Semantic network management for next‐generation networks

Abstract

To accommodate the proliferation of heterogeneous network models and protocols, the use of semantic technologies to enable an abstract treatment of networks is proposed. Network adapters are employed to lift network specific data into a semantic representation. Semantic reasoning integrates the disparate network models and protocols into a common data model by making intelligent inferences from low-level network and device details. Automatic discovery of new devices, monitoring of device state, and invocation of device actions in a generic fashion that is agnostic of network types is enabled. A prototype system called SNoMAC is described that employs the proposed approach operating over UPnP, TR-069, and heterogeneous sensors. These sensors are integrated by means of a sensor middleware named SIXTH that augments the capabilities of SNoMAC to allow for intelligent management and configuration of a wide variety of sensor devices. A major benefit of this approach is that the addition of new models, protocols, or sensor types merely involves the development of a new network adapter based on an ontology. Additionally, the semantic representation of the network and associated data allows for a variety of client interfaces to facilitate human input to the management and monitoring of the system.By the year 2021, the Internet of Things (IoT) is expected to encompass 3.5 times as many connected devices as there are people on Earth. 1 In addition to the sheer volume of devices, there is the added complexity of dealing with the unchecked proliferation of new network data models and protocols. To deal with these issues, network and active media applications will not only require high performance and scalability but will also need the means for quickly and dynamically evolving to accommodate the changing universe of devices. Doing this effectively necessitates a new approach for integrating network models and protocols that facilitates the intelligent management of devices across layers and at various levels of abstraction. This allows devices to be handled generically as collections while maintaining the specifics necessary to monitor and control them individually. This paper advocates an approach to solving this problem that leverages the benefits afforded by semantic web technologies, combined with the advantages of intelligent middleware. This automates much of the organization and integration of heterogeneous devices and provides a platform upon which a wide variety of applications can be built.Semantic web technologies enable the definition of formal data models called "ontologies" that provide a number of conceptual and computational benefits. This includes data model alignment, heterogeneous data integration, built-in data abstraction mechanisms, automated inferencing, dynamic meta-modeling, and automatic consistency checking. These ontologies form the base upon which semantic tools such as SPARQL, 2 SWRL, 3 and OWL, 4 or a hybrid of these, can make intelligent inferences about both devices themselves and their networ...

Proliferation of Cyber Situational Awareness: Today’s Truly Pervasive Drive of Cybersecurity

“…e possibility theory expresses the nonspecificity of events, while the evidence theory describes nonspecificity and conflict. Among them, the most used fuzzy set proposed by [43] is a mathematical method to deal with the uncertainty and imprecision of human cognition. To process uncertain semantic information, it is a powerful tool to describe the processing of fuzzy information in the human brain.…”

“…Not only can it be used independently to construct representation and push the management system but also can be combined with other technologies as a general information representation technology. Fuzzy sets are recognized and widely used in the field of SA [43]. In addition, the gray theory is a theoretical method that uses gray information.…”

Selected Code-Quality Characteristics and Metrics for Internet of Things Systems

“…Matheus et al utilized "long established code quality metrics", without stating which they used, to evaluate a proposed semantic network management prototype, called SNoMAC. This system should help developers or system providers to easily interconnect the variety of heterogeneous devices that make up the IoT [45].…”

Artificial intelligence‐based novel scheme for location area planning in cellular networks

“…(1) begin (2) while (count ≠ v) do (3) for i = 1 to h do (4) if w mk = highest ∧ i ≠ boundary cell of territory, then (5) Choose the ith individual to start generation process.…”

“…3 Location management enables the cellular network to trace the cellphone amid two adjacent phone calls. 4 Handoff management supports the user in nonhome location or while roaming. 5,6 Location update (LU) and terminal paging together are known as Location Management.…”