Abstract

Motivated by the increasing importance of edge computing and improvements in heterogeneous low-power, wimpy systems, we present a novel time-energy-cost analysis of wimpy edge computing in comparison with traditional brawny cloud computing. For this analysis, we use a brawny heterogeneous Amazon EC2 cloud instance with GPU and two wimpy heterogeneous systems represented by Jetson TK1 and Jetson TX1. As the paradigm shift to edge computing is due to the challenges of Big Data processing, we select six representative MapReduce applications with applicability in IoT edge computing. Using our time-energy-cost analysis of both wimpy edge compute nodes and cloud computing systems with GPUs, we present several key insights. Firstly, we advocate the usage of heterogeneous systems with GPU on both edge and cloud since they provide time-energy savings of up to 70% for compute-intensive applications. Secondly, we establish an equivalence ratio between one brawny cloud instance and multiple wimpy edge nodes that achieve the same or better time performance. Based on this equivalence ratio, we show that using wimpy systems as edge computing devices saves cost compared to using traditional cloud computing. Lastly, counter-to-intuition, our analysis shows that the latest Jetson TX1 system exhibits worse time-cost performance compared to the older Jetson TK1 system. This result stems from lower operating core clock frequency and lower instructions-per-cycle of Jetson TX1's GPU on some compute-intensive applications.

Abstract

With an increasing number of cybersecurity attacks due to insider threats, it is important to identify different attack mechanisms and quantify them to ease threat mitigation. We propose a discrete-event simulation model to study the impact of unintentional insider threats on the overall system security by representing time-varying human behavior using two parameters, user vulnerability and user interactions. In addition, the proposed approach determines the futuristic impact of such behavior on overall system health. We illustrate the ease of applying the proposed simulation model to explore several ”what-if” analysis for an example enterprise system and derive the following useful insights, (i) user vulnerability has a bigger impact on overall system health compared to user interactions, (ii) the impact of user vulnerability depends on the system topology, and (ii) user interactions increases the overall system vulnerability due to the increase in the number of attack paths via credential leakage.

Abstract

The transition to a “smart city” necessitates an increase in interdependencies between critical infrastructures and information technologies. Moreover, such interdependencies are across multiple domains. However, these interdependencies expose critical infrastructures to cybersecurtiy threats. Furthermore, the availability of domain-specific simulators everywhere motivates the need for federation of interoperable cybersecurity and cyberphysical testbeds to validate cybersecurity threat resiliency. This paper presents some key issues and challenges in accomplishing such a federation of testbeds. While there are multiple modeling and simulation approaches in specific domains, none of these works address the challenges of federating across multiple domains such as federation between cyberphysical testbed and cybersecurity testbed to enable validation of cybersecurity resilience. We outline a reference architecture, DEFT (feDerate tEstbeds For cybersecuriTy) with design considerations that stem from the key issues highlighted.

Abstract

In this paper, we consider a wireless co-operative network involving two transceiver nodes whose communication is aided by energy-constrained two-way relay nodes. Each relay node employs a non-regenerative relaying protocol. The transceiver nodes can simultaneously transmit information and energy and the relay nodes harvest the energy from the received signal and use the harvested energy to amplify and retransmit the signal to the destination. The relay nodes implement power- splitting (PS) scheme to apportion the received signal power to the information processing and the energy harvesting units. We address the problem of sum-rate maximization under constraints on total transmit power and harvested energy. We propose an optimal resource allocation and relay selection scheme as well as a reduced-complexity suboptimal scheme. The performance of the proposed solutions are illustrated by numerical simulations.

Abstract

In this paper, we consider a cooperative wireless network involving two transceiver nodes whose communication is assisted by energy-constrained two-way amplify-and-forward (AF) relay nodes. The transceiver nodes can simultaneously transmit information and energy, and the relay nodes harvest the energy from the received signal and use the harvested energy to amplify and retransmit the received signal to the transceiver nodes. We consider a power splitting-based relaying (PSR) protocol as well as a time switching-based relaying (TSR) protocol to effect simultaneous extraction of information and harvesting of energy at the relay. We address the problem of sum-rate maximization under constraints on the total transmit power and the harvested energy in both scenarios. In order to solve this problem, we propose an optimal resource allocation and relay selection scheme. The performance of the proposed PSR and TSR protocols is illustrated by numerical simulations.

Abstract

In this paper, we consider the problem of hybrid multi-input multi-output (MIMO) transceiver design for a non regenerative hybrid two-way amplify-forward (AF) relay based millimeter wave (mmWave) communication system. We propose two low complexity mmWave system designs based on the quality of available channel state information (CSI). We first propose the design of transceivers and a two- way AF relay, by minimizing sum-mean square error (SMSE) under the constraint of total relay transmit power while assuming the perfect channel knowledge. We later extend it to a robust design under the assumption that the transceivers posses only imperfect information about the channel state, where the CSI error is assumed to follow the Gaussian distribution. In both the designs, reduced hardware complexity (introduced due to large number of antenna elements in mmWave system) is achieved by analog-digital hybrid processing by using orthogonal matching pursuit (OMP)-based sparse signal processing. We present numerical results on the performance of both the designs over various dictionaries. The comparison results show that robust design is resilient to the presence of CSI errors. Furthermore, we also demonstrate the convergence of both the proposed algorithms to a limit even though global convergence is hard to prove due to non convex nature of overall optimization problem.

Abstract

In this paper, we present the design of optimal precoders and receive filters for a full-duplex (FD) two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying system in a cognitive radio network. The secondary user (SU) or cognitive nodes share the spectrum with the licensed primary user (PU) nodes while keeping the interference to PU nodes below a threshold. The cognitive transceivers communicate with each other with the assistance of a cognitive AF relay. The precoders for the cognitive transceivers are designed so as to maximize the signal to noise ratio (SNR) at the relay while limiting the interference to the PU node below a specified threshold. Due to FD mode of operation, all the nodes suffer from self-interference (SI). We assume the available channel state information (CSI) of loopback self-interference channels at relay and transceivers to be imperfect. We design the optimal relay precoder and transceiver receive filter, for suppressing the residual SI, by minimizing the sum of mean square error (SMSE) at the cognitive transceivers with constraint on transmit power at relay. The precoders and receive filters are updated at each time slot, taking into account the cumulative interference effect from all previous time slots, which enhances the performance of the system over time. The simulation results illustrate the effectiveness of the proposed design in terms of the achievable sum-rate.

Abstract

In this paper, we consider optimal transceiver design and relay selection for simultaneous transfer of data and energy in a cooperative network consisting of amplify-and-forward (AF) relays. In this context, we address two different problems and propose optimal relay selection and transceiver processing. Furthermore, the problems are formulated for both time switching (TS) and power splitting (PS) schemes. The first problem is the maximization of overall rate while ensuring a minimum harvested energy at the receiver. For this problem, we perform computations of optimal fractions to distribute the received signal corresponding to TS and PS schemes, the relay weighing coefficients, and optimal relay selection. In the second problem, optimal resource allocation for maximizing the overall harvested energy at the user under constraints on the minimum achievable rate has been formulated. For this problem, we propose a suitable solution to meet the requirements for both TS and PS. For both the problems, we obtain a closed form solution. Finally, the performance of proposed design under various operating conditions and parameter values are illustrated with a comparison between TS and PS schemes.

Abstract

Noise power uncertainty is a major issue in detectors for spectrum sensing. Any uncertainty in the noise power leads to significant reduction in the detection performance of the energy detector and also results in a performance limitation in the form of SNR walls. In this paper, we propose an evidence theory (also called Dempster-Shafer theory (DST)) based cooperative energy detection (CED) for spectrum sensing. The noise variance is modeled as a random variable with a known distribution. The analyzed system model is similar to a distributed parallel detection network where each secondary user (SU) evaluates the energy from its received signal samples and sends it to a fusion center (FC), which makes the final decision. However, in the proposed DST-based CED scheme, the SUs sends computed belief-values instead of actual energy value to the FC. Any uncertainty in the noise variance is accounted for by discounting the belief values based on the amount of uncertainty associated with each SU. Finally, the discounted belief values are combined using Dempster rule to reach at a global decision. Simulation results indicate that the proposed DST scheme significantly improves the detection probability at low average signal-to-noise ratio (ASNR) in comparison to the traditional sum fusion rule in the presence of noise uncertainty.

Abstract

In this paper, we consider the design of low-complexity analog-digital hybrid transceivers for a multi-input multi- output (MIMO) millimeter wave (mmWave) communication system operating in a K-user interference channel. Our objective is to achieve the energy efficiency by minimizing overall transmit power required for achieving a target mean- square error (MSE) at the receivers. We propose two transceiver designs based on the quality of the available channel state information (CSI). We first present a design that minimizes total transmit power assuming the availability of perfect channel knowledge. Later, we extend it to a robust transceiver design by considering imperfections in CSI. The proposed designs achieve reduced hardware and computational complexity by forming hybrid architecture using sparse signal processing. Hence, achieving similar MSE with lower energy consumption. We evaluate the performance of both the proposed schemes based on various parameters. Furthermore, we demonstrate the resilience of the robust design in presence of errors in CSI and performance of both the designs with various dictionaries.