Wireless communication, identification and sensing technologies enabling integrated logistics: a study in the harbor environment

In the last decade, integrated logistics has become an important challenge in the development of wireless communication, identification and sensing technology, due to the growing complexity of logistics processes and the increasing demand for adapting systems to new requirements. The advancement of wireless technology provides a wide range of options for the maritime container terminals. Electronic devices employed in container terminals reduce the manual effort, facilitating timely information flow and enhancing control and quality of service and decision made. In this paper, we examine the technology that can be used to support integration in harbor's logistics. In the literature, most systems have been developed to address specific needs of particular harbors, but a systematic study is missing. The purpose is to provide an overview to the reader about which technology of integrated logistics can be implemented and what remains to be addressed in the future

Enhancing IEEE 802.11MAC in congested environments

IEEE 802.11 is currently the most deployed wireless local area networking standard. It uses carrier sense multiple access with collision avoidance (CSMA/CA) to resolve contention between nodes. Contention windows (CW) change dynamically to adapt to the contention level: Upon each collision, a node doubles its CW to reduce further collision risks. Upon a successful transmission, the CW is reset, assuming that the contention level has dropped. However, the contention level is more likely to change slowly, and resetting the CW causes new collisions and retransmissions before the CW reaches the optimal value again. This wastes bandwidth and increases delays. In this paper we analyze simple slow CW decrease functions and compare their performances to the legacy standard. We use simulations and mathematical modeling to show their considerable improvements at all contention levels and transient phases, especially in highly congested environments

Backoff as Performance improvements Algorithms - A Comprehenssive Review

As a significant part of the Media Access Control protocol, the backoff algorithm purpose is to minimize number of collisions if not totally avoid any collision in Mobile Ad Hoc Networks, in the case of contention between nodes to access a channel. Researchers have proposed many algorithms for backoff to enhance the network performance and improve it. This paper aims at exploring the main and most studied backoff algorithms and how do these algorithms lead to an enhancement of the MANETs performance. This paper also compares between the algorithms proposed in the literature and evaluates to what extent they have affected the performance and enhance it

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Beyond multimedia adaptation: Quality of experience-aware multi-sensorial media delivery

Multiple sensorial media (mulsemedia) combines multiple media elements which engage three or more of human senses, and as most other media content, requires support for delivery over the existing networks. This paper proposes an adaptive mulsemedia framework (ADAMS) for delivering scalable video and sensorial data to users. Unlike existing two-dimensional joint source-channel adaptation solutions for video streaming, the ADAMS framework includes three joint adaptation dimensions: video source, sensorial source, and network optimization. Using an MPEG-7 description scheme, ADAMS recommends the integration of multiple sensorial effects (i.e., haptic, olfaction, air motion, etc.) as metadata into multimedia streams. ADAMS design includes both coarse- and fine-grained adaptation modules on the server side: mulsemedia flow adaptation and packet priority scheduling. Feedback from subjective quality evaluation and network conditions is used to develop the two modules. Subjective evaluation investigated users' enjoyment levels when exposed to mulsemedia and multimedia sequences, respectively and to study users' preference levels of some sensorial effects in the context of mulsemedia sequences with video components at different quality levels. Results of the subjective study inform guidelines for an adaptive strategy that selects the optimal combination for video segments and sensorial data for a given bandwidth constraint and user requirement. User perceptual tests show how ADAMS outperforms existing multimedia delivery solutions in terms of both user perceived quality and user enjoyment during adaptive streaming of various mulsemedia content. In doing so, it highlights the case for tailored, adaptive mulsemedia delivery over traditional multimedia adaptive transport mechanisms