Can SDN Technology Be Transported to Software-Defined WSN/IoT?

© 2016 IEEE. Wireless sensor networks (WSNs) are essential elements of the Internet of Things ecosystem, as such, they encounter numerous IoT challenging architectural, management and application issues. These include inflexible control, manual configuration and management of sensor nodes, difficulty in an orchestration of resources, and virtualizing sensor network resources for on-demand applications and services. Addressing these issues presents a real challenge for WSNs and IoTs. By separating the network control plane from the data forwarding plane, Software-defined networking (SDN) has emerged as network technology that addresses similar problems of current switched-networks. Despite the differences between switched network and wireless sensor network domains, the SDN technology has a real potential to revolutionize WSNs/IoTs and address their challenging issues. However, very little has been attempted to bring the SDN paradigm to WSNs. This paper identifies weaknesses of existing research efforts that aims to bring the benefits of SDN to WSNs by mapping the control plane, the OpenFlow protocol, and the functionality between the two network domains. In particular, the paper investigates the difficulties and challenges in the development of software-defined wireless sensor networking (SDWSN). Finally, the paper proposes VSensor, SDIoT controller, SFlow components with specific and relevant functionality for an architecture of an SDWSN or SDIoT infrastructure

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

A Robot-Sensor Network Security Architecture for Monitoring Applications

This paper presents SNSR (Sensor Network Security using Robots), a novel, open, and flexible architecture that improves security in static sensor networks by benefiting from robot-sensor network cooperation. In SNSR, the robot performs sensor node authentication and radio-based localization (enabling centralized topology computation and route establishment) and directly interacts with nodes to send them configurations or receive status and anomaly reports without intermediaries. SNSR operation is divided into stages set in a feedback iterative structure, which enables repeating the execution of stages to adapt to changes, respond to attacks, or detect and correct errors. By exploiting the robot capabilities, SNSR provides high security levels and adaptability without requiring complex mechanisms. This paper presents SNSR, analyzes its security against common attacks, and experimentally validates its performance

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Software defined networking based resource management and quality of service support in wireless sensor network applications

To achieve greater performance in computing networks, a setup of critical computing aspects that ensures efficient network operation, needs to be implemented. One of these computing aspects is, Quality of Service (QoS). Its main functionality is to manage traffic queues by means of prioritizing sensitive network traffic. QoS capable networking allows efficient control of traffic especially for network critical data. However, to achieve this in Wireless Sensor Networks (WSN) is a serious challenge, since these technologies have a lot of computing limitations. It is even difficult to manage networking resources with ease in these types of technologies, due to their communication, processing and memory limitations. Even though this is the case with WSNs, they have been largely used in monitoring/detection systems, and by this proving their application importance. Realizing efficient network control requires intelligent methods of network management, especially for sensitive network data. Different network types implement diverse methods to control and administer network traffic as well as effectively manage network resources. As with WSNs, communication traffic and network resource control are mostly performed depending on independently employed mechanisms to deal with networking events occurring on different levels. It is therefore challenging to realize efficient network performance with guaranteed QoS in WSNs, given their computing limitations. Software defined networking (SDN) is advocated as a potential paradigm to improve and evolve WSNs in terms of capacity and application. A means to apply SDN strategies to these compute-limited WSNs, formulates software defined wireless sensor networks (SDWSN). In this work, a resource-aware OpenFlow-based Active Network Management (OF-ANM) QoS scheme that uses SDN strategies is proposed and implemented to apply QoS requirements for managing traffic congestion in WSNs. This scheme uses SDN programmability strategies to apply network QoS requirements and perform traffic load balancing to ensure congestion control in SDWSN. Our experimental results show that the developed scheme is able to provide congestion avoidance within the network. It also allows opportunities to implement flexible QoS requirements based on the system’s traffic state. Moreover, a QoS Path Selection and Resource-associating (Q-PSR) scheme for adaptive load balancing and intelligent resource control for optimal network performance is proposed and implemented. Our experimental results indicate better performance in terms of computation with load balancing and efficient resource alignment for different networking tasks when compared with other competing schemes.Thesis (PhD)--University of Pretoria, 2018.National Research FoundationUniversity of PretoriaElectrical, Electronic and Computer EngineeringPhDUnrestricte

Leveraging software-defined networking for modular management in wireless sensor networks

Thesis (PhD (Electronics))--University of Pretoria, 2019.Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming, and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure the proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency, and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software-defined networking (SDN) provides a promising solution for flexible management of WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. Therefore in a comprehensive literature review, this study highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail. All this while drawing attention towards the advantages that SDN brings to traditional WSN management. This study also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management. A profound research challenge uncovered in the literature review is the need for an SDN-based system that would provide an opportunity for rapid testing and implementation of management modules. Therefore, this study proposes SDNMM, a generic and modular WSN management system based on SDN. SDNMM introduces the concept of management modularity using a management service interface (MSI) that enables management entities to be added as modules. The system leverages the use of SDN in WSNs and by being modular it also allows for rapid development and implementation of IoT applications. The system has been built on an open-source platform to support its generic aspect and a sample resource management module implemented and evaluated to support the proposed modular management approach. Results showed how adding a resource management module via the MSI improved packet delivery, delay, control traffic and energy consumption over comparable frameworks. However, SDN-based implementation comes at a cost of control overhead traffic which is a performance bottleneck in WSNs due to the limited in-band traffic channel bandwidth associated with WSNs. This has driven the research community to look into methods of effectively reducing the overhead control traffic in a process known as control message quenching (CMQ). In this study, a state of the art overview of control traffic reduction techniques available and being implemented for SDN-based WSNs is also presented. It provides an insight on benefits, challenges and open research areas available in the field of control message quenching for SDN-based WSNs. This study opens the door to this widely unexplored research area in its current form. Additionally, this study introduces a neighbour discovery control message quenching (ND-CMQ) algorithm to aid the reduction of neighbour reports in an SDN-based 6LoWPAN framework. The algorithm produces a significant decrease in control traffic and as a result shows improvements in packet delivery rate, packet delay, and energy efficiency compared to not implementing any CMQ algorithm and also compared to an alternative FR-CMQ algorithm based on flow setup requests.Copperbelt University under the ministry of higher education in ZambiaCouncil for Scientific and Industrial Research (CSIR)Electrical, Electronic and Computer EngineeringPhD (Electronics)Unrestricte

Security of Software-defined Wireless Sensor Networks

Wireless Sensor Network (WSN) using Software Defined Networking (SDN) can achieve several advantages such as flexible and centralized network management and efficient routing. This is because SDN is a logically centralized architecture that separates the control plane from the data plane. SDN can provide security solutions, such as routing isolation, while handling the heterogeneity, scalability, and the limited resources of WSNs. However, such centralized architecture brings new challenges due to the single attack point and having non-dedicated channels for the control plane in WSNs. In this thesis, we investigate and propose security solutions for software-defined WSNs considering energy-efficiency and resource-preservation. The details are as follows. First, the functionality of software-defined WSNs can be affected by malicious sensor nodes that perform arbitrary actions such as message dropping or flooding. The malicious nodes can degrade the availability of the network due to in-band communications and the inherent lack of secure channels in software-defined WSNs. Therefore, we design a hierarchical trust management scheme for software-defined WSNs (namely TSW) to detect potential threats inside software-defined WSNs while promoting node cooperation and supporting decision-making in the forwarding process. The TSW scheme evaluates the trustworthiness of involved nodes and enables the detection of malicious behavior at various levels of the software-defined WSN architecture. We develop sensitive trust computational models to detect several malicious attacks. Furthermore, we propose separate trust scores and parameters for control and data traffic, respectively, to enhance the detection performance against attacks directed at the crucial traffic of the control plane. Additionally, we develop an acknowledgment-based trust recording mechanism by exploiting some built-in SDN control messages. To ensure the resilience and honesty of the trust scores, a weighted averaging approach is adopted, and a reliability trust metric is also defined. Through extensive analyses and numerical simulations, we demonstrate that TSW is efficient in detecting malicious nodes that launch several communication and trust management threats such as black-hole, selective forwarding, denial of service, bad and good mouthing, and ON-OFF attacks. Second, network topology obfuscation is generally considered a proactive mechanism for mitigating traffic analysis attacks. The main challenge is to strike a balance among energy consumption, reliable routing, and security levels due to resource constraints in sensor nodes. Furthermore, software-defined WSNs are more vulnerable to traffic analysis attacks due to the uncovered pattern of control traffic between the controller and the nodes. As a result, we propose a new energy-aware network topology obfuscation mechanism, which maximizes the attack costs and is efficient and practical to be deployed. Specifically, first, a route obfuscation method is proposed by utilizing ranking-based route mutation, based on four different critical criteria: route overlapping, energy consumption, link costs, and node reliability. Then, a sink node obfuscation method is introduced by selecting several fake sink nodes that are indistinguishable from actual sink nodes, according to the k-anonymity model. As a result, the most suitable routes and sink nodes can be selected, and a highest obfuscation level can be reached without sacrificing energy efficiency. Finally, extensive simulation results demonstrate that the proposed methods strongly mitigate traffic analysis attacks and achieve effective network topology obfuscation for software-defined WSNs. In addition, the proposed methods reduce the success rate of the attacks while achieving lower energy consumption and longer network lifetime. Last, security networking functions, such as trust management and Intrusion Detection System (IDS), are deployed in WSNs to protect the network from multiple attacks. However, there are many resource and security challenges in deploying these functions. First, they consume tremendous nodes’ energy and computational resources, which are limited in WSNs. Another challenge is preserving the security at a sufficient level in terms of reliability and coverage. Watchdog nodes, as one of the main components in trust management, overhear and monitor other nodes in the network. Accordingly, a secure and energy-aware watchdog placement optimization solution is studied for software-defined WSNs. The solution balances the required energy consumption, computational resource, and security in terms of the honesty of the watchdog nodes. To this end, a multi-population genetic algorithm is proposed for the optimal placement of the watchdog function in the network given the comprehensive aspects of resources and security. Finally, simulation results demonstrate that the proposed solution robustly preserves security levels and achieves energy-efficient deployment. In summary, reactive and proactive security solutions are investigated, designed, and evaluated for software-defined WSNs. The novelty of these proposed solutions is not only efficient and robust security but also their energy awareness, which allows them to be practical on resource-constrained networks. Thus, this thesis is considered a significant advancement toward more trustworthy and dependable software-defined WSNs

Novel Architecture and Heuristic Algorithms for Software-Defined Wireless Sensor Networks

This article extends the promising software-defined networking technology to wireless sensor networks to achieve two goals: 1) reducing the information exchange between the control and data planes, and 2) counterbalancing between the sender's waiting-time and the duplicate packets. To this end and beyond the state-of-the-art, this work proposes an SDN-based architecture, namely MINI-SDN, that separates the control and data planes. Moreover, based on MINI-SDN, we propose MINI-FLOW, a communication protocol that orchestrates the computation of flows and data routing between the two planes. MINI-FLOW supports uplink, downlink and intra-link flows. Uplink flows are computed based on a heuristic function that combines four values, the hops to the sink, the Received Signal Strength (RSS), the direction towards the sink, and the remaining energy. As for the downlink flows, two heuristic algorithms are proposed, Optimized Reverse Downlink (ORD) and Location-based Downlink(LD). ORD employs the reverse direction of the uplink while LD instantiates the flows based on a heuristic function that combines three values, the distance to the end node, the remaining energy and RSS value. Intra-link flows employ a combination of uplink/downlink flows. The experimental results show that the proposed architectureand communication protocol perform and scale well with both network size and density, considering the joint problem of routing and load balancing