Constrained Application Protocol (CoAP) is a popular UDP based data transfer protocol designed for constrained nodes in lossy networks. Congestion control method is essentially required in such environment to ensure proper data transfer. CoAP offers a default congestion control technique based on binary exponential backoff (BEB) where the default method calculates retransmission time out (RTO) irrespective of Round Trip Time (RTT). CoAP simple congestion control/advanced (COCOA) is a standard alternative algorithm. COCOA computes RTO using exponential weighted moving average (EWMA) based on type of RTT; strong RTT or weak RTT. The constant weight values used in COCOA delays the variability of RTO. This delay in converging the RTO can cause QoS problems in many IoT applications. In this paper, we propose a new method called Flexi COCOA to accomplish a flexible weight based RTO computation for strong RTT samples. We show that Flexi COCOA is more network sensitive than COCOA. Specifically, the variable weight focuses on deriving better RTO and utilizing the resources more. Flexi COCOA is implemented and validated against COCOA using the Cooja simulator in Contiki OS. We carried out extensive simulations using different topologies, packet sending rates and packet error rates. Our results show that Flexi COCOA outshines COCOA and can improve QoS of IoT monitoring applications.

Mining task offloading has been attracting users of decentralized applications (DApps) because they have only devices with the limited resource, which make it difficult to execute resource-intensive mining tasks. This allows the DApp users to offload the mining tasks to a cloud and/or a mobile edge computing server managed by a cloud service provider (CSP). To ensure the sustainable cloud/edge services and the integrity of blockchain, a CSP selection problem arises, which is a problem to assign the offloading requests to an appropriate CSP. In this paper, we propose a mining task offloading strategy for the CSP selection problem to maximize the miner’s expected utility. More specifically, we formulate the CSP selection problem as a repeated stochastic game such that the coarse correlated equilibrium is achieved among miners (DApp users). In addition, we develop an online algorithm for efficiently solving the repeated stochastic game using the Lyapunov optimization and the drift-plus-penalty algorithm. Through the numerical experiments, we demonstrate the characteristics of the proposed strategy in terms of parameter sensitivity, utility, fairness, and execution time.

Nonradiative dielectric waveguide is a transmission medium for millimeter-wave integrated circuits, invented in Japan. This transmission line is characterized by low transmission loss and non-radiating nature in bends and discontinuities. It has been actively researched from 1980 to 2000, primarily at Tohoku University. This paper explains the fundamental characteristics, including passive and active circuits, and provides an overview of millimeter-wave systems such as gigabit-class ultra-high-speed data transmission applications and various radar applications. Furthermore, the performance in the THz frequency band, where future applications are anticipated, is also discussed.

Reliability is an important figure of merit of the system and it must be satisfied in safety-critical applications. This paper considers parallel applications on heterogeneous embedded systems and proposes a two-phase algorithm framework to minimize energy consumption for satisfying applications’ reliability requirement. The first phase is for initial assignment and the second phase is for either satisfying the reliability requirement or improving energy efficiency. Specifically, when the application’s reliability requirement cannot be achieved via the initial assignment, an algorithm for enhancing the reliability of tasks is designed to satisfy the application’s reliability requirement. Considering that the reliability of initial assignment may exceed the application’s reliability requirement, an algorithm for reducing the execution frequency of tasks is designed to improve energy efficiency. The proposed algorithms are compared with existing algorithms by using real parallel applications. Experimental results demonstrate that the proposed algorithms consume less energy while satisfying the application’s reliability requirements.

The concepts of programmable switches and software-defined networking (SDN) give developers flexible and deep control over the behavior of switches. We expect these concepts to dramatically improve the functionality of switches. In this paper, we focus on the concept of Deeply Programmable Networks (DPN), where data planes are programmable, and application switches based on DPN. We then propose a method to improve the performance of a key-value store (KVS) through an application switch. First, we explain the DPN and application switches. The DPN is a network that makes not only control planes but also data planes programmable. An application switch is a switch that implements some functions of network applications, such as database management system (DBMS). Second, we propose a method to improve the performance of Cassandra, one of the most popular key-value based DBMS, by implementing a caching function in a switch in a dedicated network such as a data center. The proposed method is expected to be effective even though it is a simple and traditional way because it is in the data path and the center of the network application. Third, we implement a switch with the caching function, which monitors the accessed data described in packets (Ethernet frames) and dynamically replaces the cached data in the switch, and then show that the proposed caching switch can significantly improve the KVS transaction performance with this implementation. In the case of our evaluation, our method improved the KVS transaction throughput by up to 47%.

In this research, we investigated the threshold voltage (VTH) control by partial polarization of metal-ferroelectric-semiconductor field-effect transistors (MFSFETs) with 5 nm-thick nondoped HfO2 gate insulator utilizing Kr-plasma sputtering for Pt gate electrode deposition. The remnant polarization (2Pr) of 7.2 μC/cm2 was realized by Kr-plasma sputtering for Pt gate electrode deposition. The memory window (MW) of 0.58 V was realized by the pulse amplitude and width of -5/5 V, 100 ms. Furthermore, the VTH of MFSFET was controllable by program/erase (P/E) input pulse even with the pulse width below 100 ns which may be caused by the reduction of leakage current with decreasing plasma damage.

We have designed a near-infrared wavelength Si/CaF2 DFB quantum cascade laser and investigated the possibility of single-mode laser oscillation by analysis of the propagation mode, gain, scattering time of Si quantum well, and threshold current density. As the waveguide and resonator, a slab-type waveguide structure with a Si/CaF2 active layer sandwiched by SiO2 on a Si (111) substrate and a grating structure in an n-Si conducting layer were assumed. From the results of optical propagation mode analysis, by assuming a λ/4-shifted bragg waveguide structure, it was found that the single vertical and horizontal TM mode propagation is possible at the designed wavelength of 1.70µm. In addition, a design of the active layer is proposed and its current injection capability is roughly estimated to be 25.1kA/cm2, which is larger than required threshold current density of 1.4kA/cm2 calculated by combining analysis results of the scattering time, population inversion, gain of quantum cascade lasers, and coupling theory of a Bragg waveguide. The results strongly indicate the possibility of single-mode laser oscillation.

From edge devices to cloud servers, providing optimized hardware acceleration for specific applications has become a key approach to improve the efficiency of computer systems. Traditionally, many systems employ commercial field-programmable gate arrays (FPGAs) to implement dedicated hardware accelerator as the CPU's co-processor. However, commercial FPGAs are designed in generic architectures and are provided in the form of discrete chips, which makes it difficult to meet increasingly diversified market needs, such as balancing reconfigurable hardware resources for a specific application, or to be integrated into a customer's system-on-a-chip (SoC) in the form of embedded FPGA (eFPGA). In this paper, we propose an eFPGA generation suite with customizable architecture and integrated development environment (IDE), which covers the entire eFPGA design generation, testing, and utilization stages. For the eFPGA design generation, our intellectual property (IP) generation flow can explore the optimal logic cell, routing, and array structures for given target applications. For the testability, we employ a previously proposed shipping test method that is 100% accurate at detecting all stuck-at faults in the entire FPGA-IP. In addition, we propose a user-friendly and customizable Web-based IDE framework for the generated eFPGA based on the NODE-RED development framework. In the case study, we show an eFPGA architecture exploration example for a differential privacy encryption application using the proposed suite. Then we show the implementation and evaluation of the eFPGA prototype with a 55nm test element group chip design.

Anonymous attackers have been targeting the Android ecosystem for performing severe malicious activities. Despite the complement of various vulnerabilities by security researchers, new vulnerabilities are continuously emerging. In this paper, we introduce a new type of vulnerability that can be exploited to hide data in an application file, bypassing the Android's signing policy. Specifically, we exploit padding areas that can be created by using the alignment option when applications are packaged. We present a proof-of-concept implementation for exploiting the vulnerability. Finally, we demonstrate the effectiveness of VeileDroid by using a synthetic application that hides data in the padding area and updates the data without re-signing and updating the application on an Android device.

The 2020 International Conference on Emerging Technologies for Communications (ICETC2020) was held online on December 2nd—4th, 2020, and 213 research papers were accepted and presented in each session. It is expected that the accepted papers will contribute to the development and extension of research in multiple research areas. In this survey paper, all accepted research papers are classified into four research areas: Physical & Fundamental, Communications, Network, and Information Technology & Application, and then research papers are classified into each research topic. For each research area and topic, this survey paper briefly introduces the presented technologies and methods.

With the widespread use of Internet of Things (IoT) devices in recent years, we utilize a variety of hardware devices in our daily life. On the other hand, hardware security issues are emerging. Power analysis is one of the methods to detect anomalous behaviors, but it is hard to apply it to IoT devices where an operating system and various software programs are running. In this paper, we propose an anomalous behavior detection method for an IoT device by extracting application-specific power behaviors. First, we measure power consumption of an IoT device, and obtain the power waveform. Next, we extract an application-specific power waveform by eliminating a steady factor from the obtained power waveform. Finally, we extract feature values from the application-specific power waveform and detect an anomalous behavior by utilizing the local outlier factor (LOF) method. We conduct two experiments to show how our proposed method works: one runs three application programs and an anomalous application program randomly and the other runs three application programs in series and an anomalous application program very rarely. Application programs on both experiments are implemented on a single board computer. The experimental results demonstrate that the proposed method successfully detects anomalous behaviors by extracting application-specific power behaviors, while the existing approaches cannot.

In distributed processing for communication services, a proper server selection scheme is required to reduce delay by ensuring the event occurrence order. Although a conservative synchronization algorithm (CSA) has been used to achieve this goal, an optimistic synchronization algorithm (OSA) can be feasible for synchronizing distributed systems. In comparison with CSA, which reproduces events in occurrence order before processing applications, OSA can be feasible to realize low delay communication as the processing events arrive sequentially. This paper proposes an optimal server selection scheme that uses OSA for distributed processing systems to minimize end-to-end delay under the condition that maximum status holding time is limited. In other words, the end-to-end delay is minimized based on the allowed rollback time, which is given according to the application designing aspects and availability of computing resources. Numerical results indicate that the proposed scheme reduces the delay compared to the conventional scheme.

Application-aware Traffic Engineering (TE) plays a crucial role in ensuring quality of services (QoS) for recently emerging applications such as AR, VR, cloud gaming, and connected vehicles. While a deterministic application-aware TE is required for these mission-critical applications, a negotiation procedure between applications and network operators needs to undergo major simplification to fulfill the scalability of the application based on emerging microservices and container-based architecture. In this paper, we propose a NetworkAPI framework which allows an application to indicate a desired TE behavior inside IP packets by leveraging Segment Routing over IPv6 (SRv6). In the NetworkAPI framework, the TE behavior provided by the network operator is expressed as an SRv6 Segment Identifier (SID) in the form of a 128-bit IPv6 address. Because the IPv6 address of an SRv6 SID is distributed using IP anycast, the application can utilize the unchanged SRv6 SID regardless of the application's location, as if the application controls an API on the transport network. We implement a prototype of the NetworkAPI framework on a Linux kernel. On the prototype implementation, a basic packet forwarding performance is evaluated to demonstrate the feasibility of our framework.

The term “flash crowd” describes a situation in which a large number of users access a Web service simultaneously. Flash crowds, in particular, constitute a critical problem in e-commerce applications because of the potential for enormous economic damage as well as difficulty in management. Flash crowds can become more serious depending on users' behavior. When a flash crowd occurs, the delay in server response may cause users to retransmit their requests, thereby adding to the server load. In the present paper, we propose to use the psychological factors of the users for flash crowd mitigation. We aim to analyze changes in the user behavior by presenting feedback information. To evaluate the proposed method, we performed subject experiments and stress tests. Subject experiments showed that, by providing feedback information, the average number of request retransmissions decreased from 1.33 to 0.09, and the subjects that abandoned the service decreased from 81% to 0%. This confirmed that feedback information is effective in influencing user behavior in terms of abandonment and retransmission of requests. Stress tests showed that the average number of retransmissions decreased by 41%, and the proportion of abandonments decreased by 30%. These results revealed that the presentation of feedback information could mitigate the damage caused by flash crowds in real websites, although the effect is limited. The proposed method can be used in conjunction with conventional methods to handle flash crowds.

This paper proposes an efficient server selection scheme in successive participation scenario with participating-domain segmentation. The scheme is utilized by distributed processing systems for real-time interactive communication to suppress the communication latency of a wide-area network. In the proposed scheme, users participate for server selection one after another. The proposed scheme determines a recommended server, and a new user selects the recommended server first. Before each user participates, the recommended servers are determined assuming that users exist in the considered regions. A recommended server is determined for each divided region to minimize the latency. The new user selects the recommended available server, where the user is located. We formulate an integer linear programming problem to determine the recommended servers. Numerical results indicate that, at the cost additional computation, the proposed scheme offers smaller latency than the conventional scheme. We investigate different policies to divide the users' participation for the recommended server finding process in the proposed scheme.

Android occupies a very large market share in the field of mobile devices, and quantities of applications are created everyday allowing users to easily use them. However, privacy leaks on Android terminals may result in serious losses to businesses and individuals. Current permission model cannot effectively prevent privacy data leakage. In this paper, we find a way to protect privacy data on Android terminals from the perspective of privacy information propagation by porting the concept of contextual integrity to the realm of privacy protection. We propose a computational model of contextual integrity suiting for Android platform and design a privacy protection system based on the model. The system consists of an online phase and offline phase; the main function of online phase is to computing the value of distribution norm and making privacy decisions, while the main function of offline phase is to create a classification model that can calculate the value of the appropriateness norm. Based on the 6 million permission requests records along with 2.3 million runtime contextual records collected by dynamic analysis, we build the system and verify its feasibility. Experiment shows that the accuracy of offline classifier reaches up to 0.94. The experiment of the overall system feasibility illustrates that 70% location data requests, 84% phone data requests and 46% storage requests etc., violate the contextual integrity.

A lumped element kinetic inductance detector (LeKID) relying on a superconducting resonator is a promising candidate for sensing high energy particles such as neutrinos, X-rays, gamma-rays, alpha particles, and the particles found in the dark matter owing to its large-format capability and high sensitivity. To develop a high energy camera, we formulated design rules based on the experimental results from niobium (Nb)-based LeKIDs at 1 K irradiated with alpha-particles of 5.49 MeV. We defined the design rules using the electromagnetic simulations for minimizing the crosstalk. The neighboring pixels were fixed at 150 µm with a frequency separation of 250 MHz from each other to reduce the crosstalk signal as low as the amplifier-limited noise level. We examined the characteristics of the Nb-based resonators, where the signal decay time was controlled in the range of 0.5-50 µs by changing the designed quality factor of the detectors. The amplifier noise was observed to restrict the performance of our device, as expected. We improved the energy resolution by reducing the filling factor of inductor lines. The best energy resolution of 26 for the alpha particle of 5.49 MeV was observed in our device.

Conventional sequential processing on software with a general purpose CPU has become significantly insufficient for certain heavy computations due to the high demand of processing power to deliver adequate throughput and performance. Due to many reasons a high degree of interest could be noted for high performance real time video processing on embedded systems. However, embedded processing platforms with limited performance could least cater the processing demand of several such intensive computations in computer vision domain. Therefore, hardware acceleration could be noted as an ideal solution where process intensive computations could be accelerated using application specific hardware integrated with a general purpose CPU. In this research we have focused on building a parallelized high performance application specific architecture for such a hardware accelerator for HOG-SVM computation implemented on Zynq 7000 FPGA. Histogram of Oriented Gradients (HOG) technique combined with a Support Vector Machine (SVM) based classifier is versatile and extremely popular in computer vision domain in contrast to high demand for processing power. Due to the popularity and versatility, various previous research have attempted on obtaining adequate throughput on HOG-SVM. This research with a high throughput of 240FPS on single scale on VGA frames of size 640x480 out performs the best case performance on a single scale of previous research by approximately a factor of 3-4. Further it's an approximately 15x speed up over the GPU accelerated software version with the same accuracy. This research has explored the possibility of using a novel architecture based on deep pipelining, parallel processing and BRAM structures for achieving high performance on the HOG-SVM computation. Further the above developed (video processing unit) VPU which acts as a hardware accelerator will be integrated as a co-processing peripheral to a host CPU using a novel custom accelerator structure with on chip buses in a System-On-Chip (SoC) fashion. This could be used to offload the heavy video stream processing redundant computations to the VPU whereas the processing power of the CPU could be preserved for running light weight applications. This research mainly focuses on the architectural techniques used to achieve higher performance on the hardware accelerator and on the novel accelerator structure used to integrate the accelerator with the host CPU.

Dedicated Short Range Communication (DSRC) is currently standardized as a leading technology for the implementation of Vehicular Networks. Non-safety application in DSRC is emerging beyond the initial safety application. However, it suffers from a typical issue of low data delivery ratio in urban environments, where static and moving obstacles block or attenuate the radio propagation, as well as other technical issues such as temporal-spatial restriction, capital cost for infrastructure deployments and limited radio coverage range. On the other hand, Content-Centric Networking (CCN) advocates ubiquitous in-network caching to enhance content distribution. The major characteristics of CCN are compatible with the requirements of vehicular networks so that CCN could be available by vehicular networks. In this paper, we propose a CCN-based vehicle-to-vehicle (V2V) communication scheme on the top of DSRC standard for content dissemination, while demonstrate its feasibility by analyzing the frame format of Beacon and WAVE service advertisement (WSA) messages of DSRC specifications. The simulation-based validations derived from our software platform with OMNeT++, Veins and SUMO in realistic traffic environments are supplied to evaluate the proposed scheme. We expect our research could provide references for future more substantial revision of DSRC standardization for CCN-based V2V communication.

The mapping optimization problem in Network-on-Chip (NoC) is constraint and NP-hard, and the deterministic algorithms require considerable computation time to find an exact optimal mapping solution. Therefore, the metaheuristic algorithms (MAs) have attracted great interests of researchers. However, most MAs are designed for continuous problems and suffer from premature convergence. In this letter, a binary metaheuristic mapping algorithm (BMM) with a better exploration-exploitation balance is proposed to solve the mapping problem. The binary encoding is used to extend the MAs to the constraint problem and an adaptive strategy is introduced to combine Sine Cosine Algorithm (SCA) and Particle Swarm Algorithm (PSO). SCA is modified to explore the search space effectively, while the powerful exploitation ability of PSO is employed for the global optimum. A set of well-known applications and large-scale synthetic cores-graphs are used to test the performance of BMM. The results demonstrate that the proposed algorithm can improve the energy consumption more significantly than some other heuristic algorithms.