Management and Coordination Framework for Aerial-Terrestrial Smart Drone Networks

While worms and their propagation have been a major security threat over the past years, causing major financial losses and down times for many enterprises connected to the Internet, we will argue in this paper that valuable lessons can be learned from them and that network management, which is the activity supposed to prevent them, can actually benefit from their use. We focus on five lessons learned from current malware that can benefit to the network management community. For each topic, we analyse how it is been addressed in standard management frameworks, we identify their limits and describe how current malware already provides efficient solutions to these limits. We illustrate our claim through a case study on a realistic application of worm based network management, which is currently developed in our group.

As SDN technology is becoming popular in the field of computer networks management, the need for evolvable SDN-based network management systems arises. SDN facilitates introducing abstractions to the network through programmability and control separation. In this paper, we propose an abstraction in the SDN management layer through adopting a concept of separation of network concerns. We present a management framework, termed NWManager, that provides an abstraction to the network administrator through policies based on network management functions, like behaviour analysis and monitoring, quality of service preservation and security. And based on network concerns as follows, application, communication, resources concern and common concern representing the area of intersection between basic concerns. NWManager provides various network management functions in one system. Our conducted network simulation scenario by mininet demonstrates that this abstraction and separation of concerns in management layer facilitates and enhances the management of the network. As well, it extends the network control parameters provided to the network administrator.

A network management system can be divided into the management function and management intelligence logically according to the coordination concept. We represent a cooperative network management (CNM) framework using a reactive intelligent agent. The agent includes two types of objects. The event manager agent communication object (ACO) and business object repository compose the management function. Management intelligence is embodied in an engine which analyzes the received events from the event manager and messages from the ACO, then decide to invoke the business object's method based on action rules. The CNM framework is comprised of a management console, cooperative intelligent agents and access adapters. Using this framework, the administrator can decompose the management task into several subtasks and delegate these subtasks to cooperative intelligent agents. The management framework enables the administrator to modify the intelligent agent's subtask without interrupting the system's running.

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes—a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., $k$ -nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner.

A variety of Web-based applications, mobile apps, and other over the top data services with affordable 3G/4G enabled smart devices are major factors for enormous increase in heterogeneous data traffic at enterprise and mobile networks. This creates challenges regarding traffic management and requires traffic-aware intelligent network management to deliver sustained quality of experience for subscribers. Deep packet inspection and analysis (DPIA) provides base platform for development of traffic-aware intelligent network management and security systems. However, computationally complex DPIA-related packet processing for high speed data traffic makes these systems expensive. Furthermore, conventionally these traffic-aware network management and security systems are deployed in enterprise networks with independent and dedicated DPIA-related processing resources and require multiple copies of passively provisioned high speed data from network, while performing similar DPIA operations over the same data again and again. This duplicate deployment of expensive software and hardware resources for DPIA processing eventually results in higher capital expenditures as well as operational expenditures for network operators. We have proposed a novel service-oriented framework for heterogeneous deep packet inspection and analysis (SoDPI) that simultaneously provides diversified DPIA services to multiple client applications for network management and security operations in high-speed networks. Proposed framework provides flexible and comprehensive API-based service interface for client applications to register required DPIA services. SoDPI framework implementation is based on commodity hardware and deploys shared set of DPIA-related packet processing components, requiring only single copy of passive data provisioned from network. Experimental evaluations show that novel SoDPI framework requires considerably reduced amount of software and hardware resources to fulfill heterogeneous DPIA packet processing requirements for multiple client applications in comparison with conventional network management and security applications with dedicated DPIA components. This results in lower cost impacts for network operators with more network manageability.

A typical management application in today's enterprise network involves remote cooperation of a number of skilled people within and across organisations. Hence there is a need to consider the role of human resources and their interactions in a network operation and management process. However, most of the present day management solutions concentrate on the management of network equipment/devices. In view of the critical nature of many networked applications, it is important to provide effective and reliable management from the perspective of an enterprise. This paper reports our study of human cooperation in a network management environment in a large telecom organisation. This resulted in our proposed cooperative management framework for enterprise networks, which is presented.

Wireless networks today are partially being formed by nodes (e.g. Internet access points, smartphones, femtocells) that are owned and carried by humans. In such scenarios where several strangers are expected to interact for the sake of robust data transmission, trust and cooperation incentives are of vital importance as these establish a way for the nodes involved in the system to communicate with each other in a safe manner, to share services and information, and above all, to form communities that assist in sustaining robust connectivity models. The aim of this thesis is to build a framework that will combine a fully decentralized trust management system with cooperation incentives, in order to persuade users to behave in a correct manner to create a sustainable and scalable systems in exchange of some form of compensation/remuneration, in order to achieve an overall more robust architecture.

The ETSI's Zero touch network and Service Management (ZSM) framework is a prominent initiative to tame the envisioned complexity in operating and managing 5G and beyond networks. To this end, the ZSM framework promotes the shift toward full Automation of Network and Service Management and Operation (ANSMO) by leveraging the flexibility of SDN/NFV technologies along with Artificial Intelligence, combined with the portability and reusability of model-driven, open interfaces. Besides its benefits, each leveraged enabler will bring its own security threats, which should be carefully tackled to make the ANSMO vision a reality. This paper introduces the ZSM's potential attack surface and recommends possible mitigation measures along with some research directions to safeguard ZSM system security.

The current in-vehicle network lacks a robust security communication mechanism between Electronic Control Units (ECUs). Although different proposed frameworks aim to secure the Controller Area Network (CAN) bus communication, few of them consider relevant aspects such as key refreshing and management, ECU maintenance, and vehicle manufacturing process. Despite the fact that a centralized key distribution provides an efficient mechanism, security and safety fully depend on this centralized key generator, which may lead to a single point of failure problem. In this work, we present a semi-centralized dynamic key management framework that provides a decentralized and dynamic key generation during the vehicle's operation. Our framework not only increases security and safety even if the centralized key generator is offline but also reduces the number of keys, the communication payload inside the network, and the complexity of cryptographic material sharing during the vehicle's lifetime. Moreover, we propose a dynamic generation of session keys for different groups of ECU and external devices, which is a requirement for intelligent vehicles and future Internet of Vehicles. In order to evaluate the performance, we implement our framework on three hardware platforms with different computational power and validate its advantage, efficiency, and flexibility by comparing it with other frameworks.

The ever-increasing use of broad-band Internet and complex multimedia applications is pushing fiber closer and closer to the homes. Within the European project IST HARMONICS (Hybrid Access Reconfigurable Multi-wavelength Optical Networks for IP-based Communication Services), an optical access feeder network and resource management framework were developed that tackle this demand for bandwidth and the desire to stimulate the convergence of last-mile access technologies. To cope with the lack of bandwidth in the access and last-mile networks and the different needs of applications and users, the developed management system provides end-to-end quality of service (QoS) while integrating multiple technologies. In this paper, a detailed overview of the end-to-end QoS management framework and novel time slot/wavelength MAC protocol for the optical feeder network is given. End-to-end QoS is based on Differentiated services (DiffServ) at layer 3, various QoS supporting technologies at layer 2, and QoS mappings between both layers. The paper will also focus on the field trial results of the HARMONICS project and give some guidelines for possible problems and solutions in this area.

This paper presents the design and evaluation of a generalized topology discovery, operational monitoring, and provisioning (G-TOP) controller for a carrier-grade transport network. The G-TOP controller is a vendor-specific extension of the stateful PCE that integrates network topology discovery, path computation, and provisioning functions, but decouples the switch specific management framework. The G-TOP protocol enables the G-TOP controller to collect topology information, set up LSPs, and monitor state both from and to the management framework in a unified way. To validate the feasibility of the proposed framework, the author implemented a testbed using a multi-protocol label switching transport profile (MPLS-TP) switches and performed experimental testing. The experimental results show that the centralized control framework reduces provisioning time by approximately 68 ms and the autonomous management framework reduces fault recovery time by approximately 27 ms, while reducing the traffic load on the controller by several orders of magnitude compared to the OpenFlow approach.

The WWAN/WLAN two-hop-relay system integrates two types of wireless technologies to improve wireless access throughput and coverage. However, it is unreasonable to assume that all nodes are selfless and willing to relay for other users without an incentive. In this paper, a reputation management framework for Hybrid Wireless Relay Networks is presented. Based on this framework, we show how to collect and query reputation in an accurate, secure and efficient manner. The new reputation function is designed. The simulation results show that our model performs well in terms of convergence overload, communication overload, and performance.

Closed loops are key enablers for automation that have been successfully used in many industries for long, and more recently for computing and networking applications. The Zero-touch network and service management (ZSM) framework introduced standardized components that allow the creation, execution, and governance of multiple closed loops, enabling zero-touch management of end-to-end services across different management domains. However, the coordinated and optimal instantiation and operation of multiple closed loops is an open question that is left for implementation by the ZSM specifications. In this paper, we propose a methodology that uses intents as a way of communicating requirements to be considered by autonomous management domains to coordinate hierarchies of closed loops. The intent-driven methodology facilitates hierarchical and peer interactions for delegation and escalation of intents. Furthermore, it extends the existing management capabilities of the ZSM framework and facilitates conflict-free integration of closed loops by setting optimal (and non-conflicting) goals that each closed loop in the hierarchy needs to account for. We show an example of the application of the proposed methodology in a network slicing assurance use case. The new capabilities introduced in this paper can be considered as an extension of the ZSM framework to be used in scenarios where multiple intent-driven closed loops exist.

An optimization of the energy consumption in network systems has been recently an important research issue. The main challenge is to design, develop and test novel technologies, integrated control strategies and mechanisms for network equipment enabling energy saving by adapting network capacities and resources to current traffic loads and user requirements, while ensuring end-toend Quality of Service. In general, the idea is to develop low power devices or nano-processors, concentrate network traffic on a minimal subset of network components, and modulate network devices using dynamic voltage and frequency scaling methods. Various power adapting technologies for network devices are described in literature. We developed a framework for a backbone network management which leads to the minimization of the energy consumption by this network. The concept is based on activity control of the network equipment. The framework is presented in (Niewiadomska-Szynkiewicz et al., 2012b). In this paper we describe the design, performance and potential applications of the software environment for energy efficient backbone network optimization and simulation. This system was used to illustrate the performance of our control framework for energy-aware IP networks.

The growth in the development of distributed manufacturing systems necessitates increases in efficient technologies in order to facilitate management of the networked resources. Systems such as manufacturing automation protocol (MAP) already exist which were specifically designed for managing networked manufacturing devices. However, MAP has been criticised for being over-complex and expensive for small–medium sized enterprises. The simple network management protocol (SNMP) was designed for managing TCP/IP networks, and we argue that it can also be used for managing networked manufacturing devices. However, SNMP, like MAP, is based upon a client/server architecture, and both have scalability issues. We also investigate the use of mobile agent (MA) technology as a means of managing a domain of manufacturing devices. An integrated network management framework based on MA technology is developed to direct the research into the investigation of aligning network management paradigm to the strategic management decision.