Mustafa ElNainay

Metric-based taxonomy of routing protocols for cognitive radio ad hoc networks

Cognitive radio (CR) technology is introduced to solve the problem of spectrum under-utilization in wireless networks by opportunistically exploiting portions of the spectrum temporarily vacated by licensed primary users. Devices with cognitive capabilities can be networked to create cognitive radio ad hoc networks (CRAHNs) that face many challenges in different layers due to the flexibility in the spectrum access process. In this paper, we present a survey of recent routing solutions in CRAHNs. We start by listing routing challenges associated with the CRAHNs. We then present different routing protocols that are designed for CRAHNs, they can be classified according to the routing metric into six main categories: delay based, link stability based, throughput based, location based, energy-aware, and combined or multi-metric protocols that either combine many metrics together or use different metrics according to some specific rules. Finally, possible future research directions are discussed.

Dead zone penetration protocol for cognitive radio networks

Current routing protocols for cognitive radio networks are severely affected by the frequent activity of primary users. Nodes that are in the interference range of an appearing primary user are not allowed to transmit, and therefore existing routes which utilize such nodes are obliged to undergo a route maintenance phase. This naturally provides other routes to the destination that may incur extra delay or increase packet queuing overhead. In this work, a novel route maintenance protocol is proposed that allows existing routes to endure the event of primary user presence by forming cooperative links between neighboring nodes and nulling out transmission at the primary receiver using cooperative beamforming. Our proposed protocol can be used in conjunction with any of the existing routing protocols, thus achieving modularity. Extensive simulations are done which prove that our proposed protocol outperforms existing route maintenance techniques in terms of end-to-end delay and loss ratio, with minimal incurred overhead.

A multi-metric routing protocol with service differentiation for cognitive radio ad-hoc networks

In Cognitive Radio Networks, secondary users are affected by the the activity of primary users on licensed channels. To solve this problem, most routing protocols select the most stable links/channels, or use the minimum delay route and switch to other channels when primary users become active. However, these approaches may lead to competition between the secondary users on the most preferred links/channels which may cause congestion and affect the quality of the transmissions. In this paper, a multi-metric routing protocol with service differentiation is proposed. The main idea is to use different routing metrics for different traffic types to select routes that satisfy the specific requirements of each traffic type and to make load balancing across the network. Simulation results show that, compared to other related approaches, our protocol provides better end-to-end delay and increases the aggregate throughput. It also achieves load balancing across the network.

A carpooling recommendation system based on social VANET and geo-social data

Geo-social information can be utilized for user benefits in many applications. Social interaction in vehicular ad hoc networks (VANETs) is an important source for this type of information. In this paper, we first propose and describe a general architecture of the social VANET system (S-VANET) that supports social interaction through vehicular networks. Then, we present a new carpooling recommendation system that works as S-VANET application. The main objective is to recommend individuals to join their friends during trips or travels. The proposed recommendation system uses check-in history and home location to model users, and utilizes Fast Fourier transform to represent user check-ins and find the similarity between users. The system uses hierarchical clustering with weighted center of mass method to estimate the user home location.

Spectrum occupancy analysis of cooperative relaying technique for cognitive radio networks

Dynamic Spectrum Access (DSA) is a successful solution for the spectrum scarcity problem. In DSA, unlicensed users can gain access to licensed spectrum in a way that does not harm the licensed transmission. Many technical solutions are proposed to efficiently facilitate DSA. This paper analyzes the benefits of using cooperative relaying technique on the spectrum occupancy for the unlicensed transmissions. A slotted access with interweave spectrum sharing is modeled using stationary discrete time Markov chains for both non-cooperative and cooperative unlicensed transmissions. Furthermore, the effect of the cooperation level among the unlicensed users on the achieved throughput is investigated. The results show that the mechanism of cooperative relaying is more efficient in utilizing the unused spectrum especially in crowded spectrum. Moreover, the relative average throughput increases as the cooperation increases due to efficient utilization of the spectrum holes.

A cooperative spectrum sensing scheme based on task assignment algorithm for cognitive radio networks

In cognitive radio networks, dynamic spectrum access allows an unlicensed (secondary) user to use the frequency bands that are statically allocated to licensed (primary) users under condition of causing no harm to the primary transmission. For the process of the dynamic spectrum access to succeed, spectrum sensing becomes of great importance for the secondary user (SU) to capture the under-utilized frequency bands. This process must be as fast as possible to enable efficient spectrum utilization by the SU. In order to decrease the sensing time especially for wide band spectrum while keeping acceptable sensing accuracy, it is recommended to distribute this sensing task across the SUs in a way that leads to reduction of the probability of misdetection and the probability of false alarm. This work presents a channel assignment scheme for cooperative spectrum sensing in cognitive radio networks. Based on the individual - statistically calculated- probability of error of each SU over all channels, the algorithm assigns the best k adjacent channels for each SU to decrease the probability of misdetection and the probability of false alarm. It is shown by MATLAB simulations that the presented scheme is able to reach acceptable sensing probability of error in terms of reduced sensing delay when compared to full spectrum sensing where all nodes cooperate to sense all channels (no assignment takes place). Additionally, It is shown that the overall energy consumption of the cognitive radio network is reduced resulting in better network lifetime.

TACUE: A Timing-Aware Cuts Enumeration Algorithm for Parallel Synthesis

Achieving timing-closure has become one of the hardest tasks in logic synthesis due to the required stringent timing constraints in very large circuit designs. In this paper, we propose a novel synthesis paradigm to achieve timing-closure called Timing-Aware CUt Enumeration (TACUE). In TACUE, optimization is conducted through three aspects: (1) a new divide-and-conquer strategy is proposed that generates multiple sub-cuts on the critical parts of the circuit; (2) two cut enumeration strategies are proposed; (3) an efficient parallel synthesis framework is offered to reduce computation time. Experiments on large and difficult industrial benchmarks show the promise of the proposed method.

Channel allocation for dynamic spectrum access cognitive networks using Localized island Genetic Algorithm

In our demonstration, we show how cognitive radios can be organized to form a cooperative ad-hoc cognitive radio network that utilizes the available spectrum opportunistically and efficiently through channel allocation while at the same time avoiding causing interference to primary users as they become active. Our cognitive radios are Software Defined Radios consisting of a Linux laptop and a Universal Software Radio Peripheral integrated with our extended implementation of the GNU Radio software package and our Localized island Genetic Algorithm implementation for the channel allocation.

Selecting critical implications with set-covering formulation for SAT-based Bounded Model Checking

The effectiveness of SAT-based Bounded Model Checking (BMC) critically relies on the deductive power of the BMC instance. Although implication relationships have been used to help SAT solver to make more deductions, frequently an excessive number of implications has been used. Too many such implications can result in a large number of clauses that could potentially degrade the underlying SAT solver performance. In this paper, we first propose a framework for a parallel deduction engine to reduce implication learning time. Secondly, we propose a novel set-cover technique for optimal selection of constraint clauses. This technique depends on maximizing the number of literals that can be deduced by the SAT solver during the BCP (Boolean Constraint Propagation) operation. Our parallel deduction engine can achieve a 5.7× speedup on a 36-core machine. In addition, by selecting only those critical implications, our strategy improves BMC by another 1.74× against the case where all extended implications were added to the BMC instance. Compared with the original BMC without any implication clauses, up to 55.32× speedup can be achieved.

Analytical and simulation study of the effect of secondary user cooperation on cognitive radio networks

This paper presents an analytical and simulation study of the efficiency of using cooperative communication for Dynamic Spectrum Access (DSA) in secondary infrastructure networks. The licensed and unlicensed network transmissions are modeled using a Discrete Time Markov Chain (DTMC). The secondary network spectrum occupancy and throughput are evaluated analytically and by simulation. A COoperative and COgnitive MAC protocol (CO2MAC) is developed to facilitate cooperative transmissions in secondary infrastructure networks. The results show significant performance enhancement for cooperative transmission over direct transmission, especially in crowded spectrum, where it achieves up to 80% enhancement in throughput compared to direct transmission.