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

https://www.irisa.fr/prive/Bernard.Cousin/Articles/Articles%202010/COMCOM-2010.pdf

A survey of survivability in multi-domain optical networks

In this paper we study different options for the survivability implementation in MPLS over Optical Transport Networks (OTN) in terms of network resource usage and configuration cost. We investigate two approaches to the survivability deployment: single layer and multilayer survivability and present various methods for spare capacity allocation (SCA) to reroute disrupted traffic. The comparative analysis shows the influence of the offered traffic granularity and the physical network structure on the survivability cost: for high bandwidth LSPs, close to the optical channel capacity, the multilayer survivability outperforms the single layer one, whereas for low bandwidth LSPs the single layer survivability is more cost-efficient. On the other hand, sparse networks of low connectivity parameter use more wavelengths for optical path routing and increase the configuration cost, as compared with dense networks. We demonstrate that by mapping efficiently the spare capacity of the MPLS layer onto the resources of the optical layer one can achieve up to 22% savings in the total configuration cost and up to 37% in the optical layer cost. Further savings (up to 9 %) in the wavelength use can be obtained with the integrated approach to network configuration over the sequential one, however, at the increase in the optimization problem complexity. These results are based on a cost model with different cost variations, and were obtained for networks targeted to a nationwide coverage.

Survivable MPLS Over Optical Transport Networks: Cost and Resource Usage Analysis

To minimize the number of wavelengths required by a multicast session in sparse light splitting Wavelength Divi- sion Multiplexing (WDM) networks, a light-hierarchy structure, which occupies the same wavelength on all links, is proposed to span as many destinations as possible. Different from a light- tree, a light-hierarchy accepts cycles, which are used to traverse crosswise a 4-degree (or above) multicast incapable (MI) node twice (or above) and switch two light signals on the same wavelengths to two destinations in the same multicast session. In this paper, firstly, a Graph Renewal and Distance Priority Light-tree algorithm (GRDP-LT) is introduced to improve the quality of light-trees built for a multicast request. Then, it is extended to compute light-hierarchies. Obtained numerical results demonstrate the GRDP-LT light-trees can achieve a much lower links stress, better wavelength channel cost, and smaller average end-to-end delay as well as diameter than the currently most efficient algorithm. Furthermore, compared to light-trees, the performance in terms of link stress and network throughput is greatly improved again by employing the light-hierarchy, while consuming the same amount of wavelength channel cost.

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Is Light-Tree Structure Optimal for Multicast Routing in Sparse Light Splitting WDM Networks?

Based on the false assumption that multicast incapable (MI) nodes could not be traversed twice on the same wavelength, the light-tree structure was always thought to be optimal for multicast routing in sparse splitting Wavelength Division Multiplexing (WDM) networks. In fact, for establishing a multicast session, an MI node could be crosswise visited more than once to switch a light signal towards several destinations with only one wavelength through different input and output pairs. This is called Cross Pair Switching (CPS). Thus, a new multicast routing structure light-hierarchy is proposed for alloptical multicast routing, which permits the cycles introduced by the CPS capability of MI nodes. We proved that the optimal structure for minimizing the cost of multicast routing is a set of light-hierarchies rather than the light-trees in sparse splitting WDM networks. Integer linear programming (ILP) formulations are developed to search the optimal light-hierarchies. Numerical results verified that the light-hierarchy structure could save more cost than the light-tree structure.

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Light-hierarchy: the optimal structure for multicast routing in WDM mesh networks

Redundant sensing capabilities are often required in sensor network applications due to various reasons, e.g. robustness, fault tolerance, or increased accuracy. At the same time high sensor redundancy offers the possibility of increasing network lifetime by scheduling sleep intervals for some sensors and still providing continuous service with help of the remaining active sensors. In this paper centralized and distributed algorithms are proposed to solve the k-coverage sensing problem and maximize network lifetime. When physically possible, the proposed robust Controlled Greedy Sleep Algorithm provides guaranteed service independently of node and communication errors in the network. The performance of the algorithm is illustrated and compared to results of a random solution by simulation examples.

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Bernard Cousin

Papers

A survey of survivability in multi-domain optical networks

Survivable MPLS Over Optical Transport Networks: Cost and Resource Usage Analysis

Is Light-Tree Structure Optimal for Multicast Routing in Sparse Light Splitting WDM Networks?

Light-hierarchy: the optimal structure for multicast routing in WDM mesh networks

Dependable k-coverage algorithms for sensor networks