Franco Davoli - Academia.edu (original) (raw)
Papers by Franco Davoli
25 th AIAA International …, 2007
Satellite communications represents a specialised area of telecommunications. While the developme... more Satellite communications represents a specialised area of telecommunications. While the development of satellite technology is relatively slow in comparison to wireless networks evolution, due to the need for high reliability, the services that satellites are able to offer should evolve as ...
IFAC Proceedings Volumes, Jun 1, 1985
Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, st... more Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, stochastic inputs, discrete control and state variables characterize the problem. An information structure of the decision makers is introduced which allows to solve the problem via a static team optimization.Then, on the basis of the existence of a common past information set, the structure of the optimal control strategy is studied and the possibility of using a receding-horizon control scheme is discussed. Finally,stationary infinite-horizon optimal decentralized solutions are sought. A possible procedure to find such solutions is discussed, which is simply based on standard Markov chains properties.
2018 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2018
Low latency and integration with edge computing facilities are two of the main enablers of the up... more Low latency and integration with edge computing facilities are two of the main enablers of the upcoming fifthgeneration mobile network. The geographical distribution of virtualized compute and storage resources (e.g., NFVI PoPs) allows to deploy application/service instances/components closer to mobile subscribers, and to provide much higher performance levels in terms of latency. These new degrees of freedom should be suitably managed in order to place and to migrate application components along with subscribers' move. Given the mass-scale of subscribers and the non-negligible overhead to move application components over resource-constrained edge facilities, this management should be performed in a highly scalable and effective way. In this respect, this paper presents the design of a comprehensive edge computing framework, including an orchestration algorithm, able to place and to move services in few milliseconds (<25 ms). The algorithm provides scalability levels able to support services instantiated on a per-user basis (i.e., personal services) also in the presence of complex network and service environments. The performance evaluation has been carried out by considering different service chains within diverse software live migration technologies.
2016 5th IEEE International Conference on Cloud Networking (Cloudnet), 2016
With the advent of network "softwarization", Network Functions Virtualization (NFV) is foreseen t... more With the advent of network "softwarization", Network Functions Virtualization (NFV) is foreseen to provide flexibility and programmability levels that would essentially help in coping with tomorrow's demands. However, energy efficiency and the resulting complexity of network/service management pose serious sustainability and scalability issues that may hinder NFV's advantages. This paper considers these aspects in the context of datacenter networks. We propose an energy-aware resource allocation scheme to manage virtual machines, dedicated to perform certain (virtualized) network functions, among a pool of energy-tunable physical resources (processors/cores). We use online measurements to periodically estimate some statistical features of the offered workloads by considering a fairly general renewal model that captures traffic burstiness and hardware operational settings. Then, resources are dynamically managed by jointly performing power scaling and in-server consolidation according to the actual workload variations. The average power consumption generated by this strategy is evaluated and compared with that of a classical bin-packing consolidation, over processors running always with the highest-performance configuration. Results show that the proposed approach can reduce the average power consumption of the datacenter by up to 10%, suggesting a considerable amount of annual savings.
2015 Proceedings of the Conference on Control and its Applications, 2015
We consider a networking infrastructure, upon which various "large" users (e.g., Telecom Operator... more We consider a networking infrastructure, upon which various "large" users (e.g., Telecom Operators, data centers, etc.) have multiple paths to deliver an aggregated entry flow to a certain destination. The flow of each user can be split among the different paths that traverse energy-aware routers. The routers adopt a specific strategy to minimize the power-delay product for each link, which gives rise to quadratic link (in the aggregated link flows) cost functions. We seek person-by-person satisfactory (p.b.p.s.) strategies stemming from a team optimal control problem of the users. The team optimization problem is defined among Decision Makers (DMs-one for each user) that try to minimize a common aggregate cost function of their routes, each one acting solely on the basis of the knowledge of the amount of flow to be routed. We derive piecewise linear p.b.p.s. solutions, which are characterized by a set of parameters. The latter can be found by solving a set of nonlinear fixed point equations.
Zenodo (CERN European Organization for Nuclear Research), Jun 12, 2023
The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in th... more The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in the digital transformation towards a new hyper-connected society. In order to satisfy the stringent demands of 5G-ready applications over the limited resources available at the edge, scaling mechanisms become crucial to guarantee the performance levels envisaged for 5G. Such mechanisms must be able to automatically perform according to the real-time user demands, the availability of computing resources and the state of Network Functions (NFs) and applications. In this context, this paper proposes a deep learning model, based on Artificial Neural Networks (ANNs), for the dynamic and automated orchestration of NFs. The novelty of this model is its independence from specific 5G NF implementations; this is due to the nature of the Key Performance Indicators (KPIs) used in this work, which are related to both execution environment (standard "black-box" KPIs) and standard 5G APIs ("whitebox" KPIs). Results obtained on the orchestration of a Session Management Function (SMF) reach an accuracy of 97~98% for the training and validation phases and above 95% for the deployed model, as well as higher overall accuracy by ~5% and computational resource savings with respect to a thresholdbased scheme.
Zenodo (CERN European Organization for Nuclear Research), Sep 6, 2022
Network softwarization has paved the way for 5G technologies, and a wide-range of (radically new)... more Network softwarization has paved the way for 5G technologies, and a wide-range of (radically new) verticals. As the telecommunications infrastructure evolves into a sort of distributed datacenter, multiple tenants such as vertical industries and network service providers share its aggregate pool of resources (e.g., networking, computing, etc.) in a layered "as-a-Service" approach exposed as slice abstractions. The challenge remains in the coordination of various stakeholders' assets in realizing end-to-end network slices and supporting the multi-site deployment and chaining of the micro-service components needed to implement cloud-native vertical applications (vApps). In this context, particular care must be taken to ensure that the required resources are identified, made available and managed in a way that satisfies the vApp requirements, allows for a fair share of resources and has a reasonable impact on the overall vApp deployment time. With these challenges in mind, this paper presents the Resource Selection Optimizer (RSO)-a softwareservice in the MATILDA Operations Support System (OSS), whose main goal is to select the most appropriate network and computing resources (according to some criterion) among a list of options provided by the Wide-area Infrastructure Manager (WIM). It consists of three submodules that respectively handle: (i) the aggregation of vApp components based on affinities, (ii) the forecasting of (micro-) datacenter resources utilization, (iii) and the multi-site placement of the (aggregated) vApp micro-service components. The RSO's performance is mainly evaluated in terms of the execution times of its submodules while varying their respective input parameters, and additionally, three selection policies are also compared. Experimental results aim to highlight the RSO behavior in both execution times and deployment costs, as well as the RSO interactions with other OSS submodules and network platform components, not only for multi-site vApp deployment but also for other network/services management operations.
IFAC Proceedings Volumes, Jun 1, 1985
Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, st... more Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, stochastic inputs, discrete control and state variables characterize the problem. An information structure of the decision makers is introduced which allows to solve the problem via a static team optimization.Then, on the basis of the existence of a common past information set, the structure of the optimal control strategy is studied and the possibility of using a receding-horizon control scheme is discussed. Finally,stationary infinite-horizon optimal decentralized solutions are sought. A possible procedure to find such solutions is discussed, which is simply based on standard Markov chains properties.
![Research paper thumbnail of Sensor network based localization for continuous tracking applications [invited paper]](https://attachments.academia-assets.com/109232099/thumbnails/1.jpg)
](The increasing interest in systems able to provide users with immersive services (e.g., domotics,... more The increasing interest in systems able to provide users with immersive services (e.g., domotics, context-aware applications, and immersive distance learning tools) has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs) can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes joined to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to track its moving nodes. Specifically, the nodes of the network are divided into three sets: the first set consists of anchor nodes that, according to the commands from the sink (the central node of the WSN), generate ultrasonic pulses. These pulses are received by the second set of (moving) nodes, which estimate the pulse time trip and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes, and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software, and protocol described in this paper has been deployed and tested, and some results are shown. Simulation results of the localization system are presented to show system scalability.
IEEE Network, 2018
The envisioned 5G ecosystem will be composed of heterogeneous networks based on different technol... more The envisioned 5G ecosystem will be composed of heterogeneous networks based on different technologies and communication means, including satellite communication networks. The latter can help increase the capabilities of terrestrial networks, especially in terms of higher coverage, reliability, and availability, contributing to the achievement of some of the 5G Key Performance Indicators (KPIs). Anyway, technological changes are not immediate. Many current satellite communication networks are based on proprietary hardware, which hinders the integration with future 5G terrestrial networks as well as the adoption of new protocols and algorithms. On the other hand, the two main paradigms that are emerging in the networking scenario-namely, Software Defined Networking (SDN) and Network Functions Virtualization (NFV)-can change this perspective. In this respect, this paper presents first an overview of the main research works in the field of SDN satellite networks, in order to understand the already proposed solutions. Then, some open challenges are described in the light of the network slicing concept by 5G virtualization, along with a possible roadmap including different network virtualization levels. The yet unsolved problems are evidenced toward the development and deployment of a complete integration of satellite components in the 5G ecosystem.
in this paper we consider a resource allocation problem for a satellite network, where variations... more in this paper we consider a resource allocation problem for a satellite network, where variations of fading conditions are added to those of traffic load. Since the capacity of the system is finite and divided in finite portions, the resource allocation problem reveals to be a discrete stochastic programming problem one, which is typically NP-Hard. We propose a new approach based on the minimization over a discrete constraint set using an estimation of the gradient, obtained through a "relaxed continuous extension" of the performance measure. The computation of the gradient estimation is based on the Infinitesimal Perturbation Analysis technique, applied on a Stochastic Fluid Model of the network. No closed forms of the performance measures, nor additional feedbacks concerning the state of the system and very mild assumptions on the probabilistic properties about the statistical processes involved in the problem are requested. Such optimization approach is compared with a dynamic programming algorithm that maintains a perfect knowledge about the state of the satellite network. Such comparison shows that the sensitivity estimation capability of the proposed algorithm allows to maintain the optimal resource allocation even in dynamic conditions and it is able to provide performance even better than the one reached by employing the dynamic programming approach.
In this paper, we focus on energy-aware devices able to reduce their energy requirements by adapt... more In this paper, we focus on energy-aware devices able to reduce their energy requirements by adapting their performance. We consider the device to be able to save energy through two main energy-aware primitives, namely, low power idle and power scaling. In such an environment, we propose a novel and original model for accurately representing how the joint usage of the previously cited primitives can impact on both energy consumption and network performance. As shown by the results achieved, the proposed model can be effectively applied in order to design and control energy-aware hardware of nextgeneration network devices. Index Terms-green networks; low power idle, power scaling.
PROCEEDINGS OF 6TH WORLD CONGRESS ON INTELLIGENT TRANSPORT SYSTEMS (ITS), HELD TORONTO, CANADA, NOVEMBER 8-12, 1999, 1999
An inter-vehicle network using short-range communications is considered, where the vehicles are c... more An inter-vehicle network using short-range communications is considered, where the vehicles are capable of temporarily establishing communication links with adjacent ones, by exploiting the space division multiplexing provided by directional antennas. Though the network topology is dynamically variable, the variations follow the traffic dynamics, which is orders of magnitude slower than that of the teletraffic; this fact makes it conceivable to consider finding the shortest routes within an ad-hoc network (e.g., within a platoon), which will then be used to convey important information on the traffic conditions in a multi-hop fashion. The paper defines some possible relevant metrics to be used in the calculation and presents and discusses numerical results on their application. (A*) For the covering abstract see ITRD E110327.
Zenodo (CERN European Organization for Nuclear Research), Jun 12, 2023
The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in th... more The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in the digital transformation towards a new hyper-connected society. In order to satisfy the stringent demands of 5G-ready applications over the limited resources available at the edge, scaling mechanisms become crucial to guarantee the performance levels envisaged for 5G. Such mechanisms must be able to automatically perform according to the real-time user demands, the availability of computing resources and the state of Network Functions (NFs) and applications. In this context, this paper proposes a deep learning model, based on Artificial Neural Networks (ANNs), for the dynamic and automated orchestration of NFs. The novelty of this model is its independence from specific 5G NF implementations; this is due to the nature of the Key Performance Indicators (KPIs) used in this work, which are related to both execution environment (standard "black-box" KPIs) and standard 5G APIs ("whitebox" KPIs). Results obtained on the orchestration of a Session Management Function (SMF) reach an accuracy of 97~98% for the training and validation phases and above 95% for the deployed model, as well as higher overall accuracy by ~5% and computational resource savings with respect to a thresholdbased scheme.
Research Square (Research Square), Oct 5, 2021
This article surveys the literature, over the period 2010-2020, on measurement of power consumpti... more This article surveys the literature, over the period 2010-2020, on measurement of power consumption and relevant power models of virtual entities as they apply to the telco cloud. Hardware power meters are incapable of measuring power consumption of individual virtual entities co-hosted on a physical machine. Thus, software power meters are inevitable, yet their development is difficult. Indeed, there is no direct approach to measurement and, therefore, modeling through proxies of power consumption must be used. In this survey, we present trends, fallacies and pitfalls. Notably, we identify limitations of the widely-used linear models and the progression towards Artificial Intelligence / Machine Learning techniques as a means of dealing with the seven major dimensions of variability: workload type; computer virtualization agents; system architecture and resources; concurrent, co-hosted virtualized entities; approaches towards attribution of power consumption to virtual entities; frequency; and temperature.
ABSTRACT In the field of decentralized stochastic (team) control, the search for stationary strat... more ABSTRACT In the field of decentralized stochastic (team) control, the search for stationary strategies over an infinite time horizon has always represented a challenging and still unsolved problem. For this reason, one is led to consider the application of a receding horizon control scheme. In this case, one must solve at each time instant an optimization problem with constant structure, conditioned to what has taken place in the past. More specifically, the information structure of the team which will be considered in the paper is characterized by two important properties: i) partial nestedness; ii) existence of a common past information set. With these hypotheses, and with reference to a LQG setting of the problem, it has been proven that the receding horizon control scheme yields a linear strategy of constant structure, but with time-varying parameters. This fact is due to the dependence of the solution of the optimization problem from a set of past strategies. The purpose of the paper is to determine necessary conditions for the existence of a decentralized optimal receding horizon stationary strategy.
![Research paper thumbnail of Sensor network based localization for continuous tracking applications [invited paper]](https://attachments.academia-assets.com/106557420/thumbnails/1.jpg)
](The increasing interest in systems able to provide users immersive services (e.g. domotics, conte... more The increasing interest in systems able to provide users immersive services (e.g. domotics, context-aware applications, immersive distance learning tools) has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs) can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes jointed to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to tracking its moving nodes. Specifically, the nodes of the network are divided in three sets: the first set consists of anchor nodes that, accordingly to the commands from the sink (the central node of WSN), generate ultrasonic pulses. These ones are received by the second set of (moving) nodes, which estimate the pulse-triptime and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software and protocol described in this paper has been deployed and tested, and some results are shown.
25 th AIAA International …, 2007
Satellite communications represents a specialised area of telecommunications. While the developme... more Satellite communications represents a specialised area of telecommunications. While the development of satellite technology is relatively slow in comparison to wireless networks evolution, due to the need for high reliability, the services that satellites are able to offer should evolve as ...
IFAC Proceedings Volumes, Jun 1, 1985
Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, st... more Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, stochastic inputs, discrete control and state variables characterize the problem. An information structure of the decision makers is introduced which allows to solve the problem via a static team optimization.Then, on the basis of the existence of a common past information set, the structure of the optimal control strategy is studied and the possibility of using a receding-horizon control scheme is discussed. Finally,stationary infinite-horizon optimal decentralized solutions are sought. A possible procedure to find such solutions is discussed, which is simply based on standard Markov chains properties.
2018 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2018
Low latency and integration with edge computing facilities are two of the main enablers of the up... more Low latency and integration with edge computing facilities are two of the main enablers of the upcoming fifthgeneration mobile network. The geographical distribution of virtualized compute and storage resources (e.g., NFVI PoPs) allows to deploy application/service instances/components closer to mobile subscribers, and to provide much higher performance levels in terms of latency. These new degrees of freedom should be suitably managed in order to place and to migrate application components along with subscribers' move. Given the mass-scale of subscribers and the non-negligible overhead to move application components over resource-constrained edge facilities, this management should be performed in a highly scalable and effective way. In this respect, this paper presents the design of a comprehensive edge computing framework, including an orchestration algorithm, able to place and to move services in few milliseconds (<25 ms). The algorithm provides scalability levels able to support services instantiated on a per-user basis (i.e., personal services) also in the presence of complex network and service environments. The performance evaluation has been carried out by considering different service chains within diverse software live migration technologies.
2016 5th IEEE International Conference on Cloud Networking (Cloudnet), 2016
With the advent of network "softwarization", Network Functions Virtualization (NFV) is foreseen t... more With the advent of network "softwarization", Network Functions Virtualization (NFV) is foreseen to provide flexibility and programmability levels that would essentially help in coping with tomorrow's demands. However, energy efficiency and the resulting complexity of network/service management pose serious sustainability and scalability issues that may hinder NFV's advantages. This paper considers these aspects in the context of datacenter networks. We propose an energy-aware resource allocation scheme to manage virtual machines, dedicated to perform certain (virtualized) network functions, among a pool of energy-tunable physical resources (processors/cores). We use online measurements to periodically estimate some statistical features of the offered workloads by considering a fairly general renewal model that captures traffic burstiness and hardware operational settings. Then, resources are dynamically managed by jointly performing power scaling and in-server consolidation according to the actual workload variations. The average power consumption generated by this strategy is evaluated and compared with that of a classical bin-packing consolidation, over processors running always with the highest-performance configuration. Results show that the proposed approach can reduce the average power consumption of the datacenter by up to 10%, suggesting a considerable amount of annual savings.
2015 Proceedings of the Conference on Control and its Applications, 2015
We consider a networking infrastructure, upon which various "large" users (e.g., Telecom Operator... more We consider a networking infrastructure, upon which various "large" users (e.g., Telecom Operators, data centers, etc.) have multiple paths to deliver an aggregated entry flow to a certain destination. The flow of each user can be split among the different paths that traverse energy-aware routers. The routers adopt a specific strategy to minimize the power-delay product for each link, which gives rise to quadratic link (in the aggregated link flows) cost functions. We seek person-by-person satisfactory (p.b.p.s.) strategies stemming from a team optimal control problem of the users. The team optimization problem is defined among Decision Makers (DMs-one for each user) that try to minimize a common aggregate cost function of their routes, each one acting solely on the basis of the knowledge of the amount of flow to be routed. We derive piecewise linear p.b.p.s. solutions, which are characterized by a set of parameters. The latter can be found by solving a set of nonlinear fixed point equations.
Zenodo (CERN European Organization for Nuclear Research), Jun 12, 2023
The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in th... more The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in the digital transformation towards a new hyper-connected society. In order to satisfy the stringent demands of 5G-ready applications over the limited resources available at the edge, scaling mechanisms become crucial to guarantee the performance levels envisaged for 5G. Such mechanisms must be able to automatically perform according to the real-time user demands, the availability of computing resources and the state of Network Functions (NFs) and applications. In this context, this paper proposes a deep learning model, based on Artificial Neural Networks (ANNs), for the dynamic and automated orchestration of NFs. The novelty of this model is its independence from specific 5G NF implementations; this is due to the nature of the Key Performance Indicators (KPIs) used in this work, which are related to both execution environment (standard "black-box" KPIs) and standard 5G APIs ("whitebox" KPIs). Results obtained on the orchestration of a Session Management Function (SMF) reach an accuracy of 97~98% for the training and validation phases and above 95% for the deployed model, as well as higher overall accuracy by ~5% and computational resource savings with respect to a thresholdbased scheme.
Zenodo (CERN European Organization for Nuclear Research), Sep 6, 2022
Network softwarization has paved the way for 5G technologies, and a wide-range of (radically new)... more Network softwarization has paved the way for 5G technologies, and a wide-range of (radically new) verticals. As the telecommunications infrastructure evolves into a sort of distributed datacenter, multiple tenants such as vertical industries and network service providers share its aggregate pool of resources (e.g., networking, computing, etc.) in a layered "as-a-Service" approach exposed as slice abstractions. The challenge remains in the coordination of various stakeholders' assets in realizing end-to-end network slices and supporting the multi-site deployment and chaining of the micro-service components needed to implement cloud-native vertical applications (vApps). In this context, particular care must be taken to ensure that the required resources are identified, made available and managed in a way that satisfies the vApp requirements, allows for a fair share of resources and has a reasonable impact on the overall vApp deployment time. With these challenges in mind, this paper presents the Resource Selection Optimizer (RSO)-a softwareservice in the MATILDA Operations Support System (OSS), whose main goal is to select the most appropriate network and computing resources (according to some criterion) among a list of options provided by the Wide-area Infrastructure Manager (WIM). It consists of three submodules that respectively handle: (i) the aggregation of vApp components based on affinities, (ii) the forecasting of (micro-) datacenter resources utilization, (iii) and the multi-site placement of the (aggregated) vApp micro-service components. The RSO's performance is mainly evaluated in terms of the execution times of its submodules while varying their respective input parameters, and additionally, three selection policies are also compared. Experimental results aim to highlight the RSO behavior in both execution times and deployment costs, as well as the RSO interactions with other OSS submodules and network platform components, not only for multi-site vApp deployment but also for other network/services management operations.
IFAC Proceedings Volumes, Jun 1, 1985
Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, st... more Decentralized dynamic routing in networks is considered in the paper. Finite buffers at nodes, stochastic inputs, discrete control and state variables characterize the problem. An information structure of the decision makers is introduced which allows to solve the problem via a static team optimization.Then, on the basis of the existence of a common past information set, the structure of the optimal control strategy is studied and the possibility of using a receding-horizon control scheme is discussed. Finally,stationary infinite-horizon optimal decentralized solutions are sought. A possible procedure to find such solutions is discussed, which is simply based on standard Markov chains properties.
The increasing interest in systems able to provide users with immersive services (e.g., domotics,... more The increasing interest in systems able to provide users with immersive services (e.g., domotics, context-aware applications, and immersive distance learning tools) has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs) can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes joined to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to track its moving nodes. Specifically, the nodes of the network are divided into three sets: the first set consists of anchor nodes that, according to the commands from the sink (the central node of the WSN), generate ultrasonic pulses. These pulses are received by the second set of (moving) nodes, which estimate the pulse time trip and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes, and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software, and protocol described in this paper has been deployed and tested, and some results are shown. Simulation results of the localization system are presented to show system scalability.
IEEE Network, 2018
The envisioned 5G ecosystem will be composed of heterogeneous networks based on different technol... more The envisioned 5G ecosystem will be composed of heterogeneous networks based on different technologies and communication means, including satellite communication networks. The latter can help increase the capabilities of terrestrial networks, especially in terms of higher coverage, reliability, and availability, contributing to the achievement of some of the 5G Key Performance Indicators (KPIs). Anyway, technological changes are not immediate. Many current satellite communication networks are based on proprietary hardware, which hinders the integration with future 5G terrestrial networks as well as the adoption of new protocols and algorithms. On the other hand, the two main paradigms that are emerging in the networking scenario-namely, Software Defined Networking (SDN) and Network Functions Virtualization (NFV)-can change this perspective. In this respect, this paper presents first an overview of the main research works in the field of SDN satellite networks, in order to understand the already proposed solutions. Then, some open challenges are described in the light of the network slicing concept by 5G virtualization, along with a possible roadmap including different network virtualization levels. The yet unsolved problems are evidenced toward the development and deployment of a complete integration of satellite components in the 5G ecosystem.
in this paper we consider a resource allocation problem for a satellite network, where variations... more in this paper we consider a resource allocation problem for a satellite network, where variations of fading conditions are added to those of traffic load. Since the capacity of the system is finite and divided in finite portions, the resource allocation problem reveals to be a discrete stochastic programming problem one, which is typically NP-Hard. We propose a new approach based on the minimization over a discrete constraint set using an estimation of the gradient, obtained through a "relaxed continuous extension" of the performance measure. The computation of the gradient estimation is based on the Infinitesimal Perturbation Analysis technique, applied on a Stochastic Fluid Model of the network. No closed forms of the performance measures, nor additional feedbacks concerning the state of the system and very mild assumptions on the probabilistic properties about the statistical processes involved in the problem are requested. Such optimization approach is compared with a dynamic programming algorithm that maintains a perfect knowledge about the state of the satellite network. Such comparison shows that the sensitivity estimation capability of the proposed algorithm allows to maintain the optimal resource allocation even in dynamic conditions and it is able to provide performance even better than the one reached by employing the dynamic programming approach.
In this paper, we focus on energy-aware devices able to reduce their energy requirements by adapt... more In this paper, we focus on energy-aware devices able to reduce their energy requirements by adapting their performance. We consider the device to be able to save energy through two main energy-aware primitives, namely, low power idle and power scaling. In such an environment, we propose a novel and original model for accurately representing how the joint usage of the previously cited primitives can impact on both energy consumption and network performance. As shown by the results achieved, the proposed model can be effectively applied in order to design and control energy-aware hardware of nextgeneration network devices. Index Terms-green networks; low power idle, power scaling.
PROCEEDINGS OF 6TH WORLD CONGRESS ON INTELLIGENT TRANSPORT SYSTEMS (ITS), HELD TORONTO, CANADA, NOVEMBER 8-12, 1999, 1999
An inter-vehicle network using short-range communications is considered, where the vehicles are c... more An inter-vehicle network using short-range communications is considered, where the vehicles are capable of temporarily establishing communication links with adjacent ones, by exploiting the space division multiplexing provided by directional antennas. Though the network topology is dynamically variable, the variations follow the traffic dynamics, which is orders of magnitude slower than that of the teletraffic; this fact makes it conceivable to consider finding the shortest routes within an ad-hoc network (e.g., within a platoon), which will then be used to convey important information on the traffic conditions in a multi-hop fashion. The paper defines some possible relevant metrics to be used in the calculation and presents and discusses numerical results on their application. (A*) For the covering abstract see ITRD E110327.
Zenodo (CERN European Organization for Nuclear Research), Jun 12, 2023
The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in th... more The diffusion of the Fifth-Generation (5G) of mobile radio networks will be the main driver in the digital transformation towards a new hyper-connected society. In order to satisfy the stringent demands of 5G-ready applications over the limited resources available at the edge, scaling mechanisms become crucial to guarantee the performance levels envisaged for 5G. Such mechanisms must be able to automatically perform according to the real-time user demands, the availability of computing resources and the state of Network Functions (NFs) and applications. In this context, this paper proposes a deep learning model, based on Artificial Neural Networks (ANNs), for the dynamic and automated orchestration of NFs. The novelty of this model is its independence from specific 5G NF implementations; this is due to the nature of the Key Performance Indicators (KPIs) used in this work, which are related to both execution environment (standard "black-box" KPIs) and standard 5G APIs ("whitebox" KPIs). Results obtained on the orchestration of a Session Management Function (SMF) reach an accuracy of 97~98% for the training and validation phases and above 95% for the deployed model, as well as higher overall accuracy by ~5% and computational resource savings with respect to a thresholdbased scheme.
Research Square (Research Square), Oct 5, 2021
This article surveys the literature, over the period 2010-2020, on measurement of power consumpti... more This article surveys the literature, over the period 2010-2020, on measurement of power consumption and relevant power models of virtual entities as they apply to the telco cloud. Hardware power meters are incapable of measuring power consumption of individual virtual entities co-hosted on a physical machine. Thus, software power meters are inevitable, yet their development is difficult. Indeed, there is no direct approach to measurement and, therefore, modeling through proxies of power consumption must be used. In this survey, we present trends, fallacies and pitfalls. Notably, we identify limitations of the widely-used linear models and the progression towards Artificial Intelligence / Machine Learning techniques as a means of dealing with the seven major dimensions of variability: workload type; computer virtualization agents; system architecture and resources; concurrent, co-hosted virtualized entities; approaches towards attribution of power consumption to virtual entities; frequency; and temperature.
ABSTRACT In the field of decentralized stochastic (team) control, the search for stationary strat... more ABSTRACT In the field of decentralized stochastic (team) control, the search for stationary strategies over an infinite time horizon has always represented a challenging and still unsolved problem. For this reason, one is led to consider the application of a receding horizon control scheme. In this case, one must solve at each time instant an optimization problem with constant structure, conditioned to what has taken place in the past. More specifically, the information structure of the team which will be considered in the paper is characterized by two important properties: i) partial nestedness; ii) existence of a common past information set. With these hypotheses, and with reference to a LQG setting of the problem, it has been proven that the receding horizon control scheme yields a linear strategy of constant structure, but with time-varying parameters. This fact is due to the dependence of the solution of the optimization problem from a set of past strategies. The purpose of the paper is to determine necessary conditions for the existence of a decentralized optimal receding horizon stationary strategy.
The increasing interest in systems able to provide users immersive services (e.g. domotics, conte... more The increasing interest in systems able to provide users immersive services (e.g. domotics, context-aware applications, immersive distance learning tools) has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs) can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes jointed to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to tracking its moving nodes. Specifically, the nodes of the network are divided in three sets: the first set consists of anchor nodes that, accordingly to the commands from the sink (the central node of WSN), generate ultrasonic pulses. These ones are received by the second set of (moving) nodes, which estimate the pulse-triptime and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software and protocol described in this paper has been deployed and tested, and some results are shown.