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Multicast routing refers to the transmission of packets to a group of nodes identified by a single multicast group address. It plays a critical role in supporting applications that require group communication such as video conferencing and file distribution. One particularly challenging environment for multicast routing is Mobile Ad-hoc Networks (MANETs). The major problems facing routing in such networks are node mobility, frequently changing topology, unstable wireless links, and limited transmission range. Despite these challenges, several multicast applications like data base initialization and file distribution applications require reliable and efficient delivery of data. Various approaches have been proposed for MANET multicasting, but either suffer from low Packet Delivery Ratio (PDR) or high overhead and lack of scalability. In addition, reliable multicasting requires re-transmission of lost packets, which increases protocol overhead. Recently, Reinforcement Learning (RL) techniques have been successfully used in unicast routing to provide adaptive routing schemes. RL allows wireless nodes to make efficient routing decisions based on interaction with the environment while reducing the routing overhead compared to traditional routing approaches. In this paper, we investigate whether the same results hold when applying RL to multicasting in MANETs. We aim for two main performance criteria: ensuring 100% data delivery while at the same time reducing the total number of packets transmitted over the network. Based on these metrics, we evaluate existing RL-based multicast routing techniques and suggest promising approaches for reliable and efficient multicast routing protocols.

As the number of wireless devices explodes in the lead up to the release of 5G communications technology, it is expected that the demands for usage of the wireless spectrum will increase to the point where current spectrum allocation methods will no longer be sufficient. Dynamic Spectrum Management (DSM) uses cognitive radio methods to sense the current state of spectrum usage by other devices, and then makes use of that data to allocate spectrum in time and space to best meet users communication requirements in near real time. Our previous work on a Spectrum Environment Awareness (SEA) sensor system suggests that static tasking of the large number of sensors required for 5G would consume large amounts of storage and communications resources. Intelligent and collaborative tasking of sensors would reduce both these overheads as well as the burden on data analysis. In this paper, we describe an intelligent distributed collaborative sensing system with centralized control for use in DSM-based automated spectrum assignment. We use simulation results to estimate the amount of sensor reading duplication in such a system. These results provide direction on how intelligent sensing systems can optimize the tasking of sensors in this domain.

Long Term Evolution (LTE) is a promising technology to be used for Mission-Critical Networks (MCNs); emulating such technology is important to test different scenarios before real deployment. However, using the Network Simulator (NS-3) to simulate large-scale LTE networks has proven to be very time consuming. Hence, there is a need to speed up such simulations in order to facilitate real-time emulation and interaction of large-scale LTE networks with external systems. In this paper, we propose a new approach to enable the emulation of large-scale LTE networks by employing distributed topologies along with the Message Passing Interface (MPI) protocol. The proposed approach is integrated with the Common Open Research Emulator (CORE) to enable exchange of real-time traffic between the simulated LTE network and Hardware-In-the Loop (HIL). Performance studies were carried out to evaluate the scaling performance of emulated LTE networks in real time. The results show that distributed implementation succeeds in running scenarios within the wall-clock time.

Effectively managing spectrum for an ever increasing wireless world requires an advanced agile and flexible regulatory environment that uses an extensive network of sensing devices to ensure the orderly and secure evolution of new advanced networks and technologies that work free from harmful interference. The Spectrum Environment Awareness (SEA) prototype system currently being developed at the Communications Research Centre (CRC) Canada is a system for the next generation spectrum management, aiming to help government regulators to have better control of how spectrum is being used by different services at different times and locations across Canada, and to ensure better use of spectrum and effective response to spectrum inquiries. In this paper, the SEA system functional architecture is introduced. As one of the key components within the SEA system, the integration of the intelligent tasking subsystem in SEA applications is described in detail.

Mobile Ad hoc NETworks (MANETs) are a promising communication technology for tactical environments and emergency response operations. However, the features of MANETs, including dynamic topology and open wireless medium, lead to many security vulnerabilities. Malicious nodes can drop or modify packets that are received from other nodes and diminish the reliability of networks. Therefore, secure routing in MANETs is an important area of research. In this paper, we propose a scheme that enhances routing security based on trust. In the proposed scheme, in order to improve the accuracy of trust values with indirect observations, we use Dempster-Shafer theory of evidence to fuse observers' opinions. Consequently, a more accurate trust value can be calculated from indirect observations. We then utilize the trust value to enhance the MANET routing protocol security. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.

Security is a main concern in the establishment of tactical MANETs. Literature is abundant in defining protocol extensions to provide more secure MANET communications. Also many techniques have been developed to identify different types of network attacks, such as the wormhole attack, for example. However, all these security solutions are designed for specific routing protocols. In the absence of a generic security architecture, nodes from different MANET domains cannot cooperate and benefit from security advantages across the entire network, such as secured inter-domain routing, etc. In this paper, we present a general architecture for a security trust monitoring layer that runs on top of routing protocols. This security layer can be applied to different MANET routing protocols and provide monitoring of different network attacks by adding specific plug-ins. Our modular security approach allows nodes, running different routing protocols and equipped with different security solutions, to inter-operate by exchanging security information with each other. The idea is to have a security layer monitor MANET communications and construct a trust representation model of member nodes of the MANET. The trust information gathered can be communicated to MANET nodes (upon request), and such nodes can modify their routing tables accordingly. We show that this security architecture can be implemented on a real MANET test bed. As an example of security attack, we also show the integration of wormhole detection and counter-measure with the security trust monitoring layer performed on this same test bed.

Simplified multicast forwarding (SMF) provides an optimized flooding mechanism in MANET environments to efficiently propagate multicast packets. The main difference between the SMF and traditional multicast routing is that no multicast tree is built and maintained, and no group membership management is needed. Therefore all the nodes in MANET receive the multicast information. However, a multicast border gateway is required in a MANET to interoperate with other multicast routing protocols in the wired domain as SMF does not make use of traditional multicast method. We propose a MANET SMF gateway implementation solution that addresses the issues encountered within the gateway configuration, such as interaction with the protocol independent multicast protocol (PIM). We will present the results of a tested single-gateway MANET implementation, and will also introduce a proposal for the multiple-gateway scenario. In the IETF MANET working group, the SMF design group also presents proposals for handling multiple gateways; they recommend to apply a to the multicast traffic when multiple gateways are injecting a flow into a MANET area. However this approach implies that equal multicast packets disseminated into the MANET by different gateways have different taggerlD, and hence these packets cannot be detected as duplicates. Our approach differs by preferring the use of hashing by the gateways for marking equal packets injected into the MANET, hence making these equal packets compliant for duplicate detection. This article demonstrates a successful implementation of the gateway functionality and extends its analysis by proposing a solution for the multiple-gateway configuration.

We have implemented a fully-functional wormhole attack in an IPv6 802.11b wireless Mobile Ad Hoc Network (MANET) test bed running a proactive routing protocol. Using customised analysis tools we study the traffic collected from the MANET at three different stages: i) regular operation, ii) with a "benign" wormhole joining distant parts of the network, and iii) under stress from wormhole attackers who control a link in the MANET and drop packets at random. Our focus is on detecting anomalous behaviour using timing analysis of routing traffic within the network. We first show how to identify intruders based on the protocol irregularities that their presence creates once they begin to drop traffic. More significantly, we go on to demonstrate that the mere existence of the wormhole itself can be identified, before the intruders begin the packet-dropping phase of the attack, by applying simple signal-processing techniques to the arrival times of the routing management traffic. This is done by relying on a property of proactive routing protocols? that the stations must exchange management information on a specified, periodic basis. This exchange creates identifiable traffic patterns and an intrinsic "valid station" fingerprint that can be used for intrusion detection.