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Software-Defined Networking (SDN) is becoming a native networking model for next-generation networks. However, with its decoupled architecture, SDN is susceptible to reconnaissance through time inference attacks. Attackers can use probing-based measurements and gather information such as network type and flow table size. In this paper, an automated attacker tool called RAFA is proposed to infer network type (SDN or traditional) and flow rule timeout values (hard and idle). Moreover, a lightweight defense mechanism to randomize rule timeouts with respect to network status is described. A comprehensive simulation setup with different network conditions shows that the proposed methods achieve a superior success rate in diverse settings.

Under demanding operational conditions such as traffic surges, coverage issues, and low latency requirements, terrestrial networks may become inadequate to provide the expected service levels to users and applications. Moreover, when natural disasters or physical calamities occur, the existing network infrastructure may collapse, leading to formidable challenges for emergency communications in the area served. In order to provide wireless connectivity as well as facilitate a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is needed. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs thanks to their high mobility and flexibility. In this work, we consider an edge network consisting of UAVs equipped with wireless access points. These software-defined network nodes serve a latency-sensitive workload of mobile users in an edge-to-cloud continuum setting. We investigate prioritization-based task offloading to support prioritized services in this on-demand aerial network. To serve this end, we construct an offloading management optimization model to minimize the overall penalty due to priority-weighted delay against task deadlines. Since the defined assignment problem is NP-hard, we also propose three heuristic algorithms as well as a branch and bound style quasi-optimal task offloading algorithm and investigate how the system performs under different operating conditions by conducting simulation-based experiments. Moreover, we made an open-source contribution to Mininet-WiFi to have independent Wi-Fi mediums, which were compulsory for simultaneous packet transfers on different Wi-Fi mediums.

For providing wireless connectivity and facilitating a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is instrumental. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs owing to their high mobility and agility. This paper considers a software-defined edge network consisting of UAVs equipped with wireless access points, which serve mobile users with latency-sensitive workload in an edge-to-cloud continuum setting. It investigates the task offloading paradigm to provide prioritized services via this on-demand aerial network. Accordingly, a task processing optimization model is defined to minimize the overall penalty calculated based on priority-weighted delay values against a priori defined task deadlines. Since the defined assignment problem is NP-hard, tailored heuristic models are proposed and evaluated to study how the system performs under different operating conditions.

Multimedia content transmission heavily taxes network resources and puts a significant burden on wireless systems in terms of capacity and energy consumption. In this context, device-to-device (D2D) paradigm has a utilitarian value to alleviate the network burden by utilizing short-range transmissions with less energy cost. For the realization of proper D2D networking, caching in devices is essential. Additionally, caching needs to operate efficiently with the aim of realizing network-wide energy improvements. To this end, we study multimedia caching in cellular D2D networks and propose an energy prioritized D2D caching (EPDC) algorithm in this work. We also investigate the optimal caching policy in that system setting. The impact of device capacity and D2D transmission range on energy consumption is studied by focusing on different operation modes such as D2D and base station transmissions. According to the simulation results, EPDC algorithm has substantial energy-efficiency gains over the commonly utilized Least Recently Used (LRU) algorithm and content-based caching algorithms PDC and SXO. For larger D2D transmission ranges, this improvement becomes more evident.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Future Internet is going to be shaped by networked multimedia services with exploding video traffic becoming the dominant payload. That evolution requires a remedial shift from the connection-oriented architecture to a content-centric one. Another technique to address this capacity crunch is to improve spectral utilization through new networking paradigms at the wireless network edge. To this end, Device-to-Device (D2D) communications has the potential for boosting the capacity and energy efficiency for content-centric networking. To design and implement efficient content-centric D2D networks, rigorous content modeling and in-network caching mechanisms based on such models are crucial. In this work, we develop a multidimensional content model based on popularity, chunking and layering, and devise caching schemes through this model. Our main motivation is to improve the system performance via our caching strategies. The numerical analysis shows the interplay among different system parameters and performance metrics: while our schemes perform slightly poorer in terms of system goodput, they also decrease the system energy expenditure. Overall, this improvement dominates the loss in the goodput, leading to greater energy efficiency compared to the commonly-used caching technique Least Recently Used (LRU).

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Device-to-device (D2D) transmissions in wireless edge networks are promising for optimizing system-wide energy consumption and improving system service capacity. Cooperative content caching similarly serves efficiency goals for data-intensive applications in edge networks. In this work, we propose two cooperative cache replacement algorithms in D2D networks to support these techniques: i) distance-based ii) priority-class based. Video content dissemination in an edge network is our main use-case. In such content traffic, video characteristics have a significant impact on the system behavior. Therefore, we also investigate the effect of content scene change dynamics in our system. Distance based cooperation outperforms LRU, MIN-ACC and SXO in terms of goodput while priority-class based approach consumes less energy than MIN-ACC with almost the same consumption as LRU, especially under fast changing scene regime. Besides, it is energy-wise slightly more rewarding than SXO for the fastest-changing scene case.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Future Internet is going to be shaped by networked multimedia services with exploding video traffic becoming the dominant payload. That evolution requires a remedial shift from the connection-oriented architecture to a content-centric one. Another technique to address this capacity crunch is to improve spectral utilization through new networking paradigms at the wireless network edge. To this end, Device-to-Device (D2D) communications has the potential for boosting the capacity and energy efficiency for content-centric networking. To design and implement efficient content-centric D2D networks, rigorous content modeling and in-network caching mechanisms based on such models are crucial. In this work, we develop a multidimensional content model based on popularity, chunking and layering, and devise caching schemes through this model. Our main motivation is to improve the system performance via our caching strategies. The numerical analysis shows the interplay among different system parameters and performance metrics: while our schemes perform slightly poorer in terms of system goodput, they also decrease the system energy expenditure. Overall, this improvement dominates the loss in the goodput, leading to greater energy efficiency compared to the commonly-used caching technique Least Recently Used (LRU).

Multimedia content transmission heavily taxes network resources and puts a significant burden on wireless systems in terms of capacity and energy consumption. In this context, device-to-device (D2D) paradigm has a utilitarian value to alleviate the network burden by utilizing short-range transmissions with less energy cost. For the realization of proper D2D networking, caching in devices is essential. Additionally, caching needs to operate efficiently with the aim of realizing network-wide energy improvements. To this end, we study multimedia caching in cellular D2D networks and propose an energy prioritized D2D caching (EPDC) algorithm in this work. We also investigate the optimal caching policy in that system setting. The impact of device capacity and D2D transmission range on energy consumption is studied by focusing on different operation modes such as D2D and base station transmissions. According to the simulation results, EPDC algorithm has substantial energy-efficiency gains over the commonly utilized Least Recently Used (LRU) algorithm and content-based caching algorithms PDC and SXO. For larger D2D transmission ranges, this improvement becomes more evident.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Device-to-device (D2D) transmissions in wireless edge networks are promising for optimizing system-wide energy consumption and improving system service capacity. Cooperative content caching similarly serves efficiency goals for data-intensive applications in edge networks. In this work, we propose two cooperative cache replacement algorithms in D2D networks to support these techniques: i) distance-based ii) priority-class based. Video content dissemination in an edge network is our main use-case. In such content traffic, video characteristics have a significant impact on the system behavior. Therefore, we also investigate the effect of content scene change dynamics in our system. Distance based cooperation outperforms LRU, MIN-ACC and SXO in terms of goodput while priority-class based approach consumes less energy than MIN-ACC with almost the same consumption as LRU, especially under fast changing scene regime. Besides, it is energy-wise slightly more rewarding than SXO for the fastest-changing scene case.

Multimedia content transmission heavily taxes network resources and puts a significant burden on wireless systems in terms of capacity and energy consumption. In this context, device-to-device (D2D) paradigm has a utilitarian value to alleviate the network burden by utilizing short-range transmissions with less energy cost. For the realization of proper D2D networking, caching in devices is essential. Additionally, caching needs to operate efficiently with the aim of realizing network-wide energy improvements. To this end, we study multimedia caching in cellular D2D networks and propose an energy prioritized D2D caching (EPDC) algorithm in this work. We also investigate the optimal caching policy in that system setting. The impact of device capacity and D2D transmission range on energy consumption is studied by focusing on different operation modes such as D2D and base station transmissions. According to the simulation results, EPDC algorithm has substantial energy-efficiency gains over the commonly utilized Least Recently Used (LRU) algorithm and content-based caching algorithms PDC and SXO. For larger D2D transmission ranges, this improvement becomes more evident.

Dynamic group key agreement (DGKA) protocols are one of the key security primitives to secure multiparty communications in decentralized and insecure environments while considering the instant changes in a communication group. However, with the ever-increasing number of connected devices, traditional DGKA protocols have performance challenges since each member in the group has to make several computationally intensive operations while verifying the keying materials to compute the resulting group key. To overcome this issue, we propose a new approach for DGKA protocols by utilizing Hyperledger Fabric framework as a blockchain platform. To this end, we migrate the communication and verification overhead of DGKA participants to the blockchain network in our developed scheme. This paradigm allows a flexible DGKA protocol that considers resource-constrained entities and trade-offs regarding distributed computation. According to our performance analysis, participants with low computing resources can efficiently utilize our protocol. Furthermore, we have demonstrated that our protocol has the same security features as other comparable protocols in the literature.

Next-generation wireless systems are expected to provide bandwidth-hungry services in a cost-efficient and ubiquitous manner. D2D communications, spectrum sharing and heterogeneous network architectures (HetNets) are touted as crucial enablers to attain these goals. Moreover, the shifting characteristics of network traffic towards content consumption necessitate content-centric architectures and protocols. In this work, we propose a comprehensive analytical model for a content-oriented heterogeneous wireless network with cognitive capability. We model our HetNet architecture with a Continuous Time Markov Chain (CTMC) and characterize the trade-off between energy efficiency and system goodput. We elaborate on novel elements in our model, namely the integration of universal source concept (modeling the content retrieval operation from external networks), caching and overlaying in D2D mode. Besides, our investigation on network mode selection provides further insight on how resource allocation and performance are intertwined.

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., A sizeable software defined network with a single controller responsible for all forwarding elements is potentially failure-prone and inadequate for dynamic network loads. To this end, having multiple controllers improves resilience and distributes network control overhead. However, when there is a disruption in the control plane, a rapid and performant controller-switch assignment is critical, which is a challenging technical question. In this work, we propose a proactive switch assignment approach in case of controller failures using a genetic algorithm based heuristic that considers controller load distribution, reassignment cost and probability of failure. Moreover, we compare the performance of our scheme with random and greedy algorithms. Experiment results show that our proposed PREFCP framework has better performance in terms of probability of failure and controller load distribution

Dynamic group key agreement (DGKA) protocols are one of the key security primitives to secure multiparty communications in decentralized and insecure environments while considering the instant changes in a communication group. However, with the ever-increasing number of connected devices, traditional DGKA protocols have performance challenges since each member in the group has to make several computationally intensive operations while verifying the keying materials to compute the resulting group key. To overcome this issue, we propose a new approach for DGKA protocols by utilizing Hyperledger Fabric framework as a blockchain platform. To this end, we migrate the communication and verification overhead of DGKA participants to the blockchain network in our developed scheme. This paradigm allows a flexible DGKA protocol that considers resource-constrained entities and trade-offs regarding distributed computation. According to our performance analysis, participants with low computing resources can efficiently utilize our protocol. Furthermore, we have demonstrated that our protocol has the same security features as other comparable protocols in the literature.

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., A sizeable software defined network with a single controller responsible for all forwarding elements is potentially failure-prone and inadequate for dynamic network loads. To this end, having multiple controllers improves resilience and distributes network control overhead. However, when there is a disruption in the control plane, a rapid and performant controller-switch assignment is critical, which is a challenging technical question. In this work, we propose a proactive switch assignment approach in case of controller failures using a genetic algorithm based heuristic that considers controller load distribution, reassignment cost and probability of failure. Moreover, we compare the performance of our scheme with random and greedy algorithms. Experiment results show that our proposed PREFCP framework has better performance in terms of probability of failure and controller load distribution

Next-generation wireless systems are expected to provide bandwidth-hungry services in a cost-efficient and ubiquitous manner. D2D communications, spectrum sharing and heterogeneous network architectures (HetNets) are touted as crucial enablers to attain these goals. Moreover, the shifting characteristics of network traffic towards content consumption necessitate content-centric architectures and protocols. In this work, we propose a comprehensive analytical model for a content-oriented heterogeneous wireless network with cognitive capability. We model our HetNet architecture with a Continuous Time Markov Chain (CTMC) and characterize the trade-off between energy efficiency and system goodput. We elaborate on novel elements in our model, namely the integration of universal source concept (modeling the content retrieval operation from external networks), caching and overlaying in D2D mode. Besides, our investigation on network mode selection provides further insight on how resource allocation and performance are intertwined.

SDN brings new opportunities to alleviate the existing security deficiencies of traditional networks. However, it also introduces new issues, a primary one being the vulnerabilities related to data and control plane communications. This work presents a security architecture to address security problems regarding data exchange in software-defined networks. To this end, a cryptographic key generation application is proposed to generate certificates that are used for securing communication of SDN entities (controller, switch, and application). We also provide an overview of related literature focusing on key elements in such architecture. In our model, TLS can be activated between SDN nodes to provide confidentiality, integrity, authentication, and authorization with special certificate fields. Besides, an integrated security module further strengthens the communication security by applying ACL, hardening TLS configuration and reducing the impact of private key hijacking. It also facilitates security administration tasks via per-channel activation/ deactivation of TLS protocol and monitoring of real-time security alarms.

Resilience in SDN control plane is a challenging goal when a single controller is employed. Thus, distributed controllers are deployed to realize a resilient and reliable software defined network. However, such a strategy can not succeed without an efficacious controller-switch assignment scheme. In addition to zero-day assignment, online re-assignment is crucial since due to network failures, the connections between controllers and switches may break off intermittently and impair the network operation. In this paper, we propose a reactive assignment model against network failures using integer linear programming based on load distribution of controllers. We augment our proposal with simulated annealing and random assignment approaches for switch, link and controller failures. The experimental results show that our model gives resilience against network failures and load-awareness is a effective strategy for controller assignment.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., In cases of catastrophic events such as natural disasters or physical calamities, current network infrastructure can become inoperative. Furthermore, there are transient events leading to excessive demand surges where it is needed to deploy additional network capacity on-demand. In such cases, rapid network deployments become vital to establish communications and enable networked services. Unmanned Aerial Vehicle (UAV) networks are good candidates for this kind of operation. Software-defined networking and content-centric operation are promising technologies to enable agile control, network visibility and efficient content delivery via centralized optimization in these challenged systems. In this work, we consider an edge network which is composed of UAVs and serves in a content-centric mode with in-network caching and device-to-device (D2D) transmissions. We develop a cache placement and selection scheme for energy efficient operation. We also investigate how such a system performs under different operating conditions.

Information-centric networking (ICN) is a Future Internet paradigm which uses named information (data objects) instead of host-based end-to-end communications. In-network caching is a key pillar of ICN. Basically, data objects are cached in ICN routers and retrieved from these network elements upon availability when they are requested. It is a particularly promising networking approach due to the expected benefits of data dissemination efficiency, reduced delay and improved robustness for challenging communication scenarios in IoT domain. From the security perspective, ICN concentrates on securing data objects instead of ensuring the security of end-to-end communication link. However, it inherently involves the security challenge of access control for content. Thus, an efficient access control mechanism is crucial to provide secure information dissemination. In this work, we investigate Attribute Based Encryption (ABE) as an access control apparatus for information centric IoT. Moreover, we elaborate on how such a system performs for different parameter settings such as different numbers of attributes and file sizes.

The Internet of Things (IoT) contains a diverse set of sensors, actuators and other Internet-connected devices communicating, processing data and performing a multitude of functions. It is emerging as an integral part of societal infrastructure enabling smart services. However, these connected objects might have various vulnerabilities that can lead to serious security compromises and breaches. Securing and hardening of IoT systems is thus of vital importance. In that regard, attack graphs provide analytical support to prevent multistep network attacks by showing all possible sequences of vulnerabilities and their interactions. Since attack graphs generally consist of a very large number of nodes, it is computationally challenging to analyze them for network hardening. In this paper, we propose a greedy algorithm using compact attack graphs to find a cost-effective solution to protect IoT systems. First, we extract all possible attack paths which reach predetermined critical resources embedded in the network. Then, exploit or initial condition with minimum effective cost is selected to be removed. This cost is calculated as a function of contribution to attack paths (the higher, the better) and removal cost (the lower, the better). This process continues iteratively until the total cost exceeds the allocated budget. The experimental results show that our algorithm scales almost linearly with the network size and it can be applied to large-scale graphs with a very large number of IoT nodes. In addition to network-hardening, our proposal measures the security level of the network in every step to demonstrate the vulnerability grade of the system.

SDN brings new opportunities to alleviate the existing security deficiencies of traditional networks. However, it also introduces new issues, a primary one being the vulnerabilities related to data and control plane communications. This work presents a security architecture to address security problems regarding data exchange in software-defined networks. To this end, a cryptographic key generation application is proposed to generate certificates that are used for securing communication of SDN entities (controller, switch, and application). We also provide an overview of related literature focusing on key elements in such architecture. In our model, TLS can be activated between SDN nodes to provide confidentiality, integrity, authentication, and authorization with special certificate fields. Besides, an integrated security module further strengthens the communication security by applying ACL, hardening TLS configuration and reducing the impact of private key hijacking. It also facilitates security administration tasks via per-channel activation/ deactivation of TLS protocol and monitoring of real-time security alarms.

Resilience in SDN control plane is a challenging goal when a single controller is employed. Thus, distributed controllers are deployed to realize a resilient and reliable software defined network. However, such a strategy can not succeed without an efficacious controller-switch assignment scheme. In addition to zero-day assignment, online re-assignment is crucial since due to network failures, the connections between controllers and switches may break off intermittently and impair the network operation. In this paper, we propose a reactive assignment model against network failures using integer linear programming based on load distribution of controllers. We augment our proposal with simulated annealing and random assignment approaches for switch, link and controller failures. The experimental results show that our model gives resilience against network failures and load-awareness is a effective strategy for controller assignment.

Information-centric networking (ICN) is a Future Internet paradigm which uses named information (data objects) instead of host-based end-to-end communications. In-network caching is a key pillar of ICN. Basically, data objects are cached in ICN routers and retrieved from these network elements upon availability when they are requested. It is a particularly promising networking approach due to the expected benefits of data dissemination efficiency, reduced delay and improved robustness for challenging communication scenarios in IoT domain. From the security perspective, ICN concentrates on securing data objects instead of ensuring the security of end-to-end communication link. However, it inherently involves the security challenge of access control for content. Thus, an efficient access control mechanism is crucial to provide secure information dissemination. In this work, we investigate Attribute Based Encryption (ABE) as an access control apparatus for information centric IoT. Moreover, we elaborate on how such a system performs for different parameter settings such as different numbers of attributes and file sizes.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., In cases of catastrophic events such as natural disasters or physical calamities, current network infrastructure can become inoperative. Furthermore, there are transient events leading to excessive demand surges where it is needed to deploy additional network capacity on-demand. In such cases, rapid network deployments become vital to establish communications and enable networked services. Unmanned Aerial Vehicle (UAV) networks are good candidates for this kind of operation. Software-defined networking and content-centric operation are promising technologies to enable agile control, network visibility and efficient content delivery via centralized optimization in these challenged systems. In this work, we consider an edge network which is composed of UAVs and serves in a content-centric mode with in-network caching and device-to-device (D2D) transmissions. We develop a cache placement and selection scheme for energy efficient operation. We also investigate how such a system performs under different operating conditions.

CR enables dynamic spectrum access to utilize licensed spectrum when it is idle. CR technology is applied to wireless ad hoc and sensor networks to form CRAHNs and CRSNs, respectively. Clustering is an efficient topology management technique to regulate communication and allocate spectrum resources by CR capabilities of nodes in CRAHNs and CRSNs. In this article, we thoroughly investigate the benefits and functionalities of clustering such as topology, spectrum, and energy management in these networks. We also overview motivations for and challenges of clustering in CRAHNs and CRSNs. Existing clustering schemes are reviewed and compared. We conclude by revealing key considerations and possible solutions for spectrum-aware clustering in multi-channel CRAHNs and CRSNs., NA

Content-oriented operation with D2D communications and spectrum sharing in the form of cognitive communications are expected to be enablers for cost-efficient nextgeneration wireless systems with bandwidth-hungry services. To this end, caching is an important building block of these systems. In this work, we model such a heterogeneous network and model a popularity-aware caching algorithm where we try to keep more popular contents in caches of system units with a higher probability compared to less popular contents. Moreover, for improving the usage of the channel capacity, overlaying for device-to-device (D2D) transmissions (unless these transmission interfere with each other) is enabled. We model our system with an analytical continuous time Markov chain (CTMC). We have a heterogeneous network architecture consisting of a LEO satellite, base station (BS) and a set of devices within the boundary of BS coverage that can get service from the satellite, from the BS or in D2D mode. Our devices operate in primary mode when they get service from the satellite but in secondary mode when they get service from the BS or some device in D2D mode over the terrestrial link. We evaluate our system for energy efficiency (EE) and goodput metrics. We looked how popularity-aware caching, integration of universal source concept and overlaying in D2D mode affect the network performance. Besides, we investigate how resource allocation (RA) and performance metrics are tangled., Comment: 20 pages, 10 figures

Atmospheric ducts that are caused by the rapid decrease in the refractive index of the lower atmosphere can trap the propagating signals. The trapping effect of atmospheric ducts provides significant received power enhancements and enables signals to reach beyond-line-of-sight distances. Although wave propagation in atmospheric ducts are well studied, there is no work that provides fading and correlation analysis for atmospheric ducts. Therefore, the main motivation of this communication is to develop a large-scale path-loss model, estimate the distribution of fading, and analyze fading correlation for space and polarization diversity systems in the presence of surface ducts. Lastly, the achievable data rate results are presented to show the performance improvement with space and polarization diversity techniques., NA

We formulate throughput maximizing, max-min fair, weighted max-min fair, and proportionally fair scheduling problems for cognitive radio networks managed by a centralized cognitive base station. We propose a very general scheduling model accomplishing goals such as making frequency, time slot, and data rate allocation to secondary users with possibly multiple antennas, in a heterogenous multi-channel and multi-user scenario. Moreover, our schedulers ensure that reliable communication between the cognitive base station and secondary users are maintained, no collisions occur among secondary users, and primary users in the service area of the cognitive base station are not disturbed. Two distinctive features of our fair schedulers are that they provide joint temporal and throughput fairness, and take throughput values experienced by secondary users in the recent past, referred to as window size, into account and use this information in the current scheduling decision. We also propose a heuristic algorithm for our fair schedulers and demonstrate through simulations that our proposed heuristic yields very close solutions to the values obtained from the optimization softwares. Furthermore, we make extensive simulations to evaluate our schedulers' performance in terms of both total throughput and fairness for varying number of secondary users, frequencies, antennas, and window size.