The growing pressures of urbanization, vehicular proliferation, and fragmented parking infrastructure pose significant sustainability and mobility challenges in modern cities. In response, we present SPOSChain (Smart Parking Optimization with SDN and Blockchain), a novel Blockchain-enhanced and Software-Defined Networking (SDN)-based smart parking system that unifies independent parking providers under a decentralized, intelligent coordination framework. SPOSChain introduces a four-layer architecture integrating IoT, data, control, and blockchain layers, to ensure transparency, scalability, and real-time responsiveness. The core parking assignment task is formulated as a fairness-driven optimization problem, which is mathematically equivalent to a parallel job scheduling problem, known to be NP-hard, thereby necessitating the development of efficient heuristic strategies. To this end, we propose, adopt, and evaluate multiple heuristic and hybrid algorithms, including Local Search, Branch-and-Bound, and Genetic Search, culminating in a time-aware Hybrid Search model. Simulation results under diverse vehicle arrival distributions (uniform, normal, and exponential) demonstrate that our approach significantly reduces load imbalance, quantified via the Total of Differences metric, while improving responsiveness and maintaining scalability. SPOSChain not only enables equitable and efficient parking allocation but also supports sustainable urban mobility by reducing driver search time, CO 2 emissions, and network overhead. These results underscore the transformative potential of programmable, decentralized parking systems in future smart city infrastructures.

Software-Defined Networking (SDN) and Blockchain (BC) are transformative technologies reshaping network management and security, utilizing their synergies. SDN’s centralized control enhances flexibility and efficiency but introduces vulnerabilities due to its single point of control. With its decentralized and immutable ledger, BC offers a solution by distributing control and providing a tamper-proof audit trail. This paper integrates these technologies to address blackhole attacks—a critical vulnerability where compromised SDN controllers disrupt network performance. We propose Blockchain-Enhanced SDN for Adaptive Path Finding (BeS4APF) algorithm against blackhole attacks in the multidomain SDNs. The algorithm maintains a high Packet Delivery Ratio (PDR) by dynamically adjusting network paths in response to node failures. The BeS4APF algorithm presented effectively maintains a high PDR by dynamically adjusting paths in response to node failures. The methodology involves monitoring the network, detecting compromised nodes, and recalculating optimal paths using Dijkstra’s algorithm and node-disjoint path selection. Experiments with synthetic networks of varying sizes (from 60 to 120 domains) demonstrate that the algorithm successfully handles domain-compromising node attacks, maintaining high PDR even with increasing stochastic disruptions. Our preliminary results show that, while PDR slightly deviates and recovers in smaller networks, it stabilizes towards almost 100% in larger networks after initial adjustments. This work advances the integration of SDN and BC, offering a robust approach to securing modern networks against evolving stochastic attack scenarios and threats.

Huge potentials of optical networks provide an excellent choice in meeting the exponential growth in bandwidth demand. In particular, Elastic Optical Networks (EONs), with its promising potentials in increased availability, failure resilience, load-balancing, new use cases for on-demand opportunities, and efficient resource allocations, are good candidates for the future high-speed networks. When EONs are augmented with the emerging Software Defined Networking (SDN), that decouples the data and control planes, an agile and synergistic combination emerges under a general term of SDN-based optical networking (SDON), albeit with operational challenges. In this paper, we introduce a blockchain-enabled QoS-based inter-Internet Service Provider (ISP) routing coordination framework for SDONs, SpectrumChain (SC), to eliminate centralized mediators and reduce QoS signaling overhead. Experimental results show that the SC framework can effectively handle the QoS-enabled inter-ISP routing in SDON architecture in terms of flow setup time, message overhead, and requests serviced as compared to the traditional approaches.

Data flows of various applications, such as video conferencing, telesurgery, online-gaming, etc., require particular treatment regarding Quality of Service (QoS) because of their sensitivity to such parameters as high bandwidth, low delay, and so on. However, provisioning of QoS-based routing services across Autonomous Systems (ASes) poses gruelling challenges due to the distributed nature and business confidentially hesitations. This study presents a novel blockchain-aided QoS-enabled inter-AS routing framework,QoSChain (QC), by blending merits of Software-Defined Networking (SDN) and Blockchain technologies.QCframework introduces a coordination framework with mutually distrusting participants that eliminates centralized mediators in provisioning QoS among SDN-enabled ASes. Also,QCreduces the time to set up an end-to-end (E2E) path and the number of messages exchanged and processed by SDN controllers for a QoS flow. Furthermore, it alleviates the concerns of network operators regarding potentially sensitive information disclosure resulting from the required information sharing for QoS-based cross-AS paths by masking details of any confidential information. Experimental results verify the feasibility of the proposed framework on E2E QoS-based routing among SDN networks. This work aims at being a useful primer for researchers in providing insights on how blockchain can be deployed in QoS-enabled routing.

Failures are inevitable in an operational network. They can happen anytime in different sizes and components of a network. They impact the network economics regarding CAPEX (Capital Expenditure), OPEX (Operational Expenditure), revenue lost due to service provisioning cut and so on. In order to mitigate the damages resulting from these failures, reactions of network architectures and designs are crucial for the future of the network. Recently, Software Defined Networking (SDN) has got the attention of researchers from both academia and industry as a means in order to increase network availability and reliability due to features, such as centralized automated control and global network view, it promises in networking. To this end, we explore the effects of programmable network architectures, i.e. SDN technology, and traditional network architectures, i.e. MPLS (Multiprotocol Label Switching) technology, on network economics by exploiting Number of Satisfied Service Requests and our predefined Unit Service Cost Scalability metrics under network failure scenarios: i) a random single data plane link failure and ii) a random controller (i.e. control plane) failure. To the best of our knowledge, this study is the first to consider a comparison of a programmable network architecture, i.e. SDN, along with different control plane models, Centralized (Single) Control Plane (CCP), Distributed (Flat) Control Plane (DCP), and Hierarchical Control Plane (HCP), and a non-programmable network architecture, i.e. MPLS, regarding network economics in case of network failures.

Economical and operational facets of networks drive the necessity for significant changes towards fundamentals of networking architectures. Recently, the momentum of programmable networking attempts illustrates the significance of economic aspects of network technologies. Software Defined Networking (SDN) has got the attention of researchers from both academia and industry as a means to decrease network costs and generate revenue for service providers due to features it promises in networking. In this article, we perform an economic analysis of SDN about different popular SDN control plane architectures: Centralized Control Plane (CCP), Distributed Control Plane with Local View (DCP_LV), and Hierarchical Control Plane (HCP) model. In particular, we investigate the economic impact of these control plane architectures about the unit cost for a service with bandwidth QoS parameter as well as Total Cost of Ownership (TCO) and network revenue for network owners under different traffic patterns. We characterize the unit cost for a service concerning CAPEX, OPEX, and workload of a network in a certain time period and apply the calculation methods in different SDN control plane models. Our experiments and analysis show that CCP model shows the highest TCO while DCP_LV model results in lowest amount among them. In addition, HCP model shows the lowest unit cost for a service among all models while CCP gives the highest cost for the same service tier. This work aims at being a useful primer to providing insights regarding the economic impact of control plane architectures in SDN for network researchers and owners to plan their investments.

In communication networks such as ISPs, telcos, and mobile network operators (MNOs), determining a correct unit cost for a service with QoS is a crucial task for the future of companies. A well-defined and efficient cost model is an essential tool to analyze network dynamics and in decisionmaking processes in a network. Also, knowing the real unit cost for a service helps network administrators/operators in various tasks such as service pricing, profitability analysis, and planning for possible introductions of new services or technologies. In this paper, we study the determination of unit cost for a service with QoS parameters. We characterize the unit cost for a service with respect to CAPEX (Capital Expenditures), OPEX (Operational Expenditures), and workload of a network in a certain time period. In addition, we investigate the relationship between the unit cost of a service and scalability of a network. We apply the proposed scheme in Software Defined Network (SDN) based architectures: centralized single controller architecture, distributed controllers architecture, and hierarchic controllers architecture. Our experiments show that there is an inverse relation between unit cost of a service and control plane scalability of the architectures: more scalable architectures result in lower unit costs for services.

Although many solutions have been proposed from both industry and academia, pricing the Internet services is still an ongoing research problem for researchers. In this paper, we propose an optimal pricing scheme for inter-AS traffic requests with QoS made by customers in Software Defined Networks (SDNs). This pricing scheme exploits the Nash bargaining problem which aims to maximize benefits of both service providers and customers. We integrate a new cost function and network connectivity degree factor into the proposed pricing scheme. Also, we give a general scheme of revenue and profit that a service provider makes. This scheme employs the idea of penalty for each request that a service provider cannot provide for its customers. Furthermore, we apply these schemes in our scalable hierarchic architecture with extensive experiments.

Software Defined Networking (SDN) architecture promises to mitigate limitations of traditional networking architectures in order to satisfy today's complex networking needs. However, as all new networking architectures, SDN also presents several inevitable technical challenges to be addressed by researchers. Control plane scalability is one of the crucial issues deserving more attention from both academia and industry in SDN as well. There are many existing solutions proposing a way to alleviate the control plane scalability in SDN. However, one prominent common ground they share is that they measure the control plane scalability performance in terms of typical network QoS parameters such as throughput and latency. Although these metrics may be a good performance indicators for quality of service measurement in mid-term and long-term, they may not reflect real scalability performance of control planes in SDN environments. However, a metric for scalability of control plane in SDN can provide network administrators some insights while they construct their SDN networks. In this paper, we firstly explore the roots of control plane scalability problem in SDN as well as proposed existing solutions. We then propose a metric in order to evaluate the control plane scalability in SDN. We give mathematical models of the proposed metric over different control plane designs. Further, we compare the performance of these control plane designs by extensive experiments.

All new networking architectures come with their own problems. Software Defined Networking (SDN) has its own challenges which are needed to be addressed by researchers as well. One of the crucial problems with SDN is the control plane scalability since it is a bottleneck for its evolution. As the network grows, the number of messages a controller receives also increases. This increase puts the controller scalability in the heart of problems of SDN. In this paper, we propose a hierarchy-based network architecture along with an inter-AS routing approach with QoS. We exploit idea of levels in which networks with controllers reside and a main controller, which works like a broker, is on top of them to keep the global network state and view. Our experiment results indicate that a controller in a hierarchic setting handles 50% less number of traffic than a controller in a non-hierarchic environment.

With the proliferation of the application areas of the Wireless Sensor Networks (WSNs) and the technological advances in sensor electronics, target tracking has become one of the most important functions in WSNs. The overwhelming majority of moving target tracking studies in WSNs has assumed either one-dimensional space (lineland), or two-dimensional domain (flat-land). However, many existing, such as environmental monitoring of rugged terrain, structural health monitoring of buildings, underground and underwater WSN applications, and emerging applications, such as search-and-rescue via Micro Aerial Vehicles, reconnaissance by insect-sized flying robots, need target tracking in three-dimensional space. In this study, we assume a Wireless Aerial Sensor Network (WASN) with conventional low-power and low-complexity features and devise a low spatial and temporal complexity moving target tracking mechanism in 3D based on g-h filter that considers measurement errors. Our prefatory simulations show promising preliminary results for our approach in terms of very low inaccuracy rates between the true location of the target and the forecasts at the sink node as well as negligible estimate errors in terms of Euclidean distance.

The impact of the computing field is becoming more profound everyday in all facets of modern society. Despite significant efforts from academia and relatively high demand for computing, technology producers are needed more than ever. This has been corroborated by a recent NSF Press Release [1], stating that computing is the only STEM discipline with more job openings than college graduates to fill them up. A major responsibility for such an outcome rests upon educators' ability to produce professionals capable of handling ever more complex technical challenges. In this challenging environment, the importance of practical work in science and engineering, supported by lab exercises, is widely known. While it is desirable to create physical laboratories for teaching these technologies, it is not always possible nor desirable. In this paper, we present an effective alternative approach, in the form of an affordable, virtualized laboratory environment that can be used in a variety of computing and engineering courses, as well as in other fields, in lieu of physical labs. Results of a survey supporting the validity of this approach are also presented. Students in four different classes were surveyed concerning the effectiveness and desirability of this virtual laboratory approach. The survey results indicate that student response to and interest in the virtual environment is very strong.