There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Table Of Integrals Series And Products

Technological evolution of mobile user equipment (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. A suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud. Nevertheless, this option introduces significant execution delay consisting of delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such a delay is inconvenient and makes the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling it to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: 1) decision on computation offloading; 2) allocation of computing resource within the MEC; and 3) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Technological evolution of mobile user equipments (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. Suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud (CC). Nevertheless, this option introduces significant execution delay consisting in delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such delay is inconvenient and make the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: i) decision on computation offloading, ii) allocation of computing resource within the MEC, and iii) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

Advancements in network technologies dramatically increased management complexity. Cognitive networking was introduced to deal with this problem, by providing algorithms for autonomous network management and protocol reconfiguration. In this paper, we propose a framework for cognitive configuration and optimization of communication protocols called CogProt. CogProt is a distributed framework that allows dynamic reconfiguration of operational protocol stack parameters for optimizing protocol performance under changing network conditions. As a proof of concept, the framework is illustrated for the cognitive configuration of TCP congestion window evolution. In this setup, the TCP window increase factor is adjusted in runtime based on the TCP goodput experienced in the immediate past. Simulation results demonstrate that the proposed cognitive framework is able to improve average TCP performance under changing network conditions.

/pdf/cogprot-a-framework-for-cognitive-configuration-and-oueg07ep6t.pdf

CogProt: A Framework for Cognitive Configuration and Optimization of Communication Protocols

Device-to-Device (D2D) communication has emerged as a new technology, which minimizes data transmission in radio access networks by leveraging direct interaction between nearby mobile devices. D2D communication has a great potential in solving the capacity bottleneck problem of cellular networks by offloading cellular traffic of proximity-based applications to D2D links. This provides several benefits including, but are not limited to, lower transfer delays, higher data rates, and better energy efficiency. However, security in D2D communication, which is equally essential for the success of D2D communication in future networks, is a less investigated topic in literature. In this paper, we propose the combination of the PGP and reputation-based model to bootstrap trust in D2D environments. Our proposal aims at minimizing any suspicious connection with selfish users. Offloading cellular traffic to trusted D2D links provides significant throughput gain over the conventional cellular network. Our results show that the capacity gain can be as high as 133%.

Towards bootstrapping trust in D2D using PGP and reputation mechanism

Vehicle-to-everything (V2X) communication is a powerful concept that not only ensures public safety (e.g., by avoiding road accidents) but also offers many economic benefits (e.g., by optimizing the macroscopic behavior of the traffic across an area). On the one hand, V2X communication brings new business opportunities for many stakeholders, such as vehicle manufacturers, retailers, Mobile Network Operators (MNOs), V2X service providers, and governments. On the other hand, the convergence of these stakeholders to a common platform possesses many technical and business challenges. In this article, we identify the issues and challenges faced by V2X communications, while focusing on the business models. We propose different solutions to potentially resolve the identified challenges in the framework of 5G networks and propose a high-level hierarchy of a potential business model for a 5G-based V2X ecosystem. Moreover, we provide a concise overview of the legislative status of V2X communications across different regions in the world.

/pdf/a-business-and-legislative-perspective-of-v2x-and-mobility-4fbd501481.pdf

A Business and Legislative Perspective of V2X and Mobility Applications in 5G Networks

Typical smart city applications generally require two different communications infrastructures, a wide area cellular network to provide connectivity and long-range communications and efficient communication strategies for transmitting short data packets, particularly in case of Internet of Things (IoT) devices The cellular infrastructure is optimized for high data rates and large data sizes while IoT devices mostly exchange small data packets with high energy efficiency and low data rates To fully exploit both communication infrastructures together, different strategies related to 5G and Device-to-Device (D2D) communications are proposed in literature In this paper, we survey these strategies and provide useful considerations for seamless integration of smart city applications in 5G networks Moreover, we present smart city scenarios, their communication requirements and the potential impact on the life of citizens Finally, we elaborate big data impact on smart cities with possible security and privacy concerns

Integrating smart city applications in 5G networks

Collaborative spectrum sensing (CSS) consumes a significant amount of energy during sensing and reporting the sensing results. Such an issue becomes a challenge in the multi-channel systems. In this paper we propose two different energy-efficient CSS schemes, namely, Reduced-Energy Sensing Scheme (RESS) and Reduced-Energy Reporting Scheme (RERS). In RESS, the channels that have been identified as occupied will not be sensed for a number of next sensing rounds, while in RERS, only the sensing results of a subset of the sensed channels will be reported channels. In both schemes, the energy and time resources expended in CSS will be saved. Moreover, the saved time will be exploited in data transmission, improving the throughput. Simulation results show a significant improvement in the energy efficiency of multi-channel CSS.

Fabrizio Granelli

Papers

CogProt: A Framework for Cognitive Configuration and Optimization of Communication Protocols

Towards bootstrapping trust in D2D using PGP and reputation mechanism

A Business and Legislative Perspective of V2X and Mobility Applications in 5G Networks

Integrating smart city applications in 5G networks

Multi-channel collaborative spectrum sensing in cognitive radio networks