Record/replay is one essential tool in clouds to provide many capabilities such as fault tolerance, software debugging, and security analysis by recording the execution into a log and replaying it deterministically later on. However, in virtualized environments, the log file increases heavily due to saving a considerable amount of I/O data, finally introducing significant storage costs. To mitigate this problem, this paper proposes RR-Row, a redirect-on-write based virtual machine disk for record/replay scenarios. RR-Row appends the written data into new blocks rather than overwrites the original blocks during normal execution so that all written data are reserved in the disk. In this way, the record system only saves the block id instead of the full content, and the replay system can directly fetch the data from the disk rather than the log, thereby reducing the log size a lot. In addition, we propose several optimizations for improving I/O performance so that it is also suitable for normal execution. We implement RR-Row for QEMU and conduct a set of experiments. The results show that RR-Row reduces the log size by 68% compared to the currently used Raw/QCow2 disk without compromising I/O performance.

In this paper, we investigate optimal design of millimeter-wave (mmWave) multiuser line-of-sight multiple-input-multiple-output (LOS MIMO) systems using hybrid arrays of subarrays based on hybrid block diagonalization (BD) precoding and combining scheme. By introducing a general 3D geometric channel model, the optimal subarray separation products of the transmitter and receiver for maximizing sum-rate is designed in terms of two regular configurations of adjacent subarrays and interleaved subarrays for different users, respectively. We analyze the sensitivity of the optimal design parameters on performance in terms of a deviation factor, and derive expressions for the eigenvalues of the multiuser equivalent LOS MIMO channel matrix, which are also valid for non-optimal design. Simulation results show that the interleaved subarrays can support longer distance communication than the adjacent subarrays given the appropriate fixed subarray deployment.

This paper introduces heuristic approaches and a deep reinforcement learning approach to solve a joint virtual network function deployment and scheduling problem in a dynamic scenario. We formulate the problem as an optimization problem. Based on the mathematical description of the optimization problem, we introduce three heuristic approaches and a deep reinforcement learning approach to solve the problem. We define an objective to maximize the ratio of delay-satisfied requests while minimizing the average resource cost for a dynamic scenario. Our introduced two greedy approaches are named finish time greedy and computational resource greedy, respectively. In the finish time greedy approach, we make each request be finished as soon as possible despite its resource cost; in the computational resource greedy approach, we make each request occupy as few resources as possible despite its finish time. Our introduced simulated annealing approach generates feasible solutions randomly and converges to an approximate solution. In our learning-based approach, neural networks are trained to make decisions. We use a simulated environment to evaluate the performances of our introduced approaches. Numerical results show that the introduced deep reinforcement learning approach has the best performance in terms of benefit in our examined cases.

A power-scalable sub-sampling phase-locked loop (SSPLL) is proposed for realizing dual-mode operation; high-performance mode with good phase noise and power-saving mode with moderate phase noise. It is the most efficient way to reduce power consumption by lowering the supply voltage. However, there are several issues with the low-supply millimeter-wave (mmW) SSPLL. This work discusses some techniques, such as a back-gate forward body bias (FBB) technique, in addition to employing a CMOS deeply depleted channel process (DDC).

A power-scalable wideband distributed amplifier is proposed. For reducing the power consumption of this power-hungry amplifier, it is efficient to lower the supply voltage. However, there is a hurdle owing to the transistor threshold voltage. In this work, a CMOS deeply depleted channel process is employed to overcome the hurdle.

5G service has been launched in various countries, and research for the beyond 5G is already underway actively around the world. In beyond 5G, it is expected to expand the various capabilities of communication technologies to cover further wide use cases from 5G. As a candidate elemental technology, cell free massive MIMO has been widely researched and shown its potential to enhance the capabilities from various aspects. However, for deploying this technology in reality, there are still many technical issues such as a cost of distributing antenna and installing fronthaul, and also the scalability aspects. This paper surveys research trends of cell free massive MIMO, especially focusing on the deployment challenges with an introduction to our specific related research activities including some numerical examples.

The shared last level cache (SLLC) in tile chip multiprocessors (TCMP) provides a low off-chip miss rate, but it causes a long on-chip access latency. In the two-level cache hierarchy, data replication stores replicas of L1 victims in the local LLC (L2 cache) to obtain a short local LLC access latency on the next accesses. Many data replication mechanisms have been proposed, but they do not consider both L1 victim reuse behaviors and LLC replica reception capability. They either produce many useless replicas or increase LLC pressure, which limits the improvement of system performance. In this paper, we propose a two-level cache aware adaptive data replication mechanism (TCDR), which controls replication based on both L1 victim reuse behaviors prediction and LLC replica reception capability monitoring. TCDR not only increases the accuracy of L1 replica selection, but also avoids the pressure of replication on LLC. The results show that TCDR improves the system performance with reasonable hardware overhead.

Although many software engineering studies have been conducted, it is not clear whether they meet the needs of software development practitioners. Some studies evaluated the effectiveness of software engineering research by practitioners, to clarify the research satisfies the needs of the practitioners. We performed replicated study of them, recruiting practitioners who mainly belong to SMEs (small and medium-sized enterprises) to the survey. We asked 16 practitioners to evaluate cutting-edge software engineering studies presented in ICSE 2016. In the survey, we set the viewpoint of the evaluation as the effectiveness for the respondent's own work. As a result, the ratio of positive answers (i.e., the answers were greater than 2 on a 5-point scale) was 33.3%, and the ratio was lower than past studies. The result was not affected by the number of employees in the respondent's company, but would be affected by the viewpoint of the evaluation.

Network Slicing (NS) is recognized as a key technology for the 5G network in providing tailored network services towards various types of verticals over a shared physical infrastructure. It offers the flexibility of on-demand provisioning of diverse services based on tenants' requirements in a dynamic environment. In this work, we focus on two important issues related to 5G Core slices: the deployment and the reconfiguration of 5G Core NSs. Firstly, for slice deployment, balancing the workloads of the underlying network is beneficial in mitigating resource fragmentation for accommodating the future unknown network slice requests. In this vein, we formulate a load-balancing oriented 5G Core NS deployment problem through an Integer Linear Program (ILP) formulation. Further, for slice reconfiguration, we propose a reactive strategy to accommodate a rejected NS request by reorganizing the already-deployed NSs. Typically, the NS deployment algorithm is reutilized with slacked physical resources to find out the congested part of the network, due to which the NS is rejected. Then, these congested physical nodes and links are reconfigured by migrating virtual network functions and virtual links, to re-balance the utilization of the whole physical network. To evaluate the performance of deployment and reconfiguration algorithms we proposed, extensive simulations have been conducted. The results show that our deployment algorithm performs better in resource balancing, hence achieves higher acceptance ratio by comparing to existing works. Moreover, our reconfiguration algorithm improves resource utilization by accommodating more NSs in a dynamic environment.

A novel direction of arrival (DOA) estimation method for the coherent signal is presented in this paper. The proposed method applies the eigenvector associated with max eigenvalue, which contains the DOAs of all signals, to form a Toeplitz matrix, yielding an unconstrained optimization problem. Then, the DOA is obtained by peak searching of the pseudo power spectrum without the knowledge of signal number. It is illustrated that the method has a great performance and low computation complexity for the coherent signal. Simulation results verify the usefulness of the method.

A temperature-variation-tolerant intermittent startup circuit (ISC) that suppresses quiescent current to 300nA at 0.48V was developed. The ISC is a key circuit for a batteryless wireless sensor that can detect a 1μA generation current of energy harvesting sources from the intervals of wireless signals. The ISC consists of an ultralow-voltage detector composed of a depletion-type MOSFET and low-Vth MOSFETs, a Dickson-type gate-boosted charge pump circuit, and a power-switch control circuit. The detector consists of a voltage reference comparator and a feedback-controlled latch circuit for a hysteresis function. The voltage reference comparator, which has a common source stage with a folded constant-current-source load composed of a depletion-type nMOSFET, makes it possible to reduce the temperature dependency of the detection voltage, while suppressing the quiescent current to 300nA at 0.48V. The ISC fabricated with fully-depleted silicon-on-insulator (FD-SOI) CMOS technology also suppresses the variation of the quiescent current. To verify the effectiveness of the circuit, the ISC was fabricated in a 0.8-μm triple-Vth FD-SOI CMOS process. An experiment on the fabricated system, the ISC boosts the input voltage of 0.48V to 2.4V while suppressing the quiescent current to less than 300nA at 0.48V. The measured temperature coefficient of the detection voltage was ±50ppm/°C. The fluctuation of the quiescent current was 250nA ± 90nA in the temperature range from 0°C to 40°C. An intermittent energy harvesting sensor with the ISC was also fabricated. The sensor could detect a generation current of 1μA at EH sources within an accuracy of ±15% in the temperature range from 0°C to 40°C. It was also successfully applied to a self-powered wireless plant-monitoring sensor system.

Replayable chosen ciphertext (RCCA) security was introduced by Canetti, Krawczyk, and Nielsen (CRYPTO'03) in order to handle an encryption scheme that is “non-malleable except tampering which preserves the plaintext.” RCCA security is a relaxation of CCA security and a useful security notion for many practical applications such as authentication and key exchange. Canetti et al. defined non-malleability against RCCA (NM-RCCA), indistinguishability against RCCA (IND-RCCA), and universal composability against RCCA (UC-RCCA). Moreover, they proved that these three security notions are equivalent when considering a PKE scheme whose plaintext space is super-polynomially large. Among these three security notions, NM-RCCA seems to play the central role since RCCA security was introduced in order to capture “non-malleability except tampering which preserves the plaintext.” However, their definition of NM-RCCA is not a natural extension of that of original non-malleability, and it is not clear whether their NM-RCCA captures the requirement of original non-malleability. In this paper, we propose definitions of indistinguishability-based and simulation-based non-malleability against RCCA by extending definitions of original non-malleability. We then prove that these two notions of non-malleability and IND-RCCA are equivalent regardless of the size of plaintext space of PKE schemes.

To solve the problem of the self-deployment of heterogeneous directional wireless sensor networks in 3D space, this paper proposes a weighted Voronoi diagram-based self-deployment algorithm (3DV-HDDA) in 3D space. To improve the network coverage ratio of the monitoring area, the 3DV-HDDA algorithm uses the weighted Voronoi diagram to move the sensor nodes and introduces virtual boundary torque to rotate the sensor nodes, so that the sensor nodes can reach the optimal position. This work also includes an improvement algorithm (3DV-HDDA-I) based on the positions of the centralized sensor nodes. The difference between the 3DV-HDDA and the 3DV-HDDA-I algorithms is that in the latter the movement of the node is determined by both the weighted Voronoi graph and virtual force. Simulations show that compared to the virtual force algorithm and the unweighted Voronoi graph-based algorithm, the 3DV-HDDA and 3DV-HDDA-I algorithms effectively improve the network coverage ratio of the monitoring area. Compared to the virtual force algorithm, the 3DV-HDDA algorithm increases the coverage from 75.93% to 91.46% while the 3DV-HDDA-I algorithm increases coverage from 76.27% to 91.31%. When compared to the unweighted Voronoi graph-based algorithm, the 3DV-HDDA algorithm improves the coverage from 80.19% to 91.46% while the 3DV-HDDA-I algorithm improves the coverage from 72.25% to 91.31%. Further, the energy consumption of the proposed algorithms after 60 iterations is smaller than the energy consumption using a virtual force algorithm. Experimental results demonstrate the accuracy and effectiveness of the 3DV-HDDA and the 3DV-HDDA-I algorithms.

A consecutive-k-out-of-n:G system consists of n components which are arranged in a line and the system works if and only if at least k consecutive components work. This paper discusses the optimization problems for a consecutive-k-out-of-n:G system. We first focus on the optimal number of components at the system design phase. Then, we focus on the optimal replacement time at the system operation phase by considering a preventive replacement, which the system is replaced at the planned time or the time of system failure which occurs first. The expected cost rates of two optimization problems are considered as objective functions to be minimized. Finally, we give study cases for the proposed optimization problems and evaluate the feasibility of the policies.

When a unit repeats some works over again and undergoes minimal repairs at failures, it is more practical to replace it preventively at the end of working cycles or at its failure times. In this case, it would be an interesting problem to know which is better to replace the unit at a number of working cycles or at random failures from the point of cost. For this purpose, we give models of the expected cost rates for the following replacement policies: (1) The unit is replaced at a working cycle N and at a failure number K, respectively; (2) Replacement first and last policies with working cycle N and failure number K, respectively; (3) Replacement overtime policies with working cycle N and failure number K, respectively. Optimizations and comparisons of the policies for N and K are made analytically and numerically.

To develop countermeasures against fault attacks, it is important to model an attacker's ability. The instruction skip model is a well-studied practical model for fault attacks on software. Contrastingly, few studies have investigated the instruction replacement model, which is a generalization of the instruction skip model, because replacing an instruction with a desired one is considered difficult. Some previous studies have reported successful instruction replacements; however, those studies concluded that such instruction replacements are not practical attacks because the outcomes of the replacements are uncontrollable. This paper proposes the concept of a controllable instruction replacement technique that uses the laser irradiation of flash memory. The feasibility of the proposed technique is demonstrated experimentally using a smartcard-type ARM SC100 microcontroller. Then, practical cryptosystem attacks that exploit the proposed technique are investigated. The targeted cryptosystems employ the AES with software-based anti-fault countermeasures. We demonstrate that an existing anti-instruction-skip countermeasure can be circumvented by replacing a critical instruction, e.g., a branch instruction to detect fault occurrence.

In recent years, multi-party computation (MPC) frameworks based on replicated secret sharing schemes (RSSS) have attracted the attention as a method to achieve high efficiency among known MPCs. However, the RSSS-based MPCs are still inefficient for several heavy computations like algebraic operations, as they require a large amount and number of communication proportional to the number of multiplications in the operations (which is not the case with other secret sharing-based MPCs). In this paper, we propose RSSS-based three-party computation protocols for modular exponentiation, which is one of the most popular algebraic operations, on the case where the base is public and the exponent is private. Our proposed schemes are simple and efficient in both of the asymptotic and practical sense. On the asymptotic efficiency, the proposed schemes require O(n)-bit communication and O(1) rounds,where n is the secret-value size, in the best setting, whereas the previous scheme requires O(n2)-bit communication and O(n) rounds. On the practical efficiency, we show the performance of our protocol by experiments on the scenario for distributed signatures, which is useful for secure key management on the distributed environment (e.g., distributed ledgers). As one of the cases, our implementation performs a modular exponentiation on a 3,072-bit discrete-log group and 256-bit exponent with roughly 300ms, which is an acceptable parameter for 128-bit security, even in the WAN setting.

In compressive sensing theory (CS), the restricted isometry property (RIP) is commonly used for the measurement matrix to guarantee the reliable recovery of sparse signals from linear measurements. Although many works have indicated that random matrices with excellent recovery performance satisfy the RIP with high probability, Toeplitz-structured matrices arise naturally in real scenarios, such as applications of linear time-invariant systems. Thus, the corresponding measurement matrix can be modeled as a Toeplitz (partial) structured matrix instead of a completely random matrix. The structure characteristics introduce coherence and cause the performance degradation of the measurement matrix. To enhance the recovery performance of the Toeplitz structured measurement matrix in multichannel convolution source separation, an efficient construction of measurement matrix is presented, referred to as sparse random block-banded Toeplitz matrix (SRBT). The sparse signal is pre-randomized by locally scrambling its sample locations. Then, the signal is subsampled using the sparse random banded matrix. Finally, the mixing measurements are obtained. Based on the analysis of eigenvalues, the theoretical results indicate that the SRBT matrix satisfies the RIP with high probability. Simulation results show that the SRBT matrix almost matches the recovery performance of random matrices. Compared with the existing banded block Toeplitz matrix, SRBT significantly improves the probability of successful recovery. Additionally, SRBT has the advantages of low storage requirements and fast computation in reconstruction.

Full-duplex access points (APs) deployment can significantly affect network performance of a wireless local area network (WLAN). Unlike in traditional half-duplex networks, location of a full-duplex AP will affect network coverage quality as well as full-duplex transmission opportunities. However, the effect of full-duplex AP deployment on network performance and the differences between half- and full-duplex AP deployment have not been well investigated yet. In this paper, we first theoretically analyze the effect of full-duplex AP deployment on WLAN throughput. Exact full-duplex transmission probability is derived in presence of Rayleigh fading with different AP locations. Our analysis reveal that a good AP deployment profile can exploit more full-duplex transmission opportunities and greatly improve network performance. The full-duplex AP deployment problem is then formulated as an integer linear programming (ILP) problem in which our objective is to obtain optimized network throughput. Then we develop a heuristic algorithm to solve the formulated problem and optimal deployment profile can be produced. Simulation results validate that the WLAN throughput as well as full-duplex transmission opportunities can be significantly improved by our generated full-duplex AP deployment profile.

In this paper, we propose a method to construct a scalable sensor data stream delivery system that guarantees the specified delivery quality of service (i.e., total reachability to destinations), even when delivery server resources (nodes) are in a heterogeneous churn situation. A number of P2P-based methods have been proposed for constructing a scalable and efficient sensor data stream system that accommodates different delivery cycles by distributing communication loads of the nodes. However, no existing method can guarantee delivery quality of service when the nodes on the system have a heterogeneous churn rate. As an extension of existing methods, which assign relay nodes based on the distributed hashing of the time-to-deliver, our method specifies the number of replication nodes, based on the churn rate of each node and on the relevant delivery paths. Through simulations, we confirmed that our proposed method can guarantee the required reachability, while avoiding any increase in unnecessary resource assignment costs.