With current network management technologies, management functions typically reside outside the network in management stations and servers, which interact with network elements and devices via network protocols for management, in order to execute management tasks, including fault, configuration, accounting, performance, and security management, or, short (FCAPS). Most of these tasks are performed on a per-device basis. During network operation, for instance, a management station periodically polls individual devices in its domain for the values of local variables, such as devices counters or performance parameters. These variables are then processed on the management station to compute an estimate of a network-wide state, which is analyzed and acted upon by management applications. This paradigm of interaction between the management system and managed system underlies traditional management frameworks and protocols, including SNMP, TMN [1] and OSI-SM. [2]
In the view of Future Internet activities in the research communities around the globe, the network management of a Future Internet is of major concern in the view of requiring more self-management, more automation of the management, and easier use of management tools. In-network management has been developed and discussed in a larger community gathered around project partners involved in the EU FP7 project 4WARD, [3] EU project AutoI [4] and EU project UniverSELF. [5]
In-network management (INM) supports management operations by the means of a highly distributed architecture. The main objective is the design of management functions that are located in- or close to the network elements and services to be managed, in most of the cases co-located on the same nodes; as target approach, they would be co-designed with the network elements and services. The vision of the INM paradigm of embedding management capabilities in the network. The benefit of the resulting distributed in-bound network management architecture - is the inherent support for self-management features, integral automation and autonomicity capabilities, easier use of management tools and empowering the network with inbuilt cognition and intelligence. Additional benefits include reduction and optimisation in the amount of external management interactions, which is key to the minimization of manual interaction and the sustaining of manageability of large networked systems and moving from a managed object paradigm to one of management by objective.
The design space of INM is spanned along seven axes:
UMF – Unified Management Framework [7] is being developed by the UniverSelf project, as the means of integrating the design space for INM.
More detailed information about that concept can be found in: [8] [9] [10] [11] [12]
An Embedded Operating System (EOS) is an operating system designed specifically for embedded computer systems. These systems aim to enhance functionality and reliability to perform dedicated tasks. When the multitasking method employed allows for timely task execution, such an OS may qualify as a real-time operating system (RTOS).
IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering. They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. These definition languages were developed under funding from U.S. Air Force and, although still most commonly used by them and other military and United States Department of Defense (DoD) agencies, are in the public domain.
FCAPS is the ISO Telecommunications Management Network model and framework for network management. FCAPS is an acronym for fault, configuration, accounting, performance, security, the management categories into which the ISO model defines network management tasks. In non-billing organizations accounting is sometimes replaced with administration.
Self-management is the process by which computer systems manage their own operation without human intervention. Self-management technologies are expected to pervade the next generation of network management systems.
Autonomic computing (AC) is distributed computing resources with self-managing characteristics, adapting to unpredictable changes while hiding intrinsic complexity to operators and users. Initiated by IBM in 2001, this initiative ultimately aimed to develop computer systems capable of self-management, to overcome the rapidly growing complexity of computing systems management, and to reduce the barrier that complexity poses to further growth.
The Telecommunications Management Network is a protocol model defined by ITU-T for managing open systems in a communications network. It is part of the ITU-T Recommendation series M.3000 and is based on the OSI management specifications in ITU-T Recommendation series X.700.
Computer-aided production engineering (CAPE) is a relatively new and significant branch of engineering. Global manufacturing has changed the environment in which goods are produced. Meanwhile, the rapid development of electronics and communication technologies has required design and manufacturing to keep pace.
NetOps is defined as the operational framework consisting of three essential tasks, Situational Awareness (SA), and Command & Control (C2) that the Commander (CDR) of US Strategic Command (USSTRATCOM), in coordination with DoD and Global NetOps Community, employs to operate, manage and defend the Global Information Grid (GIG) to ensure information superiority for the United States.
A federal enterprise architecture framework (FEAF) is the U.S. reference enterprise architecture of a federal government. It provides a common approach for the integration of strategic, business and technology management as part of organization design and performance improvement.
Autonomic networking follows the concept of Autonomic Computing, an initiative started by IBM in 2001. Its ultimate aim is to create self-managing networks to overcome the rapidly growing complexity of the Internet and other networks and to enable their further growth, far beyond the size of today.
Apache OFBiz is an open source enterprise resource planning (ERP) system. It provides a suite of enterprise applications that integrate and automate many of the business processes of an enterprise.
Capability management is a high-level management function, with particular application in the context of defense.
An element management system (EMS) consists of systems and applications for managing network elements (NE) on the network element-management layer (NEL) of the Telecommunications Management Network (TMN) model.
Operations support systems (OSS), operational support systems in British usage, or Operation System (OpS) in NTT are computer systems used by telecommunications service providers to manage their networks. They support management functions such as network inventory, service provisioning, network configuration and fault management.
Policy-based management is a technology that can simplify the complex task of managing networks and distributed systems. Under this paradigm, an administrator can manage different aspects of a network or distributed system in a flexible and simplified manner by deploying a set of policies that govern its behaviour. Policies are technology independent rules aiming to enhance the hard-coded functionality of managed devices by introducing interpreted logic that can be dynamically changed without modifying the underlying implementation. This allows for a certain degree of programmability without the need to interrupt the operation of either the managed system or of the management system itself. Policy-based management can increase significantly the self-managing aspects of any distributed system or network, leading to more autonomic behaviour demonstrated by Autonomic computing systems.
Cloud management is the management of cloud computing products and services.
The network and service management taxonomy serves as a classification system for research on the management of computer networks and the services provided by computer networks. The taxonomy has been created and is being maintained by a joint effort of the Flamingo FP7 Project and the Committee of Network Operations and Management (CNOM) of the Communications Society (COMSOC) of the Institute of Electrical and Electronics Engineers (IEEE) and the Working Group 6.6 of the International Federation of Information Processing (IFIP). The taxonomy is organized into seven categories. The first four categories identify what kind of network/service/business aspect is being managed and which functional areas are covered. The remaining three categories identify which management paradigms, technologies, and methods are used.
Infrastructure as code (IaC) is the process of managing and provisioning computer data center resources through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools. The IT infrastructure managed by this process comprises both physical equipment, such as bare-metal servers, as well as virtual machines, and associated configuration resources. The definitions may be in a version control system, rather than maintaining the code through manual processes. The code in the definition files may use either scripts or declarative definitions, but IaC more often employs declarative approaches.
Digital banking is part of the broader context for the move to online banking, where banking services are delivered over the internet. The shift from traditional to digital banking has been gradual, remains ongoing, and is constituted by differing degrees of banking service digitization. Digital banking involves high levels of process automation and web-based services and may include APIs enabling cross-institutional service composition to deliver banking products and provide transactions. It provides the ability for users to access financial data through desktop, mobile and ATM services.
Autonomous cargo ships, also known as autonomous container ships or maritime autonomous surface ships (MASS), are crewless vessels that transport either containers or bulk cargo over navigable waters with little or no human interaction. Different methods and levels of autonomy can be achieved through monitoring and remote control from a nearby manned ship, an onshore control center or through artificial intelligence and machine learning, letting the vessel itself decide the course of action.