Increasing the capacity of wireless mesh networks has motivated numerous studies. In this context, the cross-layer optimization techniques involving joint use of routing and link scheduling are able to provide better capacity improvements. Most works in the literature propose linear programming models to combine both mechanisms. However, this approach has high computational complexity and cannot be extended to large-scale networks. Alternatively, algorithmic solutions are less complex and can obtain capacity values close to the optimal. Thus, we propose the REUSE algorithm, which combines routing and link scheduling and aims to increase throughput capacity in wireless mesh networks. Through simulations, the performance of the proposal is compared to a developed linear programming model, which provides optimal results, and to other proposed mechanisms in the literature that also deal with the problem algorithmically. We observed higher values of capacity in favor of our proposal when compared to the benchmark algorithms.
Abstract-This work investigates the problem of channel sensing order used by a cognitive multichannel network, where each user is able to perform primary user detection on only one channel at a time. The sensing order indicates the sequence of channels sensed by the secondary users when searching for an available channel. When using an optimal sensing order, the secondary user can find faster a free channel with high quality. Brute-force algorithms may be used to find the optimal sensing order. However, this approach requires great computational effort. Even in scenarios where the secondary user knows the probability of each channel being available, the sensing order where the most available channels are sensed first is not ideal when using adaptive modulation. Therefore, we propose an approach using reinforcement learning to search dynamically for the optimal sensing order. Through simulations, we evaluated our proposal and compared its performance with other mechanisms, and the results obtained are close to the optimal value provided by the brute-force and superior to the other mechanisms in most of the scenarios.
Abstract-Data and control messages broadcasting is a widely used mechanism in network applications and protocols, which can have latency requirements for the information delivery. One solution to achieve low latencies is to solve the Minimum-Latency Broadcast Scheduling (MLBS) problem. However, MLBS is a NP-Complete problem, thus some works propose approximation algorithms. This paper presents simulation results of wellknown flood control mechanisms over IEEE 802.11 scheduling (CSMA/CA), which show that simple heuristics can provide acceptable latencies. Thus, a distributed scheduling mechanism that requires only partial topology knowledge is proposed and evaluated when combined with flood control mechanisms on CSMA/CA and TDMA networks. Results show the good performance of the proposal compared to theoretical limits of centralized algorithms.
Abstract. Service discovery allows the interaction between network nodes to cooperate in activities or to share resources in client-server, multi-layer, as well as in peer-to-peer architectures. Ad hoc networks pose a great challenge in the design of efficient mechanisms for service discovery. The lack of infrastructure along with node mobility makes it difficult to build robust, scalable and secure mechanisms for ad hoc networks. This paper proposes a scalable service discovery architecture based on directory nodes organized in an overlay network. In the proposed architecture, directory nodes are dynamically created with the aim of uniformly covering the entire network while decreasing the query latency for a service (QoS) and the number of control messages for the sake of increased scalability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.