Graph Theory for Survivability Design in Communication Networks

Design of survivable communication networks has been a complex task. Without establishing network survivability, there can be severe consequences when a physical link fails. Network failures which may be caused by dig-ups, vehicle crashes, human errors, system malfunctions, fire, rodents, sabotage, natural disasters (e.g. floods, earthquakes, lightning storms), and some other factors, have occurred quite frequently and sometimes with unpredictable consequences. To tackle these, survivability measures in a communication network can be implemented at the service layer, the logical layer, the system layer, and the physical layer

A secure and energy-aware approach for cognitive radio communications

The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radiospectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using sucha technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcityproblem and maximize spectrum efficiency. However, two major impediments have been limiting thewidespread adoption of cognitive radio technology. The software-defined radio technology, which is theenabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature ofthe CR can lead to major security concerns about the data being sent and how safe it is. In this paper,we introduce an energy-and-security-aware CR-based communication approach that alleviates the powerconsumption of the CR technique and enhances its security measures according to the confidentialitylevel of the data being sent. Furthermore, the proposed approach takes into account user-related factors,such as the user’s battery level and user’s data type, and network-related factors, such as the number ofunutilized bands and vulnerability level and then models the research question as a constrained optimizationproblem. Considering the time complexity of the optimum solution, we also propose a heuristic solution.We examine the proposed solution against existing solutions, and our obtained results show that theproposed approach can save energy consumption up to 18%, increase user throughput up to 20%, andachieve better spectrum utilization, up to 98%. Our proposed admission approach has the potential toopen a new research direction towards safer and greener cognitive radio techniques

Analysis of GPS and UWB positioning system for athlete tracking

In recent years, wearable performance monitoring systems have become increasingly popular in competitive sports. Wearable devices can provide vital information including distance covered, velocity, change of direction, and acceleration, which can be used to improve athlete performance and prevent injuries. Tracking technology that monitors the movement of an athlete is an important element of sport wearable devices. For tracking, the cheapest option is to use global positioning system (GPS) data however, their large margins of error are a major concern in many sports. Consequently, indoor positioning systems (IPS) have become popular in sports in recent years where the ultra-wideband (UWB) positioning sensor is now being used for tracking. IPS promises much higher accuracy, but unlike GPS, it requires a longer set-up time and its costs are significantly more. In this research, we investigate the suitability of the UWB-based localisation technique for wearable sports performance monitoring systems. We implemented a hardware set-up for both positioning sensors, UWB and the GPS-based (both 10 Hz and 1 Hz) localisation systems, and then monitored their accuracy in 2D and 3D side-by-side for the sport of tennis. Our gathered data shows a major drawback in the UWB-based localisation system. To address this major drawback we introduce an artificial intelligent model, which shows some promising results

A segmentation method for shared protection in WDM networks

Shared link and shared path protections have been recognized as preferred schemes to protect traffic flows against network failures. In recent years, another method referred to as Shared Segment Protection has been studied as an alternative solution for protection. This method is more flexible and efficient in terms of capacity utilization and restoration time. However, to our best knowledge, this method has mostly been studied in dynamic provisioning scenarios in which searching for restoration paths is dynamically performed after a failure has occurred. In this paper, based on the path segmentation idea, we propose a method to generate good candidate routes for traffic demands in static provisioning. These candidates are used as input parameters of an Integer Linear Programming (ILP) model for shared backup protection. Numerical results show that the capacity efficiency resulting from these candidates is much better than the best known Shared Backup Path Protection (SBPP) schemes. In addition, although the restoration time of our scheme is a little bit longer than those implementing link protection, it is still faster than path protection schemes

K Pair of disjoint paths Algorithm for Protection in WDM Optical Networks

Survivable routing in wavelength division multiplexing (WDM) optical networks has been proven to be NP-hard problem. There is a trade-off between the computational time and the optimality of solutions in existing approaches to the problem. Existing heuristic approaches purely based the graph algorithms are efficient in computational time but do not offer optimal solutions and may fail in some cases even when a solution exists. Meanwhile, the integer linear programming (ILP) models offer optimal solutions but are intractable even with moderate scale networks. In this paper, we introduce a new algorithm for finding K pairs of disjoint paths which are employed as K candidate pairs for each connection in the ILP models. We introduce an ILP model for dedicated path protection in which the number of decision variables is mainly dependant on traffic requests and the constant K, not on the network siz

A Shared Backup Path Protection Scheme for Optical Mesh Networks

We propose a new heuristic ILP model for share backup path protection (SBPP) scheme of mesh networks, which used the sets of disjoint-joint primary-backup path candidates of using path-pair candidates. The solution of the model is near optimal and provides all the routing details of demands as well as the sharing information between backup paths, and also simplifies the wavelength assignment problem if the wavelength continuity is a consideration. The new entities are introduced into this model that allow to control the resource utilization as well as congestion level of the network for optimization purposes and the pre-processing of data offers more control in properties of the path candidate

Dynamic Wavelength routing in all optical mesh network

Wavelength-division multiplexing (WDM) offers the capability to handle the increasing demand of network traffic in a manner that takes advantage of already deployed optical fibers. Lightpaths are optical connections carried end-to-end over a wavelength on each intermediate link. Wavelengths are the main resource in WDM networks. Due to the inherent channel constraints, a dynamic control mechanism is required to efficiently utilize the resource to maximize lightpath connections. In this paper, we investigate a class of adaptive routing called dynamic wavelength routing (DWR), in which wavelength converters (WCs) are not utilized in the network. The objective is to maximize the wavelength utilization and reduces the blocking probability in an arbitrary network. This approach contains two sub-algorithms: least congestion with least nodal-degree routing algorithm (LCLNR) and dynamic two-end wavelength routing algorithm (DTWR). We demonstrate that DWR can significantly improve the blocking performance, and the results achieved as good as placing sparse WCs in the networ

Capacity Utilization versus Congestion Levels in wavelength Routing for large scale WDM Networks

Wavelength routing (WR) has been a key issue in WDM optical networks which carry huge amount of traffic aggregated from Internet protocol (IP), asynchronous transfer mode (ATM) and SDH/SONET layers. The problem, however, has been proved NP-hard. The time complexity and the optimality of solutions are two conflicting metrics. In addition, for optimization purposes, capacity utilization and network congestion level can be compromised to reduce the blocking probability of future connections. In this paper, we propose a heuristic approach for WR in large scale networks based on a balanced model developed for the capacity utilization and the congestion level. This is a two step approach, i.e K shortest paths (KSP) algorithm and a path selection algorithm (PSA), and is applicable not only at network design phase but also for online provisioning where a number of traffic connections may be requested simultaneously. We investigate the time complexity and the optimality of solutions as metrics for comparing our approach and the ILP formulation for wavelength routing. Simulation results show that our approach yields very promising results in terms of the optimality of solutions whilst also applicable to very large scale networks, say 500 nodes or mor

Green and secure computation offloading for cache-enabled IoT networks

The ever-increasing number of diverse and computation-intensive Internet of things (IoT) applications is bringing phenomenal growth in global Internet traffic. Mobile devices with limited resource capacity (i.e., computation and storage resources) and battery lifetime are experiencing technical challenges to satisfy the task requirements. Mobile edge computing (MEC) integrated with IoT applications offloads computation-intensive tasks to the MEC servers at the network edge. This technique shows remarkable potential in reducing energy consumption and delay. Furthermore, caching popular task input data at the edge servers reduces duplicate content transmission, which eventually saves associated energy and time. However, the offloaded tasks are exposed to multiple users and vulnerable to malicious attacks and eavesdropping. Therefore, the assignment of security services to the offloaded tasks is a major requirement to ensure confidentiality and privacy. In this article, we propose a green and secure MEC technique combining caching, cooperative task offloading, and security service assignment for IoT networks. The study not only investigates the synergy between energy and security issues, but also offloads IoT tasks to the edge servers without violating delay requirements. A resource-constrained optimization model is formulated, which minimizes the overall cost combining energy consumption and probable security-breach cost. We also develop a two-stage heuristic algorithm and find an acceptable solution in polynomial time. Simulation results prove that the proposed technique achieves notable improvement over other existing strategies