32 pubs · 411 cites · h-index 9
Mininet is a widely adopted emulator for prototyping and experimenting with Software-Defined Networking (SDN). Its main graphical interface, MiniEdit, however, offers limited functionality and low interactivity, which hampers adoption and constrains advanced experimentation. Although several alternative tools have been proposed, none has become a definitive replacement, largely due to the absence of essential integrated features. We present Mininet-GUI, a web-based tool that enables real-time creation, editing, and execution of Mininet topologies. Mininet-GUI allows dynamic manipulation of hosts, switches, controllers, and links, as well as direct command execution through the interface. Unlike existing approaches, it provides interactive topology editing, simplified terminal access via WebShell, and support for exporting and importing topologies in JSON and Python formats. Mininet-GUI is designed to make SDN experimentation more accessible and efficient for both beginners and advanced researchers. This paper describes its architecture, capabilities, and applicability through common use cases.
In the context of next-generation mobile networks, mobility control mechanisms are anticipated to provide infrastructures that can adapt to a broad range of requirements enforced by heterogeneous devices and applications. A mechanism that is central to this adaptability is the handover. During this critical phase of mobility lifecycle management, an appropriate technique for selecting the most suitable Point of Attachment (PoA) must be employed to ensure that mobile devices maintain optimal connectivity. Among the various strategies used to tackle the handover decision problem, the Multiple Attribute Decision-Making (MADM) method is one of the most cost-effective, given the benefits provided by its decision-making approach. Despite its popularity, mobility management mechanisms often employ MADM methods without conducting a thorough performance analysis to justify the approach. One of the main reasons for such referenceless handover technique adoptions is the lack of studies that could inform researchers, developers, mobility managers, and operators about the primary differences among available MADM methods. To fill this knowledge gap, in this paper, we conduct a comprehensive review of the literature on MADM methods in the domain of handover decisions. In particular, our contribution includes providing a detailed summary of the step-wise mathematical implementation in addition to a broad discussion of the main MADM methods in the quality-oriented mobility decision domain, thoroughly classifying their characteristics, and analyzing strengths and limitations. We also compare different categories of MADM methods and discuss some open issues and research challenges in this area.
Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN's performance. We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future.
The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing.
Software-Defined Networking (SDN) controllers are nowadays expected to manage large infrastructures and services in a practical, efficient, and optimized way. To achieve such control, SDN networks should increase the automation of orchestration functions to fullfil both service and network management lifecycles. However, network management applications have stringent resource demands that orchestrators need to honor. Most of the available orchestrators focus on high-level approaches that rely exclusively on the Northbound API (NB-API). A few strategies have also been designed to optimize the controllers' internal mechanisms through features enabled by the Southbound API (SB-API). However, such solutions do not focus on optimal information delivery to the orchestrator, a crucial property to provide prompt feedback in response to network events, and to potentially drive self-healing and auto-scaling properties. To address such need, we present NOTORIETY, an orchestration system that provides an abstraction for real-time SDN network controller event message handling. NOTORIETY is able to maximize the orchestration capabilities of SDN controllers including innovative features for processing and delivering network event information. NOTORIETY's design consists of mechanisms that empower SDN-controlled entities by applying filtering rules to efficiently control and optimize data flows provided by the SDN controller. We implemented a testbed to assess our NOTORIETY proposal following the guidelines provided in the RFC 8456, and we benchmark its performance over three SDN controllers (OpenDaylight, ONOS, and Floodlight). The evaluation results reveal the effectiveness of NOTORIETY in reducing the execution time of SDN requests, load processing, and overall data marshaling volume in several scenarios.
The expansion of the Internet has grown the possibilities for fraudulent actions. Among these possibilities, we highlight the phishing activity, created with the objective of capturing user's credentials through a false page similar to the original one. This work proposes PhishKiller, a tool capable of detecting and mitigating phishing attacks by means a proxy approach employed to intercept user‐accessed addresses, and featureless machine learning techniques to classify URLs. The proof‐of‐concept evaluation results revealed that PhishKiller has a more cost‐effective compared to state of the art, with an accuracy of 98.30% and taking only 81.68 ms to predict and block malicious websites.
Ultradense Networks (UDNs) seek to scale the 5th-Generation mobile network systems at unforeseen amounts of networks, users, and mobile traffic. We believe that the Wi-Fi sharing service is an asset in expanding 5G UDN capacity requirements for higher coverage and ubiquitous wireless broadband connectivity. However, the limitations of the Wi-Fi sharing pioneer deployment, along with other related works, has led our team to carry out further research. As a result, it was found that FOg CloUd Slicing for Wi-Fi sharing (FOCUS) is a suitable means of expanding 5G UDN capacities. FOCUS applies end-to-end Network-Cloud slice definitions on top of the Wi-Fi sharing technology, with the aim of offering multitenancy and multiservice support for a wide range of services, while meeting carrier-grade requirements and resource control at runtime and making full use of a “softwarized” approach. The feasibility of the FOCUS system is assessed in a real testbed deployment prototype, which allows an accurate view to be obtained of the basic functional principles and system-level proof-of-concept alongside the FON de facto Wi-Fi sharing service. The results suggest that FOCUS offers much greater benefits than FON, owing to its capacity to provide end-to-end Network-Cloud Slices while ensuring independent/isolated service delivery with resource adaptation at runtime.
The slicing of resources in federated clouds has been explored as a facilitator for the creation of multiple independent virtual infrastructures, namely virtual slices, operating under the physical infrastructure of federated data centers, each specially adapted to the needs of the tenants. Among the main challenges related to the management of slices in these environments, mainly due to the technological limitations of the infrastructures, the security aspects related to confidentiality, availability, and isolation have been called the attention of the scientific community. In this context, this paper presents an initial discussion of the security requirements of federated cloud slicing through a case study on the Novel Enablers for Cloud Slicing(NECOS) platform, which is an initiative to deal with the limitations of cloud computing to respond to the demand for new services through a new concept: the Lightweight Slice Defined Cloud(LSDC), which presents itself as an approach that extends virtualization to all the resources in the networks and involved data centers and provides uniform management with a high level of orchestration.
Future mobility management systems need to in-corporate innovative methods to improve mobile multimedia networking, such as quality-oriented decision-making functions for selecting the best Point of Attachment (PoA) for in-transit Moving Objects (MOs). Among the various correlating algorithms raised in the literature, solutions based on the Multiple Attribute Decision Making (MADM) are beneficial by their efficiency in mobile multimedia networking. For the best of our knowledge, the literature lacks a comprehensive analysis concerning the subjective aspects related to user perception/satisfaction, the key to assessing multimedia Quality of Experience (QoE). The state of the art in MADM quality-oriented mobility management evaluation only address network-/packet-level Quality of Service (QoS) measures. Therefore, this work fills this gap by undertaking a user-centric QoE evaluation of the foremost available MADM-based algorithms used in quality-oriented mobility management over our previous work: the Extended Elitism for Best Selection (E2BS). The QoE evaluation is conducted leveraging the flexibility of the Software-Defined Mobile Networking (SDMN) paradigm. The QoE analysis outcomes demonstrate that E2BS outperforms the selected MADM-based methods, by improving the overall QoE perceived by mobile users when consuming multimedia mobile flows.