arXiv subjects

Jemin Lee

Publications and source records attributed to Jemin Lee.

At least 37 records · Page 2Linked to original sources

arXiv2023

Ensuring End-to-End Security with Fine-grained Access Control for Connected and Autonomous Vehicles

As advanced V2X applications emerge in the connected and autonomous vehicle (CAV), the data communications between in-vehicle end-devices and outside nodes increase, which make the end-to-end (E2E) security to in-vehicle end-devices as the urgent issue to be handled. However, the E2E security with fine-grained access control still remains as a challenging issue for resource-constrained end-devices since the existing security solutions require complicated key management and high resource consumption. Therefore, we propose a practical and secure vehicular communication protocol for the E2E security based on a new attribute-based encryption (ABE) scheme. In our scheme, the outsourced computation is provided for encryption, and the computation cost for decryption constantly remains small, regardless of the number of attributes. The policy privacy can be ensured by the proposed ABE to support privacy-sensitive V2X applications, and the existing identity-based signature for outsourced signing is newly reconstructed. Our scheme achieves the confidentiality, message authentication, identity anonymity, unlinkability, traceability, and reconfigurable outsourced computation, and we also show the practical feasibility of our protocol via the performance evaluation.

cs.CR↗

arXiv2023

Joint Service Caching and Computing Resource Allocation for Edge Computing-Enabled Networks

In this paper, we consider the service caching and the computing resource allocation in edge computing (EC) enabled networks. We introduce a random service caching design considering multiple types of latency sensitive services and the base stations (BSs)' service caching storage. We then derive a successful service probability (SSP). We also formulate a SSP maximization problem subject to the service caching distribution and the computing resource allocation. Then, we show that the optimization problem is nonconvex and develop a novel algorithm to obtain the stationary point of the SSP maximization problem by adopting the parallel successive convex approximation (SCA). Moreover, to further reduce the computational complexity, we also provide a low complex algorithm that can obtain the near-optimal solution of the SSP maximization problem in high computing capability region. Finally, from numerical simulations, we show that proposed solutions achieve higher SSP than baseline schemes. Moreover, we show that the near-optimal solution achieves reliable performance in the high computing capability region. We also explore the impacts of target delays, a BSs' service cache size, and an EC servers' computing capability on the SSP.

cs.NI↗

arXiv2022

Average Age of Information Penalty of Short-Packet Communications with Packet Management

In this paper, we analyze the non-linear age of information (AoI) performance in a point-to-point short packet communication system, where a transmitter generates packets based on status updates and transmits the packets to a receiver. Specifically, we investigate three packet management strategies, namely, the non-preemption with no buffer strategy, the non-preemption with one buffer strategy, and the preemption strategy. To characterize the level of the receiver's dissatisfaction on outdated data, we adopt a generalized α-βAoI penalty function into the analysis and derive closed-form expressions for the average AoI penalty achieved by the three packet management strategies. Simulation results are used to corroborate our analysis and explicitly evaluate the impact of various system parameters, such as the coding rate and status update generation rate, on the AoI performance. Additionally, we find that the value of αreflects the system transmission reliability.

cs.IT↗

arXiv2022

CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution

Mobile devices run deep learning models for various purposes, such as image classification and speech recognition. Due to the resource constraints of mobile devices, researchers have focused on either making a lightweight deep neural network (DNN) model using model pruning or generating an efficient code using compiler optimization. Surprisingly, we found that the straightforward integration between model compression and compiler auto-tuning often does not produce the most efficient model for a target device. We propose CPrune, a compiler-informed model pruning for efficient target-aware DNN execution to support an application with a required target accuracy. CPrune makes a lightweight DNN model through informed pruning based on the structural information of subgraphs built during the compiler tuning process. Our experimental results show that CPrune increases the DNN execution speed up to 2.73x compared to the state-of-the-art TVM auto-tune while satisfying the accuracy requirement.

cs.LG↗

arXiv2022

Quantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment

To adopt convolutional neural networks (CNN) for a range of resource-constrained targets, it is necessary to compress the CNN models by performing quantization, whereby precision representation is converted to a lower bit representation. To overcome problems such as sensitivity of the training dataset, high computational requirements, and large time consumption, post-training quantization methods that do not require retraining have been proposed. In addition, to compensate for the accuracy drop without retraining, previous studies on post-training quantization have proposed several complementary methods: calibration, schemes, clipping, granularity, and mixed-precision. To generate a quantized model with minimal error, it is necessary to study all possible combinations of the methods because each of them is complementary and the CNN models have different characteristics. However, an exhaustive or a heuristic search is either too time-consuming or suboptimal. To overcome this challenge, we propose an auto-tuner known as Quantune, which builds a gradient tree boosting model to accelerate the search for the configurations of quantization and reduce the quantization error. We evaluate and compare Quantune with the random, grid, and genetic algorithms. The experimental results show that Quantune reduces the search time for quantization by approximately 36.5x with an accuracy loss of 0.07 ~ 0.65% across six CNN models, including the fragile ones (MobileNet, SqueezeNet, and ShuffleNet). To support multiple targets and adopt continuously evolving quantization works, Quantune is implemented on a full-fledged compiler for deep learning as an open-sourced project.

cs.LG↗

arXiv2022

Facing to Latency of Hyperledger Fabric for Blockchain-enabled IoT: Modeling and Analysis

Hyperledger Fabric (HLF), one of the most popular private blockchains, has recently received attention for blockchain-enabled Internet of Things (IoT). However, for IoT applications to handle time-sensitive data, the processing latency in HLF has emerged as a new challenge. In this article, therefore, we establish a practical HLF latency model for HLF-enabled IoT. We first discuss the structure and transaction flow of HLF-enabled IoT. After implementing real HLF, we capture the latencies that each transaction experiences and show that the total latency of HLF can be modeled as a Gamma distribution, which is validated by conducting a goodness-of-fit test (i.e., the Kolmogorov-Smirnov (KS) test). We also provide the parameter values of the modeled latency distribution for various HLF environments. Furthermore, we explore the impacts of three important HLF parameters including transaction generation rate, block size, and block-generation timeout on the HLF latency. As a result, this article provides design insights on minimizing the latency for HLF-enabled IoT.

cs.DC↗

arXiv2021

Energy-efficient Cooperative Offloading for Edge Computing-enabled Vehicular Networks

Edge computing technology has great potential to improve various computation-intensive applications in vehicular networks by providing sufficient computation resources for vehicles. However, it is still a challenge to fully unleash the potential of edge computing in edge computing-enabled vehicular networks. In this paper, we develop the energy-efficient cooperative offloading scheme for edge computing-enabled vehicular networks, which splits the task into multiple subtasks and offloads them to different roadside units (RSUs) located ahead along the route of the vehicle. We first establish novel cooperative offloading models for the offline and online scenarios in edge computing-enabled vehicular networks. In each offloading scenario, we formulate the total energy minimization with respect to the task splitting ratio, computation resource, and communication resource. In the offline scenario, we equivalently transform the original problem to a convex problem and obtain optimal solutions for multi-vehicle case and single-vehicle case, respectively. Furthermore, we show that the method proposed for the offline scenario can also be applied to solve the optimization problem in the online scenario. Finally, through numerical results, by analyzing the impact of network parameters on the total energy consumption, we verify that our proposed solution consumes lower energy than baseline schemes.

eess.SP↗

arXiv2021

Non-Terrestrial Networks for UAVs: Base Station Service Provisioning Schemes with Antenna Tilt

By focusing on unmanned aerial vehicle (UAV) communications in non-terrestrial networks (NTNs), this paper provides a guideline on the appropriate base station (BS) service provisioning scheme with considering the antenna tilt angle of BS. Specifically, two service provisioning schemes are considered including the inclusive-service BS (IS-BS) scheme, which makes BSs serve both ground users (GUs) and aerial users (AUs) (i.e., UAVs) simultaneously, and the exclusive-service BS (ES-BS) scheme, which has BSs for GUs and BSs for AUs. By considering the antenna tilt angle-based channel gain, we derive the network outage probability for both IS-BS and ES-BS schemes, and show the existence of the optimal tilt angle that minimizes the network outage probability after analyzing the conflict impact of the antenna tilt angle. We also analyze the impact of various network parameters, including the ratio of GUs to total users and densities of total and interfering BSs, on the network outage probability. Finally, we analytically and numerically show in which environments each service provisioning scheme can be superior to the other one.

eess.SP↗

arXiv2021

Precoding Design for Multi-user MIMO Systems with Delay-Constrained and -Tolerant Users

In both academia and industry, multi-user multiple-input multiple-output (MU-MIMO) techniques have shown enormous gains in spectral efficiency by exploiting spatial degrees of freedom. So far, an underlying assumption in most of the existing MU-MIMO design has been that all the users use infinite blocklength, so that they can achieve the Shannon capacity. This setup, however, is not suitable considering delay-constrained users whose blocklength tends to be finite. In this paper, we consider a heterogeneous setting in MU-MIMO systems where delay-constrained users and delay-tolerant users coexist, called a DCTU-MIMO network. To maximize the sum spectral efficiency in this system, we present the spectral efficiency for delay-tolerant users and provide a lower bound of the spectral efficiency for delay-constrained users. We consider an optimization problem that maximizes the sum spectral efficiency of delay-tolerant users while satisfying the latency constraint of delay-constrained users, and propose a generalized power iteration (GPI) precoding algorithm that finds a principal precoding vector. Furthermore, we extend a DCTU-MIMO network to the multiple time slots scenario and propose a recursive generalized power iteration precoding algorithm. In simulation results, we prove proposed methods outperform baseline schemes and present the effect of network parameters on the ergodic sum spectral efficiency.

eess.SP↗

arXiv2021

Ensuring Data Freshness for Blockchain-enabled Monitoring Networks

The age of information (AoI) is a recently proposed metric for quantifying data freshness in real-time status monitoring systems where timeliness is of importance. In this paper, the problem of characterizing and controlling the AoI is studied in the context of blockchain-enabled monitoring networks (BeMN). In BeMN, status updates from sources are transmitted and recorded in a blockchain. To investigate the statistical characteristics of the AoI in BeMN, the transmission latency and the consensus latency are first rigorously modeled. Then, the average AoI, the AoI violation probability, and the peak AoI violation probability are derived in a closed form so as to quantify the performance of BeMN. Furthermore, a simplified form is derived for the AoI violation probability, and it is shown that this quantity can capture the upper or lower bound of the actual AoI violation probability. Simulation results show that each BeMN parameters (i.e., target successful transmission probability, block size, and timeout) can have conflicting effects on the AoI-related performance. Subsequently, design insights are provided to maintain the freshness of the status data in BeMN. Then, experimental results with a real Hyperledger Fabric platform further validate the accuracy of our modeling and analysis.

eess.SP↗

arXiv2021

Securing Fresh Data in Wireless Monitoring Networks: Age-of-Information Sensitive Coverage Perspective

With the development of IoT, the sensor usage has been elevated to a new level, and it becomes more crucial to maintain reliable sensor networks. In this paper, we provide how to efficiently and reliably manage the sensor monitoring system for securing fresh data at the data center (DC). A sensor transmits its sensing information regularly to the DC, and the freshness of the information at the DC is characterized by the age of information (AoI) that quantifies the timeliness of information. By considering the effect of the AoI and the spatial distance from the sensor on the information error at the DC, we newly define an error-tolerable sensing (ETS) coverage as the area that the estimated information is with smaller error than the target value. We then derive the average AoI and the AoI violation probability of the sensor monitoring system, and finally present the η-coverage probability, which is the probability that the ETS coverage is greater than η ratio of the maximum sensor coverage. We also provide the optimal transmission power of the sensor, which minimizes the average energy consumption while guaranteeing certain level of the η-coverage probability. Numerical results validate the theoretical analysis and show the tendency of the optimal transmission power according to the maximum number of retransmissions. This paper can pave the way to efficient design of the AoI-sensitive sensor networks for IoT.

eess.SY↗

arXiv2020

Base Station Coordination Scheme for Multi-tier Ultra-dense Networks

In this paper, we consider a relative received link power (RRLP)-based coordinated multi-point (CoMP) joint transmission (JT) in the multi-tier ultra-dense networks (UDN). In this CoMP scheme, we identify the cooperating base stations (BSs) by comparing the average received link power (ARLP) of the neighbouring BSs with respect to the BS having the strongest ARLP (i.e., the main link BS) to a user. To analyze the performance of this CoMP scheme in the downlink multi-tier UDN, we first approximate the received signal power distribution, and derive the coverage probability using stochastic geometry. After revisiting the area spectral efficiency (ASE) to make it more suitable for CoMP transmission in UDN, we also analyze the ASE and the network energy efficiency (NEE). Using simulations, we validate the derived coverage probability, and investigate the CoMP performance in multi-tier UDN. Our simulations show that the RRLP-based CoMP scheme can outperform the fixed number of strongest BS-based CoMP scheme in the high BS density regime. Our study of the NEE performance reveals that not only the RRLP-based CoMP scheme is more efficient than conventional non-CoMP transmission scenario, but also its NEE performance improves with the average number of cooperating BSs.

cs.IT↗

arXiv2020

Securing Communications with Friendly Unmanned Aerial Vehicle Jammers

In this paper, we analyze the impact of a friendly unmanned aerial vehicle (UAV) jammer on UAV communications in the presence of multiple eavesdroppers. We first present channel components determined by the line-of-sight (LoS) probability between the friendly UAV jammer and the ground device, and introduce different channel fadings for LoS and non-line-of-sight (NLoS) links. We then derive the secrecy transmission probability satisfying both constraints of legitimate and wiretap channels. We also analyze the secrecy transmission probability in the presence of randomly distributed multiple friendly UAV jammers. Finally, we show the existence of the optimal UAV jammer location, and the impact of the density of eavesdroppers, the transmission power of the UAV jammer, and the density of UAV jammers on the optimal location.

eess.SP↗

arXiv2020

EC-SVC: Secure CAN Bus In-Vehicle Communications with Fine-grained Access Control Based on Edge Computing

In-vehicle communications are not designed for message exchange between the vehicles and outside systems originally. Thus, the security design of message protection is insufficient. Moreover, the internal devices do not have enough resources to process the additional security operations. Nonetheless, due to the characteristic of the in-vehicle network in which messages are broadcast, secure message transmission to specific receivers must be ensured. With consideration of the facts aforementioned, this work addresses resource problems by offloading secure operations to high-performance devices, and uses attribute-based access control to ensure the confidentiality of messages from attackers and unauthorized users. In addition, we reconfigure existing access control based cryptography to address new vulnerabilities arising from the use of edge computing and attribute-based access control. Thus, this paper proposes an edge computing-based security protocol with fine-grained attribute-based encryption using a hash function, symmetric-based cryptography, and reconfigured cryptographic scheme. In addition, this work formally proves the reconfigured cryptographic scheme and security protocol, and evaluates the feasibility of the proposed security protocol in various aspects using the CANoe software.

cs.CR↗

arXiv2020

Age of Information Analysis in Hyperledger Fabric Blockchain-enabled Monitoring Networks

Age of information (AoI) is a recently proposed metric for quantifying data freshness in real-time status monitoring systems where timeliness is of importance. In this paper, we explore the data freshness in the Hyperledger Fabric Blockchain-enabled monitoring network (HeMN) by leveraging the AoI metric. In HeMN, status updates from sources are transmitted through an uplink and recorded in a Hyperledger Fabric (HLF) network. To provide a stochastic guarantee of data freshness, we derive a closed-form of AoI violation probability by considering the transmission latency and the consensus latency. Then, we validate our analytic results through the implemented HLF platform. We also investigate the effect of the target successful transmission probability (STP) on the AoI violation probability.

eess.SP↗

arXiv2020

Is Blockchain Suitable for Data Freshness? -- Age-of-Information Perspective

Recent advances in blockchain have led to a significant interest in developing blockchain-based applications. While data can be retained in blockchains, the stored values can be deleted or updated. From a user viewpoint that searches for the data, it is unclear whether the discovered data from the blockchain storage is relevant for real-time decision-making process for blockchain-based application. The data freshness issue serves as a critical factor especially in dynamic networks handling real-time information. In general, transactions to renew the data require additional processing time inside the blockchain network, which is called ledger-commitment latency. Due to this problem, some users may receive outdated data. As a result, it is important to investigate if blockchain is suitable for providing real-time data services. In this article, we first describe blockchain-enabled (BCE) networks with Hyperledger Fabric (HLF). Then, we define age of information (AoI) of BCE networks and investigate the influential factors in this AoI. Analysis and experiments are conducted to support our proposed framework. Lastly, we conclude by discussing some future challenges.

cs.DC↗

arXiv2020

Mobile Edge Computing-Enabled Heterogeneous Networks

The mobile edge computing (MEC) has been introduced for providing computing capabilities at the edge of networks to improve the latency performance of wireless networks. In this paper, we provide the novel framework for MEC-enabled heterogeneous networks (HetNets), composed of the multi-tier networks with access points (APs) (i.e., MEC servers), which have different transmission power and different computing capabilities. In this framework, we also consider multiple-type mobile users with different sizes of computation tasks, and they offload the tasks to a MEC server, and receive the computation resulting data from the server. We derive the successful edge computing probability (SECP), defined as the probability that a user offloads and finishes its computation task at the MEC server within the target latency. We provide a closed-form expression of the approximated SECP for general case, and closed-form expressions of the exact SECP for special cases. This paper then provides the design insights for the optimal configuration of MEC-enabled HetNets by analyzing the effects of network parameters and bias factors, used in MEC server association, on the SECP. Specifically, it shows how the optimal bias factors in terms of SECP can be changed according to the numbers of user types and tiers of MEC servers, and how they are different to the conventional ones that did not consider the computing capabilities and task sizes.

cs.IT↗

arXiv2019

Impact of an Interfering Node on Unmanned Aerial Vehicle Communications

Unlike terrestrial communications, unmanned aerial vehicle (UAV) communications have some advantages such as the line-of-sight (LoS) environment and flexible mobility. However, the interference will be still inevitable. In this paper, we analyze the effect of an interfering node on the UAV communications by considering the LoS probability and different channel fading for LoS and non-line-of-sight (NLoS) links, which are affected by the elevation angle of the communication link. We then derive a closed-form outage probability in the presence of an interfering node for all the possible scenarios and environments of main and interference links. After discussing the impacts of transmitting and interfering node parameters on the outage probability, we show the existence of the optimal height of the UAV that minimize the outage probability. We also show the NLoS environment can be better than the LoS environment if the average received power of the interference is more dominant than that of the transmitting signal on UAV communications. Finally, we analyze the outage probability for the case of multiple interfering nodes using stochastic geometry and the outage probability of the single interfering node case, and show the effect of the interfering node density on the optimal height of the UAV.

eess.SP↗