We transform the 3D underwater sensor network (USN) localization problem into its 2D counterpart by employing sensor depth information and a simple projection technique. We first prove that a nondegenerative projection preserves network localizability. We then prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed bilateration localization scheme for 3D USNs termed as Underwater Sensor Positioning (USP). Through extensive simulations, we show that USP has the following nice features: 1) improved localization capabilities over existing 3D methods, 2) low storage and computation requirements, 3) predictable and balanced communication overhead, and 4) robustness to errors from the underwater environment.

Motivated by the observation that channel assignment for multiradio multi-channel mesh networks should support both unicast and local broadcast 1 , should be interference-aware, and should result in low overall switching delay, high throughput, and low overhead, we propose two flexible localized channel assignment algorithms based on s-disjunct superimposed codes. These algorithms support the local broadcast and unicast effectively, and achieve interference-free channel assignment under certain conditions. In addition, under the primary interference constraints 2 , the channel assignment algorithm for unicast can achieve 100% throughput with a simple scheduling algorithm such as the maximal weight independent set scheduling, and can completely avoid hidden/exposed terminal problems under certain conditions. Our algorithms make no assumptions on the underlying network and therefore are applicable to a wide range of MR-MC mesh network settings. We conduct extensive theoretical performance analysis to verify our design.

Mobile IP has been developed to handle mobility of Internet hosts at the network layer. Mobile IP, however, suffers from a number of drawbacks such as requirement of infrastructure change, high handover latency, high packet loss rate, and conflict with network security solutions. In this paper, we describe and evaluate the performance of SIGMA, a Seamless IP diversity based Generalized Mobility Architecture. SIGMA utilizes multihoming to achieve a seamless handover of a mobile host, and is designed to solve many of the drawbacks of Mobile IP, including requirement for changes in infrastructure. We first evaluate the signaling cost of SIGMA and compare with that of Hierarchical Mobile IPv6 (an enhancement of Mobile IP) by analytical modeling, followed by comparison of handover performance of SIGMA and Mobile IPv6 enhancements. Criteria for performance evaluation include handover latency, packet loss, throughput, and network friendliness. Our results indicate that in most cases SIGMA has a lower signaling cost than Hierarchical Mobile IPv6. Moreover, for a typical network configuration, SIGMA has a higher handover performance over Mobile IP.

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One of the most challenging network security concerns for network administrators is the presence of rogue access points. Rogue access points, if undetected, can be an open door to sensitive information on the network. Many data raiders have taken advantage of the undetected rogue access points in enterprises to not only get free Internet access, but also to view confidential information. Most of the current solutions to detect rouge access points are not automated and are dependent on a specific wireless technology. In this paper, we present a rogue access point detection approach. The approach is an automated solution which can be installed on any router at the edge of a network. The main premise of our approach is to distinguish authorized WLAN hosts from unauthorized WLAN hosts connected to rogue access points by analyzing traffic characteristics at the edge of a network. Simulation results verify the effectiveness of our approach in detecting rogue access points in a heterogeneous network comprised of wireless and wired subnets.

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The Internet of Things (IoT) is a significant branch of the ongoing advances in the Internet and mobile communications. Yet, the use of a large number of IoT devices can severely worsen the spectrum scarcity problem. The usable spectrum resources are almost entirely occupied, and thus, the increasing demands of radio access from IoT devices cannot be met. To tackle this problem, the Cognitive Internet of Things (CIoT) has been proposed. In a CIoT network, secondary users, i.e., sensors and actuators, can access the licensed spectrum bands provided by licensed primary users (such as cellular telephones). Security is a major concern in CIoT networks. However, the traditional encryption method at upper layers (such as symmetric and asymmetric ciphers) may not be suitable for CIoT networks since these networks are composed of low-profile devices. In this paper, we address the security issues in spectrum-leasing-based CIoT networks using physical layer methods. Considering that the CIoT networks are cooperative in nature, we propose to employ cooperative jamming to achieve secure transmission. In our proposed cooperative jamming scheme, a certain secondary user is employed as the helper to harvest energy transmitted by the source and then uses the harvested energy to generate an artificial noise that jams the eavesdropper without interfering with the legitimate receivers. The goal is to minimize the Signal to Interference plus Noise Ratio (SINR) at the eavesdropper subject to the Quality of Service (QoS) constraints of the primary traffic and the secondary traffic. We formulate the minimization problem into a two-stage robust optimization problem based on the worst-case Channel State Information of the Eavesdropper (ECSI). By using Semi-Definite Programming (SDP), the optimal solutions of the transmit covariance matrices can be obtained. Moreover, in order to build an incentive mechanism for the secondary users, we propose an auction framework based on the cooperative jamming scheme. The proposed auction framework jointly formulates the helper selection and the corresponding energy allocation problems under the constraint of the eavesdropper's SINR. By adopting the Vickrey auction, truthfulness and individual rationality can be achieved. Simulation results demonstrate the effective performance of the cooperative jamming scheme and the auction framework.