Spectrum Allocation Algorithms for Cognitive Radio Mesh Networks

Empowered by the cognitive radio technology, and motivated by the sporadic channel utilization, both spatially and temporally, dynamic spectrum access networks (also referred to as cognitive radio networks and next generation wireless networks) have emerged as a solution to improve spectrum utilization and provide more flexibility to wireless communication. A cognitive radio network is composed of wireless users, referred to as secondary users, which are allowed to use licensed spectrum bands as long as their are no primary, licensed, users occupying the channel in their vicinity. This restricted spectrum access strategy leads to heterogeneity in channel availability among secondary users. This heterogeneity forms a significant source of performance degradation for cognitive radio networks, and poses a great challenge on protocol design. In this dissertation, we propose spectrum allocation algorithms that take into consideration the heterogeneity property and its effect on the network performance. The spectrum allocation solutions proposed in this dissertation address three major objectives in cognitive radio mesh networks. The first objective is maximizing the network coverage, in terms of the total number of served clients, and at the same time simplifying the communication coordination function. To address this objective, we proposed a received based channel allocation strategy that alleviates the need for a common control channel, thus simplifying the coordination function, and at the same time maximizes the number of clients served with link reliability guarantees. We show the superiority of the proposed allocation strategy over other existing strategies. The second objective is improving the multicast throughput to compensate for the performance degradation caused by channel heterogeneity. We proposed a scheduling algorithm that schedules multicast transmissions over both time and frequency and integrates that with the use of network coding. This algorithm achieves a significant gain, measured as the reduction in the total multicast time, as the simulation results prove. We also proposed a failure recovery algorithm that can adaptively adjust the schedule in response to temporary changes in channel availability. The last objective is minimizing the effect of channel switching on the end-to-end delay and network throughput. Channel switching can be a significant source of delay and bandwidth wastage, especially if the secondary users are utilizing a wide spectrum band. To address this issue, we proposed an on-demand multicast routing algorithm for cognitive radio mesh networks based on dynamic programming. The algorithm finds the best available route in terms of end-to-end delay, taking into consideration the switching latency at individual nodes and the transmission time on different channels. We also presented the extensibility of the proposed algorithm to different routing metric. Furthermore, a route recovery algorithm that takes into consideration the overhead of rerouting and the route cost was also proposed. The gain of these algorithms was proved by simulation

Robust provisioning of multicast sessions in cognitive radio networks

Today\u27s wireless networks use fixed spectrum over long term and fixed geographical regions. However, spectrum utilization varies by time and location, which leads to temporal and special spectrum underutilization. Therefore, new ways to improve spectrum utilization are needed. Cognitive radio is an emerging technology that enables dynamic sharing of the spectrum in order to overcome spectrum underutilization problem. Users in cognitive radio networks are either primary or secondary users. A primary user is the user who is licensed to use a channel, and has priority to use it over any other user. The secondary user uses a licensed spectrum channel opportunistically when a primary user is idle. Hence, it has to vacate the channel within a certain tolerable interference time when the primary user appears. As a result of this, the secondary user needs to find backup channels to protect the links it is using from primary user\u27s interruption. In this thesis, we concentrate on supporting the multicast service mode using cognitive radio networks. Moreover, we are concerned with supporting this mode of service such that it is robust in the face of failures. The type of failures we are interested in is channel disappearance due to the resumption of activities by primary users. We develop three algorithms which provide robust multicasting in such networks. Our three proposed algorithms are: 1) multicast sessions protection without link-sharing, 2) multicast sessions protection with link-sharing and 3) multicast sessions protection using rings. These algorithms provision multiple multicast sessions, and protect them against single primary user interruption at a time. They also take into account that the activities of a primary user may disrupt communication in several groups, of secondary users, which are referred to as Shared Primary User Risk Group (SPURG). The objective of the proposed algorithms is to increase the number of sessions that can be accommodated in the network and minimize the cost of provisioning the sessions. Multicast sessions protection with/without link-sharing algorithms generate a primary tree for each multicast session, and protect each link of it using a backup tree. Multicast sessions protection with link-sharing allows backup trees to share some links of the primary tree within the same session, and share some links within backup trees for any session. In the third algorithm, a ring is generated where it starts and ends at the source node, and passes through all destination nodes. Also, we compare the performances of our three proposed algorithms. Simulation results show that the number of accommodated sessions in the network increases and the cost of multicast sessions decreases when the number of available channels increases or the session size decreases. Also, multicast sessions protection with link-sharing algorithm outperforms the other two algorithms in terms of the number of sessions in the network. On the other hand, multicast sessions protection using rings achieves the lowest cost for multicast sessions compared with the other two proposed algorithms

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

On spectrum allocation strategies in Cognitive Radio Networks

Due to the temporal and spatial underutilization of licensed spectrum bands, as well as the crowdedness of unlicensed bands, a new spectrum access paradigm has been recently proposed namely, Cognitive Radio (CR). CR enables users to adjust their transceivers\u27 frequencies depending on the availability of licensed frequency bands which are otherwise unused by their licensees, called Primary Users (PUs). Thus, unlicensed wireless users, called Secondary Users (SUs) can dynamically and opportunistically access unused licensed bands in order to improve their throughput and service reliability. Whenever the licensed users, or the PUs, become active, SUs must vacate their bands. This dissertation is concerned with the operation of Cognitive Radio Networks (CRNs), and deals with four important problems. First, a performance model to study heterogeneous channel access in CRNs is presented. In this model, there are two types of licensed channels, where one type has a larger bandwidth, and hence a higher service rate for SUs. Therefore, SUs prefer to use such channels, if available, over channels in the second type which have a lower service rate. SUs may also switch from the second to the first type of channels when they become available, even if their current channels are still available. We also model the SUs\u27 sensing process, and derive several SUs\u27 performance metrics including average waiting time. Numerical results show that our proposed operational model outperforms a baseline model that does not support prioritized access. Second, we introduce a low overhead scheme for the uplink channel allocation within a single cell of CRNs operating as Wireless Mesh Networks (CR-WMNs). The scheme does not rely on using a Common Control Channel (CCC). The proposed mechanism is based on the use of Physical Layer Network Coding (PNC), in which two (or three) Secondary Users (SUs) who are requesting uplink channel allocation are allowed to transmit synchronously over a randomly selected channel from a set of available channels, and without coordination. A Mesh Router (MR) which is listening to these transmissions, and is in charge of channel allocation, can detect up to 2 (or 3) requests, on the same channel due to the use of PNC, and replies back with a control packet which contains information about channel assignment. Our proposed mechanisms significantly outperform traditional schemes that rely on using one CCC, or do not use PNC, in terms of channel allocation overhead time. Third, we also propose to enable SUs to recover their packets which collide with PUs\u27 transmissions when a PU becomes active for two scenarios, based on the received phase shifts. When a collision occurs between an SU and a PU transmitters, the SU\u27s receiver considers the PU\u27s transmission as an interference, and hence, cancels its effect in order to recover its corresponding received packet\u27s signals. Recovering collided packets, instead of retransmitting them saves transmitters\u27 energy. Numerical results show that a high percentage of energy can be saved over the traditional scheme, in which our packets recovery mechanisms are not employed. Finally, we propose a novel multicast resilient routing approach to select primary and backup paths from an SU source to SUs destinations. Our approach employs a multilayer hyper-graph, in order to model the network, e.g., channels. The primary paths to destination SUs are selected to minimize the end-to-end delay which takes into consideration channels switching latency and transmission delay. To protect the multicast session, we find a backup path for primary path, if feasible, such that these two paths are shared risk hyper-edge disjoint, in order to prevent a concurrent failure for these two paths, when the corresponding PU for this hyper-edge becomes active. Our simulation results show that increasing the number of available channels, increase the number of feasible primary and backup paths, and the maximum path delay decreases almost linearly