A Comprehensive Survey of Network Function Virtualization

A novel paradigm that changes the scene for the modern communication and computation systems is the Edge Computing. It is not a coincidence that terms like Mobile Cloud Computing, Cloudlets, Fog Computing, and Mobile-Edge Computing are gaining popularity both in academia and industry. In this paper, we embrace all these terms under the umbrella concept of “Edge Computing” to name the trend where computational infrastructures hence the services themselves are getting closer to the end user. However, we observe that bringing computational infrastructures to the proximity of the user does not magically solve all technical challenges. Moreover, it creates complexities of its own when not carefully handled. In this paper, these challenges are discussed in depth and categorically analyzed. As a solution direction, we propose that another major trend in networking, namely software-defined networking (SDN), should be taken into account. SDN, which is not proposed specifically for Edge Computing, can in fact serve as an enabler to lower the complexity barriers involved and let the real potential of Edge Computing be achieved. To fully demonstrate our ideas, initially, we put forward a clear collaboration model for the SDN-Edge Computing interaction through practical architectures and show that SDN related mechanisms can feasibly operate within the Edge Computing infrastructures. Then, we provide a detailed survey of the approaches that comprise the Edge Computing domain. A comparative discussion elaborates on where these technologies meet as well as how they differ. Later, we discuss the capabilities of SDN and align them with the technical shortcomings of Edge Computing implementations. We thoroughly investigate the possible modes of operation and interaction between the aforementioned technologies in all directions and technically deduce a set of “Benefit Areas” which is discussed in detail. Lastly, as SDN is an evolving technology, we give the future directions for enhancing the SDN development so that it can take this collaboration to a further level.

How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions

A system and method of serverless peer-to-peer group management and maintenance is presented. Group formation and discovery of private, public, and enumerated groups are provided, as is a method of joining such a peer-to-peer group. Group information management provided by the present invention ensures that each node maintains a current database from the initial joining of the group through the run phase of membership. Group graph maintenance utilizes a group signature to ensure that partitions in a graph may be detected and repaired. The utility of connections within the graph are also monitored so that non-productive connections may be dropped to increase the efficiency of the group. The diameter of the graph is also monitored and adjusted to ensure rapid information transfer throughout the group. A disconnect procedure is used to maintain the graph integrity and prevent partitions resulting from the departure of a group member.

Peer-to-peer group management and method for maintaining peer-to-peer graphs

Control of Discrete-event Systems provides a survey of the most important topics in the discrete-event systems theory with particular focus on finite-state automata, Petri nets and max-plus algebra. Coverage ranges from introductory material on the basic notions and definitions of discrete-event systems to more recent results. Special attention is given to results on supervisory control, state estimation and fault diagnosis of both centralized and distributed/decentralized systems developed in the framework of the Distributed Supervisory Control of Large Plants (DISC) project. Later parts of the text are devoted to the study of congested systems though fluidization, an over approximation allowing a much more efficient study of observation and control problems of timed Petri nets. Finally, the max-plus algebraic approach to the analysis and control of choice-free systems is also considered. Control of Discrete-event Systems provides an introduction to discrete-event systems for readers that are not familiar with this class of systems, but also provides an introduction to research problems and open issues of current interest to readers already familiar with them. Most of the material in this book has been presented during a Ph.D. school held in Cagliari, Italy, in June 2011. This book constitutes the refereed proceedings of the Third International Workshop on Tools and Algorithms for the Construction and Analysis of Systems, TACAS '97, held in Enschede, The Netherlands, in April 1997. The book presents 20 revised full papers and 5 tool demonstrations carefully selected out of 54 submissions; also included are two extended abstracts and a full paper corresponding to invited talks. The papers are organized in topical sections on space reduction techniques, tool demonstrations, logical techniques, verification support, specification and analysis, and theorem proving, model checking and applications. The refereed proceedings of the 24th International Conference on Applications and Theory of Petri Nets, ICATPN 2003, held in Eindhoven, The Netherlands, in June 2003. The 25 revised full papers presented together with 6 invited contributions were carefully reviewed and selected from 77 submissions. All current issues on research and development in the area of Petri nets are addressed, in particular concurrent systems design and analysis, model checking, networking, business process modeling, formal methods in software engineering, agent systems, systems specification, systems validation, discrete event systems, protocols, and prototyping. The contents of this volume are application oriented. The volume contains a de tailed presentation of 19 applications of CP-nets, covering a broad range of ap plication areas. Most of the projects have been carried out in an industrial set ting.

Coloured Petri Nets Basic Concepts, Analysis Methods and Practical Use

Survey A survey of routing protocols for smart grid communications

Wireless mesh networks (WMNs) are multihop wireless networks with self-healing and self-configuring capabilities. These features, plus the ability to provide wireless broadband connectivity at a comparatively low cost, make WMNs a promising technology for a wide range of applications. While discussing the suitability of WMN technology for public safety and crisis management communication, this article highlights its strengths and limitations and points to current and future research in this context.

Wireless Mesh Networks for Public Safety and Crisis Management Applications

Now found in domestic, commercial, industrial, military, and healthcare applications, wireless networks are becoming ubiquitous. Wireless mesh networks (WMNs) combine the robustness and performance of conventional infrastructure networks with the large service area and self-organizing and self-healing properties of mobile ad hoc networks. In this article, the authors consider the problem of ensuring security in WMNs, introduce the IEEE 802.11s draft standard, and discuss the open security threats faced at the network and data-link layers.

/pdf/securing-wireless-mesh-networks-46oocoinur.pdf

Securing Wireless Mesh Networks

Software Defined Networking (SDN) is a new networking paradigm, with a great potential to increase network efficiency, ease the complexity of network control and management, and accelerate the rate of technology innovation. One of the core concepts of SDN is the separation of the network's control and data plane. The intelligence and the control of the network operation and management, such as routing, is removed from the forwarding elements (switches) and is concentrated in a logically centralised component, i.e. the SDN controller. In order for the controller to configure and manage the network, it needs to have up-to-date information about the state of the network, in particular its topology. Consequently, topology discovery is a critical component of any Software Defined Network architecture. In this paper, we evaluate the cost and overhead of the de facto standard approach to topology discovery currently implemented by the major SDN controller frameworks, and propose simple and practical modifications which achieve a significantly improved efficiency and reduced control overhead. We have implemented our new topology discovery approach on the widely used POX controller platform, and have evaluated it for a range of network topologies via experiments using the Mininet network emulator. Our results show that our proposed modifications achieve an up to 45% reduction in controller load compared to the current state-of-the-art approach, while delivering identical discovery functionality.

Efficient topology discovery in software defined networks

Machine Learning (ML)-based Network Intrusion Detection Systems (NIDSs) have proven to become a reliable intelligence tool to protect networks against cyberattacks. Network data features has a great impact on the performances of ML-based NIDSs. However, evaluating ML models often are not reliable, as each ML-enabled NIDS is trained and validated using different data features that may do not contain security events. Therefore, a common ground feature set from multiple datasets is required to evaluate an ML model's detection accuracy and its ability to generalise across datasets. This paper presents NetFlow features from four benchmark NIDS datasets known as UNSW-NB15, BoT-IoT, ToN-IoT, and CSE-CIC-IDS2018 using their publicly available packet capture files. In a real-world scenario, NetFlow features are relatively easier to extract from network traffic compared to the complex features used in the original datasets, as they are usually extracted from packet headers. The generated Netflow datasets have been labelled for solving binary- and multiclass-based learning challenges. Preliminary results indicate that NetFlow features lead to similar binary-class results and lower multi-class classification results amongst the four datasets compared to their respective original features datasets. The NetFlow datasets are named NF-UNSW-NB15, NF-BoT-IoT, NF-ToN-IoT, NF-CSE-CIC-IDS2018 and NF-UQ-NIDS are published at this http URL for research purposes.

NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems

https://espace.library.uq.edu.au/view/UQ:541407/UQ541407_OA.pdf

Marius Portmann

Papers

Wireless Mesh Networks for Public Safety and Crisis Management Applications

Securing Wireless Mesh Networks

Efficient topology discovery in software defined networks

NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems

Efficient topology discovery in OpenFlow-based Software Defined Networks