Optimization of multitenant radio admission control through a semi-Markov decision process

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Network slicing in future 5G systems enables the provision of multitenant networks in which a network infrastructure owned by an operator is shared among different tenants, such as mobile virtual operators, over-the-top providers or vertical market players. The support of network slicing within the radio access network requires the introduction of appropriate radio resource management functions to ensure that each tenant gets the required radio resources in accordance with the expected service level agreement (SLA). This paper addresses radio admission control (RAC) functionality in multiservice and multitenant scenarios as a mechanism for regulating the acceptance of new guaranteed bit rate service requests of different tenants. This paper proposes an optimization framework that models the RAC as a semi-Markov decision process and, as a result, derives an optimal decision-making policy that maximizes an average long-term function representing the desired optimization target. A reward function is proposed to capture the degree of tenant satisfaction with the received service in relation to the expected SLA, accounting for both the provision of excess capacity beyond the SLA and the cost associated with sporadic SLA breaches. The proposed approach is evaluated by means of simulations, and its superiority to other reference schemes in terms of reward and other key performance indicators is analyzed.Peer ReviewedPostprint (author's final draft

Network Science for IoT

The research work presented in this thesis is based on the concept and defintion of network that can spread in several and different real world contexts. Indeed, we can refer to a network in a telecommunications sense considering a collection of transmitters, receivers, and communication channels that send or are used to send information to one another. However, as a matter of fact, in nature there are other several examples of networks: the human brain is one of them. The relationship between the actors in Hollywood can be studied in terms of network as well, a generic social community can be compared to a network, eco-systems are networks of species. The recent Network Science aims at studying all these systems using a set of common mathematical methods. In the following of the thesis, we will focus on some of well known telecommunications networks issues using standard telecommunications procedures to address them, with relevant reference to video flow transmissions and management of electric vehicles networks. At the same time, different models aiming at reach the same goals in contexts that may differ from a telecommunications setup can be used. In more details, we will evaluate queueing systems, jamming problems, groups recognition in networks, and mobile computing using game theoretic approaches. It is worth noting that this aspect can be also seen in a reverse order. Indeed, we will discuss how standard telecommunications analysis can be used to investigate on problems not directly related to a telecommunications background. In particular, one of our future purposes is to investigate on the brain connectivity that is raising significant interest in the recent scientific society