Power Aware Routing in Mobile Ad Hoc Networks

To support bursty traffic on the Internet (and especially WWW) efficiently, optical burst switching (OBS) is proposed as a way to streamline both protocols and hardware in building the future gener...

Optical burst switching (OBS) - a new paradigm for an optical Internet

Computer communications

In the fifth-generation (5G) mobile communication system, various service requirements of different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous network (HetNet) has been studied in recent years. Compared with homogeneous networks, HetNets can increase the opportunity in the spatial resource reuse and improve users’ quality of service by developing small cells into the coverage of macrocells. Since there is mutual interference among different users and the limited spectrum resource in HetNets, however, efficient resource allocation (RA) algorithms are vitally important to reduce the mutual interference and achieve spectrum sharing. In this article, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNets. Second, RA models are discussed. Then, we present a classification to analyze current RA algorithms for the existing works. Finally, some challenging issues and future research trends are discussed. Accordingly, we provide two potential structures for 6G communications to solve the RA problems of the next-generation HetNets, such as a learning-based RA structure and a control-based RA structure. The goal of this article is to provide important information on HetNets, which could be used to guide the development of more efficient techniques in this research area.

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A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges

Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time, within a highly dynamic environment. This need for stringent communication quality-of-service (QoS) requirements as well as mobile edge and core intelligence can only be realized by integrating fundamental notions of artificial intelligence (AI) and machine learning across the wireless infrastructure and end-user devices. In this context, this paper provides a comprehensive tutorial that introduces the main concepts of machine learning, in general, and artificial neural networks (ANNs), in particular, and their potential applications in wireless communications. For this purpose, we present a comprehensive overview on a number of key types of neural networks that include feed-forward, recurrent, spiking, and deep neural networks. For each type of neural network, we present the basic architecture and training procedure, as well as the associated challenges and opportunities. Then, we provide an in-depth overview on the variety of wireless communication problems that can be addressed using ANNs, ranging from communication using unmanned aerial vehicles to virtual reality and edge caching.For each individual application, we present the main motivation for using ANNs along with the associated challenges while also providing a detailed example for a use case scenario and outlining future works that can be addressed using ANNs. In a nutshell, this article constitutes one of the first holistic tutorials on the development of machine learning techniques tailored to the needs of future wireless networks.

Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial

When multicasting in optical networks is implemented within the switching control plane, it combines the efficiency of multicast trees along with the high speed and low delay of optical communications. Multicast nodes must be equipped with light splitters. Light splitters are expensive equipment. Therefore, a limited number of optical nodes will have this splitting capability. A good placement of optical splitters can increase the efficiency of the multicast signaling and routing techniques on the one hand, and reduce the number of splitters on the other hand. This leads to faster multicast trees setting up, lower data transmission delays, and less traffic on the network links; thus saving of optical links capacity for other multicast and unicast transmissions. In order to achieve efficient multicasting in optical network, we propose to take into account network characteristics i.e. link capacity and node degree when placing the optical splitters. The benefits of the smart placement of light splitters will be clearly shown in heterogeneous optical networks, where multicast traffic is not uniformly distributed over the network, and optical links connecting different nodes in the network have different characteristics.

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Efficient placement of light splitters in heterogeneous optical networks

Heterogeneous Networks (HetNETs) are considered as an effective solution to improve the coverage and system throughput for future cellular networks. The extremely growing mobile market, together with the arising demand for high data rates, motivate us to open a new spectrum related to millimeter waves (mmwaves) while using beamforming that can serve simultaneously a group of users. In this paper, we formulate an optimization problem for HetNETs multi-user selection in a multi-input-multi-output and orthogonal frequency-division multiple access (MIMO-OFDMA) system, aiming to maximize the total system throughput. We solve the problem by applying a modified version of well-known metaheuristic algorithms. The optimal solution is obtained using an exhaustive search algorithm that provides an ideal solution which is complex to be computed. Greedy zero-forcing dirty-paper gZF-DP and zeroforcing selection ZFS algorithms were selected from literature for the sub-optimal solution. In parallel, a water-filling algorithm has been optimized after adding new power constraint and it has been used for power distribution. Hence, we analyze the throughput performance of our systems using throughput metric. The results show that ZFS outperforms gZF-DP algorithm as it achieves higher total throughput, While gZF-DP outperforms ZFS algorithm in the execution time.

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User Selection in 5G Heterogeneous Networks Based on Millimeter-Wave and Beamforming

Mutli-domain monitoring aims at guaranteeing QoS for services crossing several domains. It is often desirable to perform global monitoring to guarantee end-to-end QoS for services across domains and to reduce the monitoring cost. However, global monitoring might be infeasible due to confidentiality constraints. The alternative solution is to perform per-domain monitoring. In this work, we propose to evaluate global and per-domain monitoring techniques. For this end, we study the properties of multi-domain networks and the requirements of multi-domain monitoring. We formulate the problem as an Integer Linear Program (ILP). We show that it is a Nondeterministic Polynomial Time Hard (NP-Hard) problem, and therefore, we devise a heuristic that meets multi-domain properties. We show that confidentiality is far from being the only constraint to global multi-domain monitoring. In our evaluation, the confidentiality constraint has been relaxed, in order to investigate other performance metrics; namely, the monitoring cost, the quality of monitored paths, the anomaly detection delays, and the fairness of monitoring load distribution among domains. Simulation results on random topologies show that per-domain monitoring outperforms global monitoring for all these metrics, except the monitoring cost that is slightly lower for global monitoring.

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Global Vs. Per-domain monitoring of multi-domain networks

In multi-protocol label switching-traffic engineering (MPLS-TE) networks with distributed tunnel path computation on head-end routers, tunnel requests are handled one by one, in an uncoordinated manner without any knowledge of future and other requests. The order in which requests are handled has a significant impact on the network optimization and blocking probability. If it is not possible to control the arrival order, in return it is possible, in some cases, to reorder requests using the preemption function. This paper evaluates the impact of the arrival order, so as to determine efficient orders. It then proposes two preemption strategies so as to reorder arrivals and evaluate these strategies applied to the shortest constrained path computation algorithm.

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Improved MPLS-TE LSP Path Computation using Preemption

https://hal.archives-ouvertes.fr/hal-01241530/document

Bernard Cousin

Papers

Efficient placement of light splitters in heterogeneous optical networks

User Selection in 5G Heterogeneous Networks Based on Millimeter-Wave and Beamforming

Global Vs. Per-domain monitoring of multi-domain networks

Improved MPLS-TE LSP Path Computation using Preemption

Optimization models for the joint Power-Delay minimization problem in green wireless access networks