The proliferation of the Internet of Things (IoT) and embedded devices has ushered in a new generation of apps and programs to run on these devices. Unfortunately, new apps/programs can introduce cyber security vulnerabilities due to spurious information fl ows from untrusted sources, e.g., in-memory injection and other control hijacking attacks. Dynamic Information Flow Tracking (DIFT) techniques are a long-established approach to device behavioral analysis, but only for well-resourced, well-powered, full provenance computing systems. For resource constrained IoT and embedded devices, DIFT can be a prohibitive burden, and lightweight techniques have only recently begun to be investigated. This work proposes a lightweight, compiler-based DIFT system for IoT and embedded devices called CO-DIFT. CO-DIFT uses the LLVM compiler infrastructure as a framework, and security instructions are embedded directly into the executable code to prevent control fl ow attacks. Furthermore, to address the common use of heterogeneous devices in IoT, CO-DIFT is one of the few approaches designed to be machine-agnostic. The LLVM compiler infrastructure can be built and confi gured with any target machine or architecture as a hardware target that can support the storing and accessing tag memory operations. While full provenance DIFT systems show very large slowdowns, e.g., a FAROS 56x slowdown, CO-DIFT exhibits approximated slowdowns in the range 1.75x to 2.35x, drastically improving conditions for embedded IoT security operations.

Beyond 5G (B5G) networks are expected to be dense, heterogeneous wireless networks that coexist within a wide range of Radio Access Technologies (RATs). Conventional handover decision mechanisms do not capture the characteristic, parametric, and performance differences associated with each coexisting RAT in the multi-RAT network. Furthermore, a single base station does not provide the management processes required to organize the cross-RAT handover decision. Software-defined networking (SDN) has the potential to be effective for Multi-RAT handover algorithm implementation. In this work, we propose a Multiple Criteria Decision-Making (MCDM) based handover algorithm in SDN-based dense multi-RAT networks. The handover decision involves the calculation of entropy-based weights for each decision criterion. The candidate nodes are ranked using the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), which calculates the similarity of each alternative to the ideal possible and the worst possible alter-native and ranks them accordingly. The chosen case study uses Mininet WiFi to implement an SDN-controlled 5GIWIFi Multi-RAT environment and uses MCDM-based handover to optimize both RSSI and delay. Results show that the proposed MCDM-based handover improves the system throughput compared to sole RSSI-based handover, in all tested cases, by at least 18%, and there is at least 43 % reduction of handover failure.

For the next generation of wireless technologies, Orthogonal Frequency Division Multiplexing (OFDM) remains a key signaling technique. Peak-to-Average Power Ratio (PAPR) reduction must be included with OFDM to reduce the detrimental high PAPR exhibited by OFDM. The cost of PAPR reduction techniques stems from adding multiple IFFT iterations, which are computationally expensive and increase latency. We propose a novel PAPR Estimation Technique called PESTNet which reduces the necessary IFFT operations for PAPR reduction techniques by using deep learning to estimate the PAPR before the IFFT is applied. This paper gives a brief background on PAPR in OFDM systems and describes the PESTNet algorithm and the training methodologies. A case study of the estimation model is provided where results demonstrate PESTNet is able to give an accurate estimate of PAPR and can compute large batches of resource grids up to 10 times faster than IFFT based techniques.

In recent years, smart grid communications (SGC) has evolved to use new technologies not only for data delivery but also for enhanced smart grid (SG) security and reliability. Software Defined Networks (SDN) has proved to be a reliable and efficient architecture for handling diverse communication systems due to their ability to divide responsibilities of the network using control plane and data plane. This paper presents a graph learning approach for detecting and identifying Distributed Denial of Service (DDoS) attacks in SDN-SGC systems (GLASS). GLASS is a two phase framework that (1) detects if SDN-SGC is under DDoS attack using supervised graph deep learning and then (2) identifies the compromised entities using unsupervised learning methods. Network performance statistics are used for modeling SDN-SGC graphs, which train Graph Convolutional Neural Networks (GCN) to extract latent representations caused by DDoS attacks. Finally, spectral clustering is used to identify compromised entities. The experimental results, obtained by analysis of an IEEE 118-bus system, show the average throughput for compromised entities is able to maintain 84% of normal traffic level with GLASS, compared to achieving only 4% of normal throughput caused by DDoS attacks on compromised entities without the GLASS framework.

Over the past decade, online social networks (OSNs) such as Twitter and Facebook have thrived and experienced rapid growth to over 1 billion users. A major evolution would be to leverage the characteristics of OSNs to evaluate the effectiveness of the many routing schemes developed by the research community in real-world scenarios. In this demonstration, we showcase the Secure Opportunistic Schemes (SOS) middleware which allows different routing schemes to be easily implemented relieving the burden of security and connection establishment. The feasibility of creating a delay tolerant social network is demonstrated by using SOS to enable AlleyOop Social, a secure delay tolerant networking research platform that serves as a real-life mobile social networking application for iOS devices. AlleyOop Social allows users to interact, publish messages, and discover others that share common interests in an intermittent network using Bluetooth, peer-to-peer WiFi, and infrastructure WiFi.

In this paper, a game-theoretical framework for the design of distributed algorithms that control the transmission range (TR) of nodes in order to maximize throughput in Wireless Multihop Networks (WMN) is proposed. It is based on the stability region of the link-scheduling policy adopted for the network. The stability region is defined as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). The goal of the TR-control algorithms is to adapt the stability region to a given set of end-to-end flows. In the algorithms, the flows control distributively the nodes' TRs using the stability region in order to enable higher end-to-end packet rates while guaranteeing stability. In order to demonstrate how the algorithms can be designed using the proposed game-theoretical framework, a new TR-control algorithm for IEEE-802.16 WMNs is developed. Its convergence is demonstrated, and a performance bound is calculated. Finally, simulation results show that the algorithm is able to find the optimal TRs more effectively. The TRs achieve throughput levels that are at least 90 percent of the optimal throughput for 72 percent of the simulated scenarios, whereas the classic approach of spatial-reuse maximization does this for 62 percent of the scenarios.

UWB receivers based on energy detection (ED) are often an excellent choice for short-range wireless applications that require low-power and low-complexity architectures. However, this type of receiver is very sensitive to channel noise as well as inter-symbol (ISI) and inter-frame (IFI) interference caused by multipath fading. Therefore, the integration window becomes an important design parameter since the noise energy, ISI, and IFI are proportional to the integration time. This work presents analytical expressions that are corroborated with simulations to determine the optimal integration time of an ED receiver employing pulse-position modulation. The equations presented in this work are especially helpful when designing a system since they simplify calculations and trade-off decisions.

Modeling and estimating the primary user (PU) behavior is critical to implement dynamic spectrum access in cognitive radio networks. In this paper, we investigate the estimation accuracy of the PU behavior based on the Markov model. Maximum Likelihood (ML) estimation is employed to estimate the transition probabilities of the Markov model based on the sample sequence of PU idle/busy states. An approximate distribution of the ML estimator is derived to evaluate the estimation accuracy specified by the confidence level. To meet the requirement of estimation accuracy while reducing the unnecessary sensing time, we propose a learning algorithm which refines the estimation results iteratively. It dynamically estimates the required length of the sample sequence which is adaptive to the changing PU behavior. Numerical results show that the proposed estimation algorithm well tracks the variation of the PU behavior. Compared to the estimation method using fixed length of sample sequence, the proposed algorithm achieves the same requirement of the estimation accuracy with less number of samples.

Due to the size and density of small satellite networks (SSNs), the traditional clustering algorithms of large monolithic satellite networks are often limited. This paper proposes a novel distributed weight-based dominating set clustering algorithm to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. Firstly, a minimum dominating set is chosen as the candidate cluster head set based on their weight, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds.

A major challenge in wireless networks is the ability to maximize the throughput. High throughput in a wireless network requires a relatively low complex scheduling policy with a provable efficiency ratio, which is a measure of the performance of the policy in terms of throughput and stability. For most scheduling policies that achieve provable ratios, at the onset of every frame, a selection is made of a subset of links to transmit data in the immediately following frame. In this paper, we propose a policy that allows links to transmit data in any future frame by means of frame reservations. The new, reservation-based distributed scheduling approach will improve the capacity of the system and provide greater throughput. First, we create a framework to analyze the stability of reservation-based scheduling systems. Then, to demonstrate its efficacy, we propose a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks and use the new framework to find sufficient conditions for the stability of the network under this policy, i.e., we find a lower bound for its efficiency ratio. Finally, by means of simulation, we validate the mathematical analysis and compare the performance of our policy with nonreservation-based policies.

In this paper, we examine the tradeoff between fault tolerance capacity and protective (spare) wavelength utilization on a two-dimensional torus, which can be applied as a topological choice for the next-generation mission-critical Local Area Networks (LANs). The fault tolerance is enabled via applying a Four-way OptimaL Disjoint routing (FOLD) scheme to establish alternative (redundant) lightpaths. Along the spare wavelength utilization spectrum, four different Wavelength Allocation (WA) schemes, with varied spare resource demands, are studied and their wavelength efficiency in tolerating network failures is evaluated. The first WA scheme allocates no protective wavelength and hence provides zero fault tolerance capacity. The second and third WA schemes incorporate fault tolerance capability by enabling and allocating spare wavelengths, in a shared fashion, to redundant lightpaths at different levels of wavelength utilization. The fourth WA scheme allocates dedicated wavelengths to all alternative lightpaths such that no two redundant lightpaths need to share wavelength resources. A Monte-Carlo sampling assisted simulation on a 4×4 torus exhibits the performance-cost tradeoff and it is found that shared WA schemes achieve an appropriate balance between network reliability and spare resource utilization.

Non-coherent UWB receivers are often implemented using energy detection architectures which are very sensitive to noise in the channel and interference. Therefore, the receiver bandwidth plays an important role since the total noise and interference energy is proportional to this bandwidth. This work provides analytical expressions to find the optimal receiver bandwidth and quantifying the effect on the bit-error-rate (BER) due to channel noise and adjacent-channel interference (ACI). A reduction in receiver bandwidth beyond the optimal point is shown to have minimal impact on BER performance when ACI is negligible.

We investigate the channel assignment problem in a cluster-based multi-channel cognitive radio sensor network in this paper. Due to the inherent power and resource constraints of sensor networks, energy efficiency is the primary concern for network design. An R-coefficient is developed to estimate the predicted residual energy using sensor information (current residual energy and expected energy consumption) and channel conditions (primary user behavior). We examine three channel assignment approaches: Random pairing, Greedy channel search and Optimization-based channel assignment. The last two exploit R-coefficient to obtain a residual energy aware channel assignment solution. Simulation results show that R-coefficient-based approaches lead to better performance in terms of energy consumption and residual energy balance. Optimization-based channel assignment outperforms the other two approaches with respect to network lifetime.

In this paper, we study the problem of transmission power control and its effects on the link-scheduling performance when a set of end-to-end flows established in the network are given. This problem is approached by means of the stability region of the link-scheduling policy. The stability region is defined for link-scheduling policies as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). Specifically, the link-scheduling's stability region is adapted to the paths of the flows such that the flows are able to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of transmission power control based on queue stability has not been studied before. Based on this approach, we propose a transmission-power-control algorithm. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse.

High demands in data delivery latency and communication reliability encourage the use of fault-tolerance-enhanced all-optical WDM networks. Low latency is satisfied by setting up a direct lightpath between any communication pair to enable one-shot transmission. High reliability is met by establishing multiple disjoint lightpaths from the source to the destination. In this paper, we explore the fault-tolerance potential in circulant graphs, which offer good flexibility in the number of supported nodes and network connectivity. We propose a circulant-graph-based all-optical network architecture together with a fault-tolerant routing algorithm. Network resource utilization is analytically calculated and results show that increasing network connectivity helps reduce the required number of wavelengths for simultaneous all-node communications. A connection reliability model is developed combining both node and link failure effects. The reliability benefit obtained from the proposed algorithm grows almost linearly with network connectivity increase in a logarithmic scale.

Several distributed scheduling policies for wireless networks that achieve a provable efficiency ratio have been developed recently. These policies are characterized by the selection, at the onset of every time slot, of a subset of links according to the interference model of the network and the length of the links' queues. The selected subset of links is for the next time slot only. In this paper, we propose a new framework for the stability analysis of distributed scheduling policies that allow links to transmit data packets in any future time slots by means of slot reservations. Within this framework, we propose and analyze a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks. We find sufficient conditions for the stability of the network when the traffic uses one hop. Specifically, we prove a lower bound for its efficiency ratio by evaluating the stability conditions obtained from our proposed framework. Finally, we compare this lower bound with the capacity achieved in simulation results.

In this paper, we focus on the design and analysis of a torus-based backbone architecture which targets to meet both the low delay and high reliability requirements of avionic time-critical communications. Reliable optical connection between arbitrary source-destination pairs is proposed by enabling four non-overlapping lightpaths between the source and destination, which makes the network tolerant to at least three arbitrary link failures without losing connectivity. A greedy algorithm is introduced to set up the four non-overlapping lightpaths with the aim of maximizing two-terminal reliability (TTR), as well as minimizing signal attenuation and propagation delay. A wavelength assignment and reuse (WAR) method is used to reduce by half the wavelength requirement for all-to-all communication in a case study of 4 times 4 torus. Both probabilistic analysis and a packet-level simulation reveal that the proposed architecture can provide efficient communication with a 3-fault reliability guarantee.

Security plays an important role in the ability to deploy and retrieve trustworthy data from a wireless sensor network. Location verification is an effective first line of defense against attacks which take advantage of a lack, or compromise, of location information. In this work, a probabilistic approach to location verification in dense sensor networks is proposed. The proposed Probabilistic Location Verification (PLV) algorithm leverages the probabilistic dependence of the number of hops a broadcast packet traverses to reach a destination and the Euclidean distance between source and destination. A small number of verifier nodes determine the plausibility of the claimed location, which is represented by a real number between zero and one. Using the calculated plausibility metric, it is possible to create arbitrary number of trust levels in the location claimed. Simulation studies verify that the proposed solution provides high performance in face of various types of attacks.

Recent advancements of microelectronics and network protocol research enable the application of wireless sensor network in both industry and home environments. Reliability issues play a vital role to ensure the quality of service of these applications. To maximize the reliability of such a network is a both a worthy goal and a significant challenge, while maintaining the detection and response capabilities. In this paper, we examine the tradeoffs of enhancing the reliability of wireless sensor network using the ZigBee network as an example and we propose our measures to boost the reliability of the network

Wireless networks require strong security mechanisms due to their open medium. However, security effects system performance, and therefore impacts quality of service (QoS) of communications. To analyze the impact of security on system performance, we conduct a detailed experimental study on a wireless IP testbed with security at different layers. We study their impact on different types of data streams such as TCP and UDP with regard to authentication time and cryptographic overhead. Specifically, we experiment with the most widely used security protocols such as WEP, IPsec, 802.1x with RADIUS, and SSL. We classify security protocols into individual and hybrid policies. Then, a new metric, relative security index, is introduced to analyze security strength and overhead tradeoffs quantitatively. Our results demonstrate that the stronger the security, the more signaling and delay overhead; whereas, the overhead does not necessarily increase monotonically with the security strength. Also, we notice that authentication time is a more significant factor than cryptographic cost regarding their contributions towards QoS degradation in wireless networks.

Future wireless networks must be able to coordinate services within a diverse network environment. One of the most challenging problems for coordination is vertical handoff, which is the decision for a mobile node to handoff between different types of networks. While traditional handoff is based on received signal strength comparisons, vertical handoff must evaluate additional factors, such as, monetary cost, offered services, network conditions, and user preferences. In this paper, several optimizations are proposed for the execution of vertical handoff decision algorithms, with the goal of maximizing the quality of service experienced by each user. First, the concept of policy-based handoffs is discussed. Then, a cost function is defined to judge target networks based on a variety of user- and network-valued metrics. Finally, a performance analysis demonstrates that significant gains in quality of service and a more efficient use of resources can he achieved from the proposed optimizations.

Next-generation wireless communication is based on a global system of fixed and wireless mobile services that are transportable across different network backbones, network service providers, and network geographical boundaries. One of the most important problems for global wireless service is handoff management. In this paper, a new handoff technique is introduced which supports mobility between dissimilar networks. First, the system architecture is described, based on the concept of a boundary cell region between networks. Then a new inter-system handoff protocol is presented that uses boundary cells that allow the mobile terminal to roam into a different network. The performance of the protocol is analyzed in terms of the additional inter-system handoff signaling time and the minimum boundary cell area threshold for a successful transition within the prescribed time constraints.

Mobile satellite systems are a crucial component of the future global telecommunications infrastructure. An important aspect of the future system is to manage the location of both users and satellites. This paper presents a strategy for location registration (update) and paging in low Earth orbit (LEO) mobile satellite systems. First, we discuss the tradeoff that exists between four proposed satellite location area designations. Then we introduce a scheme that selects a simple location area design and uses a hierarchical database architecture to reduce the location management signaling delay. The performance of the scheme is analyzed in terms of the paging bandwidth and the location update signaling delay. Finally, we present the numerical results for several planned systems, such as GlobalStar, ICO, and IRIDIUM.

This paper describes current and proposed protocols for mobility management for public land mobile network (PLMN)-based networks, mobile Internet protocol (IP) wireless asynchronous transfer mode (ATM) and satellite networks. The integration of these networks will be discussed in the context of the next evolutionary step of wireless communication networks. First, a review is provided of location management algorithms for personal communication systems (PCS) implemented over a PLMN network. The latest protocol changes for location registration and handoff are investigated for mobile IP followed by a discussion of proposed protocols for wireless ATM and satellite networks. Finally, an outline of open problems to be addressed by the next generation of wireless network service is discussed.