Security and trust in opportunistic networks - a survey

Opportunistic networks or OppNets refer to a number of wireless nodes opportunistically communicating with each other in a form of “Store–Carry–Forward”. This occurs when they come into contact with each other without proper network infrastructure. OppNets use wireless technologies, such as IEEE 802.11, WiMAX, Bluetooth, and other short-range radio communication. In OppNets, there is no end-to-end connection between the source and the destination nodes, and the nodes usually have high mobility, low density, limited power, short radio range, and often subject to different kinds of attacks by malicious nodes. Due to these characteristics and features, OppNets are subject to serious security challenges. OppNets strongly depend on human interaction; therefore, the success of securing such networks is based on trust between people. This survey includes the security approaches in OppNets and techniques used to increase their security levels.

Securing sensor networks by moderating frequencies

Security of Wireless Sensor Network (WSN) is a key issue in information security. Most existing security protocols exploit various Mathematical tools to strengthen their security. Some protocols use the details of the geographical location of the nodes. However, to the best authors’ knowledge, none of the existing works exploit the constraints faced by the adversary, specifically, tracing a particular frequency from a large range of unknown frequency channels. The current work uses positional details of the individual nodes. Then the aim is to exploit this weakness of tracing frequencies by assigning a wide range of frequency channels to each node. Experiments using Magneto Optic Sensors reveal that any change of the parametric Faraday’s rotational angle affects the frequency of the Optical waves. This idea can perhaps be generalized for practically deployable sensors (having respective parameters) along with a suitable key management scheme.

An incremental meta-cognitive-based scaffolding fuzzy neural network

The idea of meta-cognitive learning has enriched the landscape of evolving systems, because it emulates three fundamental aspects of human learning: what-to-learn; how-to-learn; and when-to-learn. However, existing meta-cognitive algorithms still exclude Scaffolding theory, which can realize a plug-and-play classifier. Consequently, these algorithms require laborious pre- and/or post-training processes to be carried out in addition to the main training process. This paper introduces a novel meta-cognitive algorithm termed GENERIC-Classifier (gClass), where the how-to-learn part constitutes a synergy of Scaffolding Theory - a tutoring theory that fosters the ability to sort out complex learning tasks, and Schema Theory - a learning theory of knowledge acquisition by humans. The what-to-learn aspect adopts an online active learning concept by virtue of an extended conflict and ignorance method, making gClass an incremental semi-supervised classifier, whereas the when-to-learn component makes use of the standard sample reserved strategy. A generalized version of the Takagi-Sugeno Kang (TSK) fuzzy system is devised to serve as the cognitive constituent. That is, the rule premise is underpinned by multivariate Gaussian functions, while the rule consequent employs a subset of the non-linear Chebyshev polynomial. Thorough empirical studies, confirmed by their corresponding statistical tests, have numerically validated the efficacy of gClass, which delivers better classification rates than state-of-the-art classifiers while having less complexity.

Software-defined carrier wireless networks

The telecommunication industry is entering a new era. The increased traffic demands imposed by the huge number of always-on connections require a quantum leap in the field of enabling techniques. Furthermore, subscribers expect ever increasing quality of experience with its joys and wonders, while network operators and service providers aim for cost-efficient networks. These requirements require a revolutionary change in the telecommunications industry, as shown by the success of virtualization in the IT industry, which is now driving the deployment and expansion of cloud computing. Telecommunications providers are currently rethinking their network architecture from one consisting of a multitude of black boxes with specialized network hardware and software to a new architecture consisting of “white box” hardware running a multitude of specialized network software. This network software may be data plane software providing network functions virtualization (NVF) or control plane software providing centralized network management — software defined networking (SDN). It is expected that these architectural changes will permeate networks as wide ranging in size as the Internet core networks, to metro networks, to enterprise networks and as wide ranging in functionality as converged packet-optical networks, to wireless core networks, to wireless radio access networks.

A game-theoretic resource allocation approach for intercell device-to-device communications in cellular networks

Device-to-Device (D2D) communication is a recently emerged disruptive technology for enhancing the performance of current cellular systems. To successfully implement D2D communications underlaying cellular networks, resource allocation to D2D links is a critical issue, which is far from trivial due to the mutual interference between D2D users and cellular users. Most of the existing resource allocation research for D2D communications has primarily focused on the intracell scenario while leaving the intercell settings not considered. In this paper, we investigate the resource allocation issue for intercell scenarios where a D2D link is located in the overlapping area of two neighboring cells. Specifically, We present three intercell D2D scenarios regarding the resource allocation problem. To address the problem, we develop a repeated game model under these scenarios. Distinct from existing works, we characterize the communication infrastructure, namely Base Stations (BSs), as players competing resource allocation quota from D2D demand, and we define the utility of each player as the payoff from both cellular and D2D communications using radio resources. We also propose a resource allocation algorithm and protocol based on the Nash equilibrium derivations. Numerical results indicate that the developed model not only significantly enhances the system performance including sum rate and sum rate gain, but also sheds lights on resource configurations for intercell D2D scenarios.