1,721,028 research outputs found
Artificial Intelligence to Reshape the Healthcare Ecosystem
No full textThis paper intends to provide the reader with an overview of the main processes that are introducing artificial intelligence (AI) into healthcare services. The first part is organized according to an evolutionary perspective. We first describe the role that digital technologies have had in shaping the current healthcare methodologies and the relevant foundations for new evolutionary scenarios. Subsequently, the various evolutionary paths are illustrated with reference to AI techniques and their research activities, specifying their degree of readiness for actual clinical use. The organization of this paper is based on the interplay three pillars, namely, algorithms, enabling technologies and regulations, and healthcare methodologies. Through this organization we introduce the reader to the main evolutionary aspects of the healthcare ecosystem, to associate clinical needs with appropriate methodologies. We also explore the different aspects related to the Internet of the future that are not typically presented in papers that focus on AI, but that are equally crucial to determine the success of current research and development activities in healthcare
Application of Proximal Policy Optimization for Resource Orchestration in Serverless Edge Computing
No full textServerless computing is a new cloud computing model suitable for providing services in both large cloud and edge clusters. In edge clusters, the autoscaling functions play a key role on serverless platforms as the dynamic scaling of function instances can lead to reduced latency and efficient resource usage, both typical requirements of edge-hosted services. However, a badly configured scaling function can introduce unexpected latency due to so-called “cold start” events or service request losses. In this work, we focus on the optimization of resource-based autoscaling on OpenFaaS, the most-adopted open-source Kubernetes-based serverless platform, leveraging real-world serverless traffic traces. We resort to the reinforcement learning algorithm named Proximal Policy Optimization to dynamically configure the value of the Kubernetes Horizontal Pod Autoscaler, trained on real traffic. This was accomplished via a state space model able to take into account resource consumption, performance values, and time of day. In addition, the reward function definition promotes Service-Level Agreement (SLA) compliance. We evaluate the proposed agent, comparing its performance in terms of average latency, CPU usage, memory usage, and loss percentage with respect to the baseline system. The experimental results show the benefits provided by the proposed agent, obtaining a service time within the SLA while limiting resource consumption and service loss
Gossip-based monitoring of virtualized resources in 5G networks
No full textThe network function virtualization (NFV) paradigm decouples service functions (SFs) from the physical equipment where they are executed, thus increasing the efficiency of resource utilization, and makes networks and services more scalable and flexible. However, in order to efficiently manage and chain SFs to build network service slices in 5G networks, it is necessary to localize (virtualized) SFs together with their current status, which includes their load, attached virtual links status, configuration parameters, etc. To this aim, we propose a monitoring architecture able to track the network location and the current status of distributed and virtualized SFs, by using agents responsible to monitor the status of co-located SFs, both physical and virtual ones. The monitoring agents exchange their information by means of a gossip protocol to increase the reliability of the process and to build a distributed service monitoring architecture. In this way, it is possible to keep service decisions as local as possible, limiting the interactions with a centralized orchestrator, and thus increasing network scalability. We show that the network overhead of the distributed monitoring process is negligible
Improving the efficiency of circuit-switched satellite networks by means of dynamic bandwidth allocation capabilities
No full textSpecial Issue on Molecular Communications in Action: A Tutorial on Implementation, Applications, Implications
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Autonomic control and personalization of a wireless access network
No full textAs ICT services are becoming more ubiquitous and mobile and access technologies grow to be more heterogeneous and
complex, we are witnessing the increasing importance of two related needs: (i) users need to be able to configure and personalize
their services with minimal effort; (ii) operators desire to engineer and manage their networks easily and efficiently,
limiting human agency as far as possible. We propose a possible solution to reach these goals. Our vision, developed in the
so-called Simplicity project, is based on a personalization device, which, together with a brokerage framework, offers transparent
service configuration and runtime adaptation, according to user preferences and computing/networking context
conditions. The capabilities of this framework can be exploited: (i) on the user side, to personalize services, to improve
the portability of services over heterogeneous terminals and devices, to adapt services to available networking and terminal
technologies; (ii) on the network side, to give operators more powerful tools to define new solutions for distributed, technology-
independent, self-organizing, autonomic networking systems. Such systems could be designed so as to be able to
react autonomously to changing contexts and environments.
In this paper, we first describe the main aspects of the Simplicity solution. We then want to show that our approach is
indeed viable. To prove this point, we present an application which exploits the capabilities of the Simplicity system: a
mechanism to drive mobile users towards the most appropriate point of access to the network, taking into account both
user preferences and network context. We use simulation to evaluate the performance of this procedure in a specific case
study, where the aim is to balance the load in an 802.11b access network scenario. The numerical results show the effectiveness
of the proposed procedure when compared to a legacy scenario and to another solution from literature.
To give ample proof of the feasibility of our solution, we also designed and implemented a real prototype. The prototype
enables not only the load to be balanced among different 802.11 access points, but also network and application services to be
differentiated as a function of user profiles and network load. The main aspects of this prototype are presented in this paper
A tariff model to charge IP services with guaranteed quality: effect of users' demand in a case study
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