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Integrating Cognitive Radio Networks with Internet of Things, which is called Cognitive Radio Internet of Things (CRIoT), is considered to be a breakthrough for the IoT spectrum scarcity problem. Some IoT applications can be controlled in a centralized manner while others needs a distributed manner. This depends on the nature and the architecture of the deployed IoT application. This paper proposes a distributed scheduling protocol to be applied on IoT for traffic control. Three distributed access strategies are examined; classical round robin and two proposed ones named vertex cover and enhanced round robin. They are used along with the centralized scheduling protocol (SDP-PSO) proposed by the authors in [1], to produce a distributed scheduling protocol. Dealing with this scheduling as an optimization problem; an objective fitness function is formulated, so that the fog node responsible to schedule at a time interval will formulate an allocation scheme for packets at itself. Using fairness index, average queuing delay and percentage of dropped packets as performance metrics, the performance evaluations of the three access strategies show that classical round robin performs better in case of using small number of fog node. However vertex cover performs better only in all other cases. Enhanced round robin performance is in the middle between the two other protocols.

In interweave Cognitive Radio Networks (CRNs), monitoring the spectrum to detect unused portions (holes) is done by the spectrum sensing function however, it consumes both time and energy. So, some protocols use prediction to estimate the channel availability. One of these protocols use Hidden Markov Model (HMM) but in a very simple way. So, it does not perform well in several cases. In this paper, we propose two new protocols for cognitive radio channel availability prediction. Both protocols use HMM but in a more advanced way. They divide the data into two sets, thus create two HMM models. The first protocol uses Bayes theorem together with these two models, while the second one uses Support Vector Machine (SVM) with the two models HMM parameters. Evaluation of the two protocols proves that both protocols perform better than the old one that uses HMM in a classical way. It also proves that using SVM with HMM parameters is better than using HMM only. This is because dividing the data into two sets for training the protocols with, gives more flexibility to both protocols.

This paper proposes the grouped tasks scheduling (GTS) algorithm that is used to schedule tasks in cloud computing network by applying quality of service to satisfy user's needs. The proposed algorithm distributes tasks into five categories; each category has tasks with similar attributes (user type, task type, task size, and task latency). After adding tasks into right category, it starts scheduling these tasks into available services. Scheduling is done in two steps: first step is deciding which category will be scheduled first. This depends on the attributes of the tasks that belong to each category so the category that has tasks with high value of attributes will be scheduled first. Second step is deciding which task inside the chosen category will be scheduled first. This depends on the execution time of task so the task that has minimum execution time will be scheduled first.

Purpose: This study is aimed to assess the serum expression levels of miR-210 and microRNA-23b (miR-23b) in bladder cancer (BC) patients to evaluate their potential as noninvasive biomarkers. Materials and Methods: This study included 93 subjects divided into the following three groups: Group Ia, 31 patients newly diagnosed with BC; Group Ib, Group Ia patients 6 months after medical and/or surgical treatment; and Group II, 31 healthy controls. The gene expressions of miR-210 and miR-23b were determined using quantitative SYBR Green reverse transcription real-time polymerase chain reaction. Results: The expression of miR-210 was significantly higher in BC patients compared to the controls (P = 0.012), while miR-23b did not show any difference. miR-210 expression in BC patients did not differ before and after treatment (P = 0.89). Area under the curve of the receiver operating characteristic analysis for miR-210 in distinguishing BC from controls was 0.686 (95% confidence interval, 0.553–0.818) with 71% sensitivity and 61% specificity. Conclusion: miR-210 can serve as a noninvasive diagnostic marker for BC; however, it cannot be used during treatment follow-up. miR-23b cannot be used as a diagnostic nor prognostic marker for BC.

The usage of Cognitive Radio Networks (CRNs) to establish Internet of Things (IoT) smart Networks is an effective and economical solution to the IoT spectrum scarcity problem. CRNs is merged with the IoT technology to be named Cognitive Radio Internet of Things (CRIoT). Spectrum sharing/scheduling in CRIoT has not attracted a lot of attention as it should do. This paper proposes a new packets' scheduling strategy for CRIoT. It is a centralized time slotted algorithm that uses discrete permutation particle swarm optimization for scheduling packets among predicted primary network empty time slots. An objective function is formulated to maximize the fairness index among fog nodes, minimize the packets' queuing delay and minimize the number of dropped packetsat each time interval. In order to evaluate the proposed protocol, it is implemented along with another protocol named spectrum auction. Using the fairness index, the average queuing delay and the number of dropped packets as evaluation metrics, simulation results proved that the proposed protocol outperforms the spectrum auction protocol. It also has a lower time and space complexity.

DDoS attack is one of the hardest attacks to detect and mitigate in the computer world. This paper introduces two quantitative models, which use the client puzzling to detect and thwart application DDoS attacks. We simulated the models to use the probabilistic metrics to penalize the malicious users and prevent them from launching a DDoS attack while offering a stable environment to the normal users and decreasing the number of false positives and false negatives

Several approaches have been proposed for Intrusion Detection Systems (IDS) in Mobile Ad hoc Networks (MANETs). Due to lack of MANETs infrastructure and well defined perimeter MANETs are susceptible to a variety of attacker types. To develop a strong security mechanism it is necessary to understand how malicious nodes can attack the MANETs. A new IDS mechanism is presented based on End-to-End connection for securing Optimized Link State Routing (OLSR) routing protocol. This new mechanism is named as Detection and Isolation Packet Dropped Attackers in MANETs (DIPDAM). DIPDAM mechanism based on three ID messages Path Validation Message (PVM) , Attacker Finder Message (AFM) and Attacker Isolation Message (AIM). DIPDAM mechanism based on End-to-End (E2E) communication between the source and the destination is proposed. The simulation results showed that the proposed mechanism is able to detect any number of attackers while keeping a reasonably low overhead in terms of network traffic.

This paper presents a theoretical model for summative e-assessment in distance learning for the future, where exams can be conducted distantly, e.g. at home. This model aims to provide e-learning systems with an authentication approach that guarantees cheating-free summative e-assessment. It utilizes a combination of live video monitoring and a bimodal biometrics approach. Together they form a robust and highly secure model to ensure that the examinee is the correct person throughout the e-assessment period without a need for a proctor. Advanced techniques of image and video processing and feature extraction are required to implement this model.

This paper proposes a new approach for e-assessment or e-examination authentication. This approach enables educational institutions to conduct cheating-free e-examinations, which has been considered a big challenge of e-learning within the previous decade. It ensures that an examinee is the correct student throughout his exam. This approach provides virtual, interactive, and secure e-examination sessions. A prototype will be developed on Moodle with a media server to broadcast sessions. A control toolbox will be developed to provide interaction between a proctor and examinees. An e-exam can not be started without approval by a proctor who can also pause, resume or terminate an e-exam any time if an examinee violates examination instructions.

Several approaches have been proposed for Intrusion Detection Systems (IDS) in Mobile Ad hoc Networks (MANETs). Due to lack of MANETs infrastructure and well defined perimeter MANETs are susceptible to a variety of attacker types. To develop a strong security scheme it is necessary to understand how malicious nodes can attack the MANETs. Focusing on the Optimized Link State Routing (OLSR) protocol an IDS mechanism to accurately detect misbehavior node(s) in OLSR protocol based on End-to-End (E2E) communication between the source and the destination is proposed. The simulation results showed that the proposed mechanism is able to detect any number of attackers while keeping a reasonably low overhead in terms of network traffic.