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

The surge of mobile data traffic has spurred academia and industries to begin developing 5G networks. 5G is meant to overcome limitations of 4G cellular technology relying on the dominant trend of mobile network densification with the deployment of small cell base stations. To accelerate this process, low complexity and inexpensive remote radio heads (RRHs) are deployed massively and connected to a centralized pool of resources. In this work, we study the problem of inter-cell interference (ICI) which arises in frequency reuse one multi-tier 5G networks. We entrust the management of RRHs to a software-defined network controller and we take advantage of network functions virtualization. Our contributions consist of proposing Dynamic Strict Fractional Frequency Reuse (DSFFR), a method to relieve ICI which dynamically divides the small cell area in a different number of sectors. Furthermore, we formulate a joint scheduling problem composed of two schedulers which operate at different time granularity to transmit downlink packets. Modeling the coverage area with the tool of stochastic geometry and solving with simulations the joint scheduling problem, we are able to show that DSFFR outperforms the static scheme. Performances are addressed in terms of spectral efficiency and packet blocking probability.

Dynamic strict fractional frequency reuse for software-defined 5G networks

D2D communication and cognitive radio are among the key technologies that can solve the bandwidth bottleneck problem of cellular networks. These technologies help to maintain necessary communication between the user devices in case of natural disasters and traffic hotspot situations. In this paper, we efficiently employ the relay selection and cooperative beamforming (CBF) strategies for D2D communication and show that the user devices can securely communicate with each other without infrastructure support. The cloud heads in our proposal act as the primary users (PUs) and the cloud members are regarded as the secondary users (SUs) or the relay nodes. To investigate the efficiency of our proposal, we define the utilities of PUs employing relay selection and CBF, considering received signal power, latency, channel gain and security. We optimize relay selection and beamforming vector by solving mixed integer non-linear problem (MINLP). Numerical results show the efficiency and robustness of our approach.

Cognitive Radio and Device-to-Device Communication: A Cooperative Approach for Disaster Response

The advent of network softwarization is enabling multiple innovative solutions through software-defined networking (SDN) and network function virtualization (NFV). Specifically, network softwarization paves the way for autonomic and intelligent networking, which has gained popularity in the research community. Along with the arrival of 5G and beyond, which interconnects billions of devices, the complexity of network management is significantly increasing both investments and operational costs. Autonomic networking is the creation of self-organizing, self-managing, and self-protecting networks, to afford the network management complexes and heterogeneous networks. To achieve full network automation, various aspects of networking need to be addressed. So, this article proposes a novel architecture for the multi-agent-based network automation of the network management system (MANA-NMS). The architecture rely on network function atomization , which defines atomic decision-making units. Such units could represent virtual network functions. These atomic units are autonomous and adaptive. First, the article presents a theoretical discussion of the challenges arisen by automating the decision-making process. Next, the proposed multi-agent system is presented along with its mathematical modeling. Finally, MANA-NMS architecture is mathematically evaluated from functionality, reliability, latency, and resource consumption performance perspectives.

Multi-Agent Based Autonomic Network Management Architecture

Energy efficiency during spectrum sensing in cognitive radio has received a lot of attention during recent years. Such issue becomes challenging, especially with battery-powered terminals, because of its direct influence on achievable performance represented by detection accuracy. In this paper, we present a novel reporting scheme for spectrum sensing results, which significantly reduces the energy consumption without any effect on the detection accuracy. The proposed scheme is based on the observation that sensing results are consecutively reported to a Fusion Center (FC), which allows the FC to terminate the process whenever the received results are enough to make a decision according to the employed Fusion Rule (FR). Hence, the energy consumed in results' reporting is reduced as the number of reporting users is lower. Mathematical expressions for the average number of reporting users for several FRs are obtained. Simulation and analytical results show a significant reduction of the energy consumption.

Novel energy-efficient reporting scheme for spectrum sensing results in cognitive radio

The paper presents a methodology for the evaluation of the complexity and computational cost of different block ciphers, in order to be independent from the actual platforms they are implemented on. An analysis of three block ciphers se- lected by NESSIE (New European Schemes for Signatures, Integrity and Encryp- tion) in 2003 - Rijndael, Camellia and Shacal-2 - is then provided using such methodology. First, the structure of all ciphers is described, so as to emphasize the different kinds of transformations required. Then, the schemes are compared in terms of basic operations (AND, OR, shifts) for each step, in such a way to evaluate their complexity and to provide effective guidelines regarding their imple- mentation.

/pdf/a-novel-methodology-for-analysis-of-the-computational-upkrvf7rcc.pdf

Fabrizio Granelli

Papers

Dynamic strict fractional frequency reuse for software-defined 5G networks

Cognitive Radio and Device-to-Device Communication: A Cooperative Approach for Disaster Response

Multi-Agent Based Autonomic Network Management Architecture

Novel energy-efficient reporting scheme for spectrum sensing results in cognitive radio

A novel methodology for analysis of the computational complexity of block ciphers: Rijndael, Camellia and Shacal-2 compared.