The Edge-Cloud Continuum (ECC) represents an emerging distributed, multi-tier computing infrastructure that integrates the capabilities of cloud and edge computing to offer a versatile environment capable of hosting applications with specific requirements, such as low latency and high computing capacity, which neither cloud nor edge computing can individually guarantee. However, ensuring Quality of Service (QoS) across the ECC remains a complex task, particularly with regard to networking parameters, due to the limited controllability and predictability of public network segments. This work introduces a QoS-aware mechanism for constructing logical overlay networks that aim to ensure required network performance with high probability, despite the inherent variability of public network environments. The proposed approach builds the overlay by organizing nodes into layers, each defined by a target level of network Qos (e.g., latency). The construction process consists of two key stages: first, collecting network metrics among the available nodes, and second, assigning nodes to layers based on the observed metrics. To validate the proposed approach, this work presents a Monte Carlo simulation campaign that assesses its effectiveness in constructing overlay networks capable of meeting, with high probability, the required QoS levels.

The term Edge Cloud Continuum (ECC) identifies an emerging distributed, multi-tier computing infrastructure that combines the cloud and edge computing capabilities to offer a versatile environment where it is possible to deploy and manage a new type of applications - typically related to mobile and IoT fields - having specific requirements such as low-latency, high computing capabilities - that neither cloud nor edge can offer singularly. This capability comes from the combination and integration of multiple heterogeneous technologies, typically owned and offered by independent and autonomous resource and service providers. In such a scenario, the processes of deployment and management of an application are challenging issues that require the ability to coordinate multiple controllers to address fluctuations in service and resource availability, network latency, and workload demands. In this paper, the authors propose an SLA-driven, AI-based QoS Manager that, abstracting the heterogeneity of the resources and their providers, influences the performance of a distributed application by inferring the proper hardware configuration for each one of its components.

We address the problem of a Network Operator (NO) owning limited resources at the network edge. The NO wishes to enable advanced services, by virtualizing and allocating such resources among multiple tenants, i.e., third-party Service Providers, co-existing at the edge, with different Quality of Service (QoS) constraints. The NO applies a resource allocation policy with the objective of minimizing energy consumption via switching off non-used resources while guaranteeing tenants QoS requirements. We propose a resource allocation policy based on Markov Decision Processes (MDP). In simulation we show that our policy is able to reduce energy consumption, by turning off unused resources, while meeting heterogeneous SP requirements. Our code is available as open source.

DevOps methodologies reduce the gap between Developers and Operations teams, enabling automation, integration, monitoring, and team collaboration by exploiting continuous integration and deployment and providing high-scale performance for the cloud software delivery life-cycle. AIOps seems to represent the future of IT automation by leveraging DevOps methodologies, Big Data, and AI-enabled strategies for the smart orchestration of Cloud-native applications. Based on the Ananke monitoring model, this paper investigates design issues and strategies required to enable integration between clusters and applications managed by Ananke, and their metrics stored in the Prometheus Monitoring system. Some classic algorithms for anomaly detection and forecasting of time series have been introduced in the proposed AIOps Prometheus Framework for the system analysis and orchestration of applications. Finally, we propose, as a case study, an auto-scaling strategy based on the prediction of traffic peeks for a web application using the Facebook Prophet model.

Under the paradigm of Edge Computing (EC), a Network Operator (NO) deploys computational resources at the network edge and let third-party Service Providers (SPs) run on top of them, as tenants. Besides the clear advantages for SPs and final users thanks to the vicinity of computation nodes, a NO aims to allocate edge resources in order to increase its own utility, including bandwidth saving, operational cost reduction, QoE for its users, etc. However, while the number of third-party services competing for edge resources is expected to dramatically grow, the resources deployed cannot increase accordingly, due to physical limitations. Therefore, smart strategies are needed to fully exploit the potential of EC, despite its constrains. To this aim, we propose to leverage service adaptability, a dimension that has mainly been neglected so far: each service can adapt to the amount of resources that the NO has allocated to it, balancing the fraction of service computation performed at the edge and relying on remote servers, e.g., in the Cloud, for the rest. We propose EdgeMORE, a resource allocation strategy in which SPs express their capabilities to adapt to different resource constraints, by declaring the different configurations under which they are able to run, specifying the resources needed and the utility provided to the NO. The NO then chooses the most convenient option per each SP, in order to maximize the total utility. We formalize EdgeMORE as a Integer Linear Program. We show via simulation that EdgeMORE greatly improves EC utility with respect to the standard where no multiple options for running services are allowed.

Micro-service architecture enables smarter management of applications life-cycle. However, the increasing of the number of components also increases complexity, especially on operations like migration and horizontal scaling. While operations, in monolithic systems, involve only one component, operations in micro-services based applications can get complex and should involve parameters and properties like connection throughput, resources usage, robustness or consistency and reliability. To perform this kind of operations and optimization strategies in micro-services applications, we propose Ananke, a framework consisting of a time-varying multi-layer graph-based model and architecture to profile micro-services and their interactions in a platform-as-a-service environment. The aim of Ananke is to provide support and facilities for optimization strategies that a Cloud Provider can exploit to guarantee quality of service and service-level agreements better.

Mobility on Demand (MoD) services are revolutionizing the way people move in cities around the world and are often considered a convenient alternative to public transit. MoD is usually intended as a door-to-door service. However, there has been recent interest toward consolidating, e.g., aggregating, the travel demand by limiting the number of admitted stop locations. This implies users have to walk from/to their intended origin/destination.The contribution of this paper is a systematic study the impact of consolidation on the operator cost and on user QoS. We introduce a MoD system where pick-ups and drop-offs can only occur in a limited subset of admitted stop locations. The density of such locations is a system parameter: the less the density, the more the user demand is consolidated. We show that, by decreasing stop density, we can increase system capacity (number of passengers we are able to serve). On the contrary, increasing it, we can improve QoS. The system is tested in AMoDSim, an open-source simulator.This work is a first step toward flexible mobility services that are able to autonomously re-conFigure themselves, favoring capacity or QoS, depending on the amount of travel demand coming from users. In other words, the services we envisage in this work shift their operational mode to any intermediate point in the range from a taxi-like door-to-door service to a bus-like service, with few served stops and more passengers on-board.

In recent years, the widespread use of container technologies has significantly altered the interactions between cloud service providers and their customers when developing and offering services. The shift away from Virtual Private Server scenarios in Infrastructure-as-a-Service environments requires drastically changing the deployment strategies adopted by service providers. This also opens many questions on what information must be supplied by customers and how to improve the performance of user applications, especially in the case of communication-intensive applications. In this work, the authors propose the adoption of a new framework for Mesos Clusters that aims to improve the deployment strategies of communication intensive applications. Coope4M is based on the partitioning of the user application graph via the Isolation Index parameter obtained through user-knowledge on the degree of the communication between its components.

In the last years, several projects are emerged with the aim to addressing the challenge of providing solutions for deployment, monitoring, adaptation, and management of clouds belonging to different enterprises/organisations. In such scenarios the network connectivity is one of the key factors. SDN technologies represent a good solution to face this challenge. Separating the control plane from the data plan, they can supply the cloud provider with the opportunity to specify on-the fly both the network topologies and routing schemes, guaranteeing, at same time, specific level of isolation. ASSDN, the framework presented in this paper, represents the first attempt to face this kind of issue. Driving the SDN controllers of all the Network Providers involved, it allows to create, handle and monitor virtual networks that are able to span across several heterogeneous cloud environments so to guarantee specific level of QoS.

Today, the Infrastructure as a Service (IaaS) cloud environments represent a market share on which many big economical players (Amazon, Microsoft, Rack space) are converging. The hetereogenity and the degree of customization of Cloud features and funcionalities supplied, the different pricing model adopted, the different QoS strategies proposed to the customer make this market very fragmented. Within this context, the workflows represent a common models to describe both business and scientific enterprise application. This paper proposes a novel modular workflow management system called IWoM (Iaas Workflow Manager) that can work with different (public or private) IaaS platforms. Through IWoM a Cloud provider can offer to its customers a simple way to compose a workflow, associate to it with a set of QoS parameters, automatically deploy it on a IaaS middleware and handle all the operations related with the QoS provisioning. To probe the benefits of IWoM, authors analyse the deployment of workflows on the PRISMA platform, a cloud infrastructure oriented to the the provision, control and monitoring of business process belonging to EU public administrations.

The use of virtualization technologies and the introduction of multi-core processors have strongly influenced the way of designing and developing software systems. Thus controlling and effectively managing them is became a fundamental issue, especially in distributed scenarios, as Clouds or Grids, providing QoS-assured services on demand. In this work, the authors propose the adoption of a management layer composed by several, parallel and cooperating sub managers (acting as independent controllers) handling, each one, different aspects (i.e., concerns or topics) of the underlying control system. The separation of concerns, together with the parallelism of managers and with their fractal organization, are fundamental for improving the performance of the whole management system.

The optimal allocation of Communication-Intensive Applications is a well-know complex issue in Clouds. This kind of applications, due to the strong impact of communications on their performance, requires not only that their tasks are allocated on resources able to satisfy their computational requirements but also that the distance among these resources, in terms of communication delay or latency, is the smallest. The allocation strategies currently used, based on a static vision of resources' status, are not suitable for managing effectively the peculiarities of these applications. In this work we propose an innovative allocation strategy that, using information about the sequence of their internal interactions, improves the deployment of Communication-Intensive Applications on available resources. In particular, this strategy allows reducing the number of resources needed for executing each application and, very important, it allows reducing the influence of each application over the performance of the other ones running on the same cloud.

Abstract This paper proposes a software architecture based onmobile agentsfor distributed process control applications. A set of agents is employed to handle, in a single manufacturing cell, automatic assignment of control tasks to controllers, monitoring of cell functionalities and dynamic cell reconfiguration. The agents operate in a two‐layered structure: at the highest level, theplanning agentsanalyse the inputs of the system designer and automatically create thefield agents, which operate at the lowest level and embed the control tasks to be executed. Field agents, which are mobile, are able to reach autonomously the controllers of the cell, in order to perform the control activity there. Exploiting the mobility enables a field agent to change its running device when the variation of the design parameters or a system fault requires a new task distribution. Aload‐balancingalgorithm is introduced, with the objective of assigning each field agent to a controller of the manufacturing cell in order to fairly distribute the computation load. The algorithm uses abranch‐and‐boundtechnique to explore all possible solutions and applies two heuristics to throw away non‐feasible solutions and select the best branch to analyse. The algorithm is designed to run on‐line in order to allow a fast task redistribution when a fault condition occurs in the process control environment. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract This paper presents a peer‐to‐peer (P2P) approach for the management, in a computational Grid, of those resources that are featured by numerical quantity and thus characterized by a coefficient of utilization, such as percentage of CPU time, disk space, memory space, etc. The proposed approach exploits spatial computing concepts and models a Grid by means of a flat P2P architecture consisting of nodes connected by an overlay network; such a network topology, together with the quantity of resource available in each node, forms a three‐dimensional surface, where valleys correspond to nodes with a large quantity of available resource. In this scenario, this paper proposes an algorithm for resource discovery that is based on navigating such a surface, in search of the deepest valley (global minimum, that is, the best node). The algorithm, which aims at fairly distributing among nodes the quantity of leased resource, is based on some heuristics that mimic the laws of kinematics. Experimental results show the effectiveness of the algorithm. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract The dynamics of resource request rates in a Grid system can be wide ranging, to the point that request peaks for a single resource can be difficult to handle and end up greatly increasing the response time. Once a request has been submitted by a client, this has to cope with the potential overload arising. However, it is impractical to cure overload once it takes place by negotiating a different service or finding an equivalent resource, since the client would then bear the delay due to negotiation and re‐submission. Instead, in order to effectively exploit Grid resources, it is crucial that applications perform reservation of resources before using them. Reservation allows a management system to consider application needs in advance and take suitable action to improve resource availability. In particular, this enables additional resources to be secured beforehand in the background when appropriate to avoid a potential overload, rather than paying the involved costs when overload arises. This paper proposes a software architecture that integrates applications with Globus services to conveniently handle resource reservation and allocation. Within the architecture, the computational reflection technology transparently connects applications with components that take care of advance reservation, as they dynamically sense the applications' resource needs. This dynamic information augments static knowledge gathered offline from static program code analysis. Copyright © 2005 John Wiley & Sons, Ltd.

Abstract Agent Communication Contexts (ACCs) are virtual environments where agents may live and interact. In this way, as in a human society, interactions may be subject to conventions and laws depending on the context where they occur. For this to be possible, an ACC should embed the communication laws relevant to the intended class of agent applications and enforce them, as interactions among agents take place. Although context is a communication aspect relevant for all the agents of an application, its modelling should be, in principle, an orthogonal concern with respect to the design of the activities of each agent. Consistently with this view, this work advocates the separate development of, respectively, agent behaviour, and the interaction aspects constituting the context. The latter is first abstractly specified as a set of communication laws, then automatically implemented by a tool that generates the necessary ACC management and checking code from the specification. The appropriate portions of this code should be activated whenever an interaction between agents takes place, so as to ensure that (i) the constraints specified by the laws are respected by the interaction, and (ii) the actions some of the laws require are carried out before the interaction actually occurs. Moreover, this work proposes an infrastructure whereby ACC code is triggered at runtime, whenever agents interact with each other. No source code modification or recompilation is required for this. All is seamlessly accomplished by means of computational reflection, which transparently changes the meaning of the communication primitives normally used by agent programmers. Copyright © 2005 John Wiley & Sons, Ltd.

The capability to evolve an application dynamically consists in activating new portions of code while the application runs. This can be considered particularly useful when applications need to adapt to fluctuating conditions of their environment. This paper aims at providing a general infrastructure that allows object-oriented applications to dynamically modify the way they work, without stopping. This infrastructure has a twofold objective: deciding which application activities best fit the current conditions, e.g. to exploit the increased availability or loss of resources; taking into account that new classes could have been developed and force the application to incorporate them while it runs. Computational reflection is used as a means to connect the proposed infrastructure with applications, for its interception mechanism provides the ability to intervene into the application operations in order to seamlessly introduce the desired changes.

Assistant agents are software systems that help users during activities by carrying out some task as a reaction to events in their environment. This paper proposes a software architecture that allows assistant agents to extend applications by autonomously giving users suggestions and activating useful application functionalities. The connection between applications and assistant agents is realised by means of computational reflection, which allows applications to evolve essentially without changes to their source code. The proposed approach is general in that it does not depend on a specific application nor platform. Its application is demonstrated by two examples of reflective assistant agents for a Web browser supporting data presentation and e-shopping respectively.

Developing distributed software systems is a complex activity that involves facing not only the problems of a specific application, but also those typical of distribution. Computational reflection supplies a means to handle different concerns with distinct components and a framework in which the latter can interact smoothly. We propose a reflective software architecture that encapsulates distribution concerns within components that are separated from and independent of those addressing functional concerns. The proposed architecture achieves a thorough management of distribution and in particular provides a means to dynamically adapt allocation policies to the characteristics of application objects, available hosts and changes of the distributed environment. The proposed approach is helpful for achieving the incremental development of easy to evolve software systems. In particular, we discuss the benefits of applying it to existing Web and e-commerce applications.

Finding the position of a mobile agent in a wide distributed system still represents an open research issue. The paper proposes a naming scheme and a location protocol of general validity for mobile agents able to effectively meet all the typical requirements of mobile agent environments and, thus, easy to integrate into different platforms. The paper identifies the main characteristics which an agent naming scheme and a location protocol of general validity should have, and suggests some properties and parameters to be taken into account to evaluate the effectiveness of naming schemes and location protocols. Then, we propose a "human readable" agent naming scheme based on the distributed environment outlined in MASIF, and a suitable location finding protocol called the Search-By-Path-Chase. Both of them are compared with some of the solutions already provided, using the properties and the parameters suggested. The performances are finally evaluated by means of a set of measurements.

The problem of finding the position of a mobile agent in a wide distributed system still represents an open research area. In fact, although today several mobile agent platforms have been developed, each of them implements an ad hoc naming and location policy, suitably studied to address the specific requirements deriving from the design choices made. What is really needed is a naming and location scheme of general validity, able to effectively meet all the typical requirements of mobile agent environments and thus easy to integrate into different platforms. A first contribution of the paper is the identification of the main requirements which an agent naming scheme of general validity should meet. Then, some properties are suggested to be taken into account, in order to make a qualitative naming scheme classification. The second contribution of the paper is the proposal of a "human readable" agent naming scheme, based on the distributed environment outlined in MASIF, the standardization OMG proposal for mobile agent systems. In addition, two location protocols suitable for the proposed naming scheme are presented, which are particularly appropriate for Internet/intranet environments.

The aim of this paper is to discuss the problems relating to communication in distributed process control, highlighting the limits of traditional centralized communication systems based on point-to-point connections. The paper shows the real advantages that can be obtained by using a distributed common-bus communication system in time-critical process control applications, highlighting its impact on the architecture of control systems from the point of view of both hardware and software. Particular reference is made to the International Electrotechnical Commission/Instrument Society of America (IEC/ISA) communication system which is close to becoming an international standard. In particular, the solution based on the use of the distributed common-bus communication protocol is applied to the control of an orange-picking robot, which had previously been implemented in a traditional way using point-to-point communications. The choice of a case study referring to a robot control system seems an appropriate benchmark for the real potential of the fieldbus because the processes involved in a robot control system have highly critical time constraints which may stress the fieldbus communication system. The paper presents a qualitative analysis of the advantages that can be obtained by introducing the fieldbus into the orange picking robot control system. The analysis gives a detailed illustration of the hardware and software modification needed to replace the traditional point-to-point control systems of the orange picking robot with the fieldbus. Then an evaluation of the performance of fieldbus system is provided. The evaluation is made by modeling and simulating the distributed communication system with transition timed Petri nets (TTPNs). The results obtained in the study as a whole confirm the authors' conviction that, by careful analysis, it is possible and advantageous even in difficult cases to replace classical centralized point-to-point control systems with distributed systems based on use of the fieldbus.

The paper deals with the problem of scheduling the transmission of periodic processes in a distributed FieldBus system, defining the conditions guaranteeing correct transmission. The scheduling of periodic processes fixes the transmission times for each process in a table, whose length is equal to the Least Common Multiple (LCM) of all the periods. This involves great memorization problems when some periods are relatively prime. The authors identify the theoretical conditions which allow the length of the scheduling table to be drastically reduced, but still guarantee correct transmission. On the basis of the theoretical conditions given, the authors present a pre-run-time scheduling algorithm which determines a transmission sequence for each producing process within the desired scheduling interval. An online scheduling algorithm is also proposed to schedule new transmission requests which are made while the system is functioning. The reduction in the schedule length may increase the number of transmissions, thus reducing the effective bandwidth and increasing the communication overload. In order to make as complete an analysis as possible of the scheduling solution, the authors also present an analysis of both the computational complexity of the algorithms proposed and the communication overload introduced.>

The authors deal with the problem of the information exchange between processes in extended fieldbus systems. As is known, although most of the traffic in these systems is within a single bus, there is always a certain amount transiting from one fieldbus to another, often covering a certain distance. There is therefore the problem of finding ways to interconnect the various fieldbuses in such a way as to meet the time constraints imposed by the applications. The paper proposes and then assesses a way of interconnecting even a large number of fieldbuses, introducing delays which are compatible with process control requirements.>

In this paper, the authors adopt a neural approach to deal with the problem of routing in a packet switching network. The aim is to define a routing strategy which will combine the advantages of both the centralized and the distributed approaches. The neural approach presented is based on the idea of inserting a neural network (N/N) into each node in the computer network which will be responsible for computing the route between its node and the immediately adjacent one. Two distributed routing solutions are presented in the paper based on an optimizing network and a mapping network. The routing obtainable and the implementation resources needed for the two approaches are evaluated. Finally, the performance offered by the neural strategies proposed is compared with that offered by classical distributed and centralized routing solutions. As a parameter of merit, the effect of overloading caused by the additional traffic present in each solution is used.

The work presented is a case study of the application on the FieldBus protocol to motor cars. The problem of the management of traffic made up of the various actuation and control signals present in a car is addressed, and criteria for allocation of the available bandwidth and assessing the behavior of the FieldBus in various traffic conditions are discussed. The results obtained show that, in the particular case considered, the FieldBus proved to be perfectly capable of meeting the communication requirements of car control systems.>

An issue of current interest in the Open Systems Interconnection (OSI) field is the choice of a language well suited to specification and verification. For this purpose, two languages based on Milner's communication calculi are proposed, respectively intended for the specification of asynchronous and synchronous OSI systems. A formal verification method, relying upon the algebraic foundations of the two languages, is introduced and illustrated by means of examples based on nontrivial protocols and services.

An expert system implemented for studying chronic venous insufficiency is described. This disease is actually classified into three possible stadia, but studies performed on several patients showed that a further stadium exists. The system has been used for statistical evaluations of patient symptoms to detect those characterizing this stadium. An architecture for the expert system is proposed, with emphasis on the implementation of the knowledge base.>