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

We investigate in this paper the access selection and joint pricing problem in multi-operator wireless networks. The problem is formulated as a Stackelberg game, where cooperating service operators first set the service price to maximize their revenue. Then, the home operator of the mobile user performs the access selection process among the service operators, in order to maximize its own profits and its client satisfaction, in terms of perceived QoS. Competing operators decide the service price following a number of defined pricing schemes, and the home operator uses a hybrid utility function for the selection decision. We consider the Nash equilibrium as a solution of the service price setting game, where the best response is presented in function of the adopted pricing scheme. Simulation results show the efficiency of this multi-leader follower game for the access selection in a multi-operator environment, and illustrate how operators' cooperation enhances network performance and improves operators' revenue.

/pdf/access-selection-and-joint-pricing-in-multi-operator-11olag5w3u.pdf

Access selection and joint pricing in multi-operator wireless networks: A Stackelberg game

Under the hypothesis of single failures in the network, some backup paths cannot be active at the same time because they protect against the failure of different components. Hence, share the bandwidth between such backup paths is central to optimize the bandwidth allocated in the network and to decrease the bandwidth wasting. In this paper, we propose a novel algorithm, based on targeted distribution of resource allocation (TDRA), to compute the backup label switched paths (LSPs) in a distributed multiprotocol label switching (MPLS) environment. Our algorithm is scalable, efficient and capable to protect against the three types of failure risk: node, link and shared risk link group (SRLG). Indeed, the TDRA algorithm decreases the quantity of information (resource or bandwidth allocation) transmitted in the network with the selection of nodes to be advertised (with the selection of recipient nodes). Furthermore, bandwidth availability is increased by sharing bandwidth between backup LSPs as long as possible. Simulations show that the ratio of rejected backup LSPs obtained with the transmission of a small quantity of information in the network is low.

/pdf/targeted-distribution-of-resource-allocation-for-backup-lsp-2zyvz5hsgh.pdf

Targeted Distribution of Resource Allocation for Backup LSP Computation

Monitoring the quality of service in a multi-domain network allows providers to ensure the control of multi-domain service performance. A multi-domain service is a service that crosses multiple domains. In this paper, we propose several mechanisms for fault detection and fault localization. A fault is detected when an end-to-end contract is not respected. Faulty domains are domains that do not fulfill their Quality of Service (QoS) requirements. Our three proposed fault detection and localization mechanisms (FDLM) depend on the export method used. These export methods define how the measurement results are exported for analysis. We consider the periodic export, the triggered export, and a combined method. For each FDLM, we propose two sub-schemes that use different fault detection strategies. In this paper, we describe these mechanisms and evaluate their performance using Network Simulator (NS-2).

https://hal.archives-ouvertes.fr/hal-01183602/document

QoS fault detection and localization mechanisms (FDLM) in multi-domain networks adapted to export methods

Energy optimization has become a crucial issue in the realm of ICT. This paper addresses the problem of energy consumption in a Metro Ethernet network. Ethernet technology deployments have been increasing tremendously because of their simplicity and low cost. However, much research remains to be conducted to address energy efficiency in Ethernet networks. In this paper, we propose a novel Energy Aware Forwarding Strategy for Metro Ethernet networks based on a modification of the Internet Energy Aware Routing (EAR) algorithm. Our contribution identifies the set of links to turn off and maintain links with minimum energy impact on the active state. Our proposed algorithm could be a superior choice for use in networks with low saturation, as it involves a tradeoff between maintaining good network performance and minimizing the active links in the network. Performance evaluation shows that, at medium load traffic, energy savings of 60% can be achieved. At high loads, energy savings of 40% can be achieved without affecting the network performance.

Energy-Aware Forwarding Strategy for Metro Ethernet Networks

Ethernet, which has traditionally been the dominant technology in local area networks, is now facing new challenges due to the fact that networks have scaled and today's applications require more bandwidth and increased robustness against failures. The limitations of Ethernet are mainly imposed by the spanning tree protocol, which is necessary to prevent loops and provide redundancy in a switched network. The successful deployment of Ethernet over MPLS in the metro area have proved that Ethernet LANs can be further enriched with the services enabled by the label switching technique. In this article, we propose a new LAN interconnection technique based on label switching, which enhances network services, simplifies switch functionalities, while remaining flexible enough to be easily deployed in most LAN environments

/pdf/a-new-scheme-for-interconnecting-lans-with-label-switching-39zzys5osy.pdf

Bernard Cousin

Papers

Access selection and joint pricing in multi-operator wireless networks: A Stackelberg game

Targeted Distribution of Resource Allocation for Backup LSP Computation

QoS fault detection and localization mechanisms (FDLM) in multi-domain networks adapted to export methods

Energy-Aware Forwarding Strategy for Metro Ethernet Networks

A new scheme for interconnecting LANs with label switching bridges