and the average delay. In this way, a set of optimal solutions, known as Pareto set, is calculated in only one run, without a priori restrictions. Simulation results show that MMA is able to find Pareto optimal solutions. They also show that for dynamic multicast routing, where the traffic requests arrive one after another, MMA outperforms other known algorithms

Multiobjective Multicast Routing Algorithm

This paper presents a new multiobjective multicast routing algorithm (MMA) based on the Strength Pareto Evolutionary Algorithm (SPEA), which simultaneously optimizes the cost of the tree, the maximum end-to-end delay, the average delay and the maximum link utilization. In this way, a set of optimal solutions, known as Pareto set, is calculated in only one run, without a priori restrictions. Simulation results show that MMA is able to find Pareto optimal solutions. They also show that for the constrained end-to-end delay problem in which the traffic demands arrive one by one, MMA outperforms the shortest path algorithm in maximum link utilization and total cost metrics.

A Multicast Routing Algorithm Using Multiobjective Optimization

Multicast routing problem in computer networks, with more than one objective to consider, like cost and delay, is usually treated as a mono-objective Optimization Problem, where the cost of the tree is minimized subject to a priori restrictions on the delays from the source to each destination. This paper presents a new multicast algorithm based on the Strength Pareto Evolutionary Algorithm (SPEA), which simultaneously optimizes the cost of the tree, the maximum end-to-end delay and the average delay from the source node to each destination node. Simulation results show that the proposed algorithm is able to find Pareto optimal solutions. In addition, they show that for the problem of minimum cost with constrained end-to-end delay, the proposed algorithm provides better solutions than other well-known alternatives as Shortest Path and KPP algorithms.

Throughput Optimization and Traffic Engineering in WDM Networks Considering Multiple Metrics

Throughput optimization and traffic engineering in Wavelength-Division Multiplexing (WDM) networks are usually treated as mono-objective optimization problems. In this paper, we provide a multi-objective Integer Linear Program (ILP) for the joint throughput optimization and traffic engineering problem. By simultaneously i) maximizing the throughput, ii) minimizing the resource consumption, and iii) balancing the traffic load, we demonstrate that better solutions than those of mono-objective approaches are obtained. We also present a distributed heuristic algorithm, which upper-bounds the per-route resource consumption and maximizes the throughput. Simulation results validate the proposed model and heuristic algorithm. Additionally, we present an ILP formulation for another well-known problem such as routing and wavelength assignment (RWA), and discuss the impact of modeling it as a multi-objective problem.

Dynamic Routing Optimization in WDM Networks

We present a multi-objective optimization approach for joint throughput optimization and traffic engineering, where the routing request of traffic arrives one-by-one. We provide an Integer Linear Program (ILP) that simultaneously i) maximizes the aggregate throughput, ii) minimizes the resource consumption, and iii) minimizes the maximum link utilization. We study the impact of optimizing the three different objectives simultaneously in dynamic environments, and show that better solutions than those of mono-objective approaches can be obtained. Because of the complexity of the ILP, we also propose another ILP with reduced complexity, and study its performance and the optimality gap between it and optimal solutions.

Throughput Optimization in Multihop Wireless Networks with Multipacket Reception and Directional Antennas

Recent advances in the physical layer have enabled the simultaneous reception of multiple packets by a node in wireless networks. We address the throughput optimization problem in wireless networks that support multipacket reception (MPR) capability. The problem is modeled as a joint routing and scheduling problem, which is known to be NP-hard. The scheduling subproblem deals with finding the optimal schedulable sets, which are defined as subsets of links that can be scheduled or activated simultaneously. We demonstrate that any solution of the scheduling subproblem can be built with |E| + 1 or fewer schedulable sets, where |E| is the number of links of the network. This result is in contrast with previous works that stated that a solution of the scheduling subproblem is composed of an exponential number of schedulable sets. Due to the hardness of the problem, we propose a polynomial time scheme based on a combination of linear programming and approximation algorithm paradigms. We illustrate the use of the scheme to study the impact of design parameters on the performance of MPR-capable networks, including the number of transmit interfaces, the beamwidth, and the receiver range of the antennas.

A joint routing and scheduling scheme for wireless networks with multi-packet reception and directional antennas

In this paper, we present a linear programming formulation for the throughput optimization problem in wireless networks that support multi-packet reception (MPR) capability. The formulation takes into account the use of both directional and omni-directional antennas as well as the use of multiple transmitter interfaces per node. The joint routing and scheduling problem is decoupled into routing and scheduling subproblems. We show that the scheduling subproblem is intractable, and propose a polynomial time scheduling algorithm to solve it. We further demonstrate that, for certain type of networks, the completion time of the scheduling algorithm is at most two times the completion time of the the optimal scheduler, which is unknown. We use the proposed scheme for a preliminary study of several design parameters on the performance of MPR-capable networks, including the number of interfaces, the MPR capability and the beamwidth of the antennas.

Throughput Optimization in Wireless Networks with Multi-Packet Reception and Directional Antennas

Recent advances in the physical layer have enabled the simultaneous reception of multiple packets by a node in wireless networks. In this paper, we present a generalized model for the throughput optimization problem in wireless networks that support multi-packet reception (MPR) capability. Our model directly accounts for nodes with multiple transmitter antennas, which can be directional or omni-directional. We divide the problem into two subproblems: routing and scheduling. Due to the hardness of the scheduling subproblem, we propose a polynomial time heuristic based on a combination of greedy and linear programming paradigms. We use the devised scheme to study the impact of several design parameters on the performance of MPR-capable networks, including the number of interfaces, the beamwidth and the receiver range of the antennas. Numerical results demonstrate the effectiveness and the generality of the scheme, and permit us to draw valuable conclusions about MPR-capable networks.

Flexible advance reservation models for virtual network scheduling

Advance reservation services allows users to pre-reserve network resources at future instants in time. These offerings are already being used by a wide range of applications in scientific/grid computing, datacenter backup, and event broadcasting. Now most advance reservation algorithms are designed to schedule point-to-point connection requests. However, as new cloud-based services gain traction, there is a further need to schedule broader virtual network (infrastructure services) demands. These latter types are much more complex and comprise of an arbitrary number of virtual nodes mapped onto physical nodes and interconnected via a set of virtual link connections. This paper addresses this critical area and develops/analyzes several virtual network scheduling schemes, including partial provisioning strategies to improve network revenues.