System Initialization Time Research Articles

RD-VIO: Relative-depth-aided visual-inertial odometry for autonomous underwater vehicles

Because of the autonomous underwater vehicles' (AUVs') slow motion and insufficient excitations, monocular visual-inertial odometry (VIO) systems for AUVs still have large-scale errors and a lengthy initialization period. In this paper, we present a relative-depth-aided monocular visual-inertial odometry (RD-VIO) system based on two innovative methods: Inertial Measurement Unit (IMU)-depth joint initialization and relative depth tightly coupled with visual-inertial. The RD-VIO performs reprojection bundle adjustment with dynamic weight factors for visual residuals. Depth measurements acquired by depth gauge or pressure sensor are compensated with reliable inter-image IMU pre-integration to account for different sensor frequencies. Also, we adopt an IMU-depth joint initialization using relative depth measurements and IMU excitations to estimate the scale and gravity direction together, which captures the complete AUV motion changes, improving scale estimation and decreasing initialization time. To reduce scale drift and improve global accuracy and consistency, a tight coupling of relative depth and visual-inertial in the RD-VIO is employed to optimize the AUV pose from depth measurements. Using two open-source datasets and our experiments from Sanya, we evaluated the performance of RD-VIO. The evaluation results show that the proposed system can achieve a more accurate trajectory than the state-of-the-art algorithms with less system initialization time and scale error.

A Real-Time Map Restoration Algorithm Based on ORB-SLAM3

In the monocular visual-inertia mode of ORB-SLAM3, the insufficient excitation obtained by the inertial measurement unit (IMU) will lead to a long system initialization time. Hence, the trajectory can be easily lost and the map creation will not be completed. To solve this problem, a fast map restoration method is proposed in this paper, which adresses the problem of insufficient excitation of IMU. Firstly, the frames before system initialization are quickly tracked using bag-of-words and maximum likelyhood perspective-n-point (MLPNP). Then, the grayscale histogram is used to accelerate the loop closure detection to reduce the time consumption caused by the map restoration. After experimental verification on public datasets, the proposed algorithm can establish a complete map and ensure real-time performance. Compared with the traditional ORB-SLAM3, the accuracy improved by about 47.51% and time efficiency improved by about 55.96%.

Hierarchical Multi-Authority and Attribute-Based Encryption Friend Discovery Scheme in Mobile Social Networks

In mobile social networks, to guarantee the security and privacy in the friend discovery process, we propose a hierarchical multi-authority and attribute-based encryption (ABE) friend discovery scheme based on ciphertext-policy (CP)-ABE. It employs character attribute subsets to achieve flexible fine-grained access control, which solves the problem of single-point failure and performance bottleneck. Performance analysis demonstrates the superiority of our scheme in terms of system initialization time and key generation time.

Timing Analysis of System Initialization and Crash Recovery for a Segment-Based Flash Translation Layer

Recently, the capacity of flash-memory storage systems has grown rapidly, and flash-memory technology has advanced along with the wave of consumer electronics and embedded systems. In order to properly manage product cost and initialization performance, vendors face serious challenges in system design and analysis. Thus, the timing analysis of system initialization and crash recovery for a segment-based flash translation layer has become an important research topic. This article focuses on system initialization, crash recovery, and timing analysis. The timing analysis of system initialization involves the relationship between the size of the main memory and the system initialization time. The timing analysis of crash recovery explains the worst case recovery time. The experiments in this study show that the timing analysis of system initialization and crash recovery can be applied to the segment-based flash translation layer.

Satisfying quality requirements in the design of a partition‐based, distributed stock trading system

SUMMARYAlthough quality requirements (QRs) have become a major drive in today's software development, there have been very few real‐world examples in the literature that demonstrate how to meet these requirements. This paper presents such an example. Specifically, the paper describes the design of a partition‐based distributed stock trading service system that satisfies a set of QRs related to resource utilization, performance, scalability and availability. The paper evaluates this design through detailed experiments and discusses some design alternatives and the lessons learned. Central to this design are a static load distribution strategy and a dynamic load balancing strategy. The first strategy is to achieve an initial balanced workload on the system's server cluster during the system initialization time, whereas the second strategy is to maintain this balanced workload throughout the system execution time. Together, these two strategies work in unison to ensure that the server resources are efficiently utilized; the user requests are processed with the required speed; the application is partitioned with sufficient room to scale; and the system is highly available. Copyright © 2011 John Wiley & Sons, Ltd.

An Adaptive Flash Translation Layer for High-Performance Storage Systems

While the capacity of flash-memory storage systems keeps increasing significantly, an effective and efficient management of flash-memory space has become a critical design issue. Different granularities in space management impose different management costs and mapping efficiency. In this paper, we will explore an address translation mechanism (AddrTM) that can dynamically and adaptively switch between different granularities in the mapping of logical block addresses into physical block addresses in flash-memory management. The objective is to provide high performance in address mapping and space utilization and, at the same time, to have the main memory requirements, the garbage collection overhead, and the system initialization time under proper management. The experimental results show that the proposed adaptive mechanism can provide better performance improvement and practicability than other well-known coarse-grained management mechanisms over realistic workloads.

A formal approach to lock escalation

Since database management systems(DBMSs) have limited lock resources, transactions requesting locks beyond the limit must be aborted, degrading the performance abruptly. Lock escalation is considered a solution to this problem. However, existing lock escalation methods have been designed in an ad hoc manner. So, they do not provide a complete solution. In this paper, we propose a formal model of lock escalation. Using the model, we analyze the roles of lock escalation formally and solve the problems of the existing methods systematically. In particular, we introduce the concept of the unescalatable lock that cannot be escalated due to conflicts. We identify that the unescalatable lock is the major cause of exhausting lock resources. We then analyze the reasons why unescalatable locks are generated and propose a new lock escalation method, adaptive lock escalation, which controls lock escalation based on the number of unescalatable locks. Through extensive simulation, we show that adaptive lock escalation significantly outperforms existing methods reducing the number of aborts and the average response time and increasing the throughput to a great extent. Adaptive lock escalation drastically reduces (more than 10 fold) the number of lock resources required to maintain the same level of throughput and average response time. At the same time, the throughput and average response time when using adaptive lock escalation are rather insensitive to the number of lock resources. Existing methods rely on users to estimate this number accurately at system initialization time. Adaptive lock escalation greatly alleviates this burden.

Dynamic buffer allocation in video-on-demand systems

In video-on-demand (VOD) systems, as the size of the buffer allocated to user requests increases, initial latency and memory requirements increase. Hence, the buffer size must be minimized. The existing static buffer allocation scheme, however, determines the buffer size based on the assumption that the system is in the fully loaded state. Thus, when the system is in a partially loaded state, the scheme allocates a buffer larger than necessary to a user request. This paper proposes a dynamic buffer allocation scheme that allocates to user requests buffers of the minimum size in a partially loaded state, as well as in the fully loaded state. The inherent difficulty in determining the buffer size in the dynamic buffer allocation scheme is that the size of the buffer currently being allocated is dependent on the number of and the sizes of the buffers to be allocated in the next service period. We solve this problem by the predict-and-enforce strategy, where we predict the number and the sizes of future buffers based on inertia assumptions and enforce these assumptions at runtime. Any violation of these assumptions is resolved by deferring service to the violating new user request until the assumptions are satisfied. Since the size of the current buffer is dependent on the sizes of the future buffers, it is represented by a recurrence equation. We provide a solution to this equation, which can be computed at the system initialization time for runtime efficiency. We have performed extensive analysis and simulation. The results show that the dynamic buffer allocation scheme reduces initial latency (averaged over the number of user requests in service from one to the maximum capacity) to 1/29.4 /spl sim/ 1/11.0 of that for the static one and, by reducing the memory requirement, increases the number of concurrent user requests to 2.36 /spl sim/ 3.25 times that of the static one when averaged over the amount of system memory available. These results demonstrate that the dynamic buffer allocation scheme significantly improves the performance and capacity of VOD systems.

Dynamic buffer allocation in video-on-demand systems

In video-on-demand (VOD) systems, as the size of the buffer allocated to user requests increases, initial latency and memory requirements increase. Hence, the buffer size must be minimized. The existing static buffer allocation scheme, however, determines the buffer size based on the assumption that the system is in the fully loaded state. Thus, when the system is in a partially loaded state, the scheme allocates a buffer larger than necessary to a user request. This paper proposes a dynamic buffer allocation scheme that allocates to user requests buffers of the minimum size in a partially loaded state as well as in the fully loaded state. The inherent difficulty in determining the buffer size in the dynamic buffer allocation scheme is that the size of the buffer currently being allocated is dependent on the number of and the sizes of the buffers to be allocated in the next service period. We solve this problem by the predict-and-enforce strategy , where we predict the number and the sizes of future buffers based on inertia assumptions and enforce these assumptions at runtime. Any violation of these assumptions is resolved by deferring service to the violating new user request until the assumptions are satisfied. Since the size of the current buffer is dependent on the sizes of the future buffers, the size is represented by a recurrence equation. We provide a solution to this equation, which can be computed at the system initialization time for runtime efficiency. We have performed extensive analysis and simulation. The results show that the dynamic buffer allocation scheme reduces initial latency (averaged over the number of user requests in service from one to the maximum capacity) to 1 ÷ 29.4 ≁ 1 ÷ 11.0 of that for the static one and, by reducing the memory requirement, increases the number of concurrent user requests to 2.36 ∼ 3.25 times that of the static one when averaged over the amount of system memory available. These results demonstrate that the dynamic buffer allocation scheme significantly improves the performance and capacity of VOD systems.

How to Schedule Periodic and Sporadic Tasks with Resource Constraints in a Real-Time Computer System

We study the problem of scheduling periodic and sporadic tasks on the nodes of a distributed system. A periodic task consists of an infinite number of requests, each of which has a prescribed deadline. Each node is a monoprocessor machine and we assume that the existence of enough processing power for all periodic tasks is verified at system initialization time. Periodic tasks may interact each other by sharing critical resources. The Dynamic Priority Ceiling Protocol is used to guarantee that each task completes execution before its deadline and each resource is never accessed by more than one task simultaneously. In addition, we allow for the unpredictable occurrence of sporadic tasks. We develop a local scheduling scheme that permits first to test on-line whether or not an occurring hard sporadic task can be guaranteed to meet its timing requirements and second to schedule soft sporadic tasks with a minimal response time.

Simultaneous estimation of echo path and channel responses using full-duplex transmitted training data sequences

To reduce the system initialization time in high-speed full-duplex data transmission over two-wire lines, we propose an efficient full-duplex fast training algorithm which can simultaneously estimate the impulse responses of echo paths and channels at both ends. Two mutually orthogonal periodic sequences are designed and used to co-estimate the near echo, the far echo with bulk delay, and the channel response. The new algorithm can reduce the tap-setting time to half of that required by the traditional half-duplex fast training schemes. The effects of channel noise and symbol rate offset between two ends are examined in terms of both mean-square error (MSE) and signal-to-noise ratio (SNR). Both the theoretical analysis and computer simulation show that there are three degrading factors due to symbol rate offset. The SNR is inversely proportional to the sum of the estimated coefficients, the half period of the training sequences, and the square of symbol rate offset. If the far-signal-to-channel-noise ratio is 30 dB, then the degradation is significant when the symbol rate offset is more than 10/sup -4/. If it is 40 dB, then the degradation is significant when the symbol rate offset is above 3/spl times/10/sup -5/.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Scheduling periodic and sporadic tasks in a real-time system

We study the problem of scheduling periodic and sporadic time-critical tasks on the nodes of a distributed system. A periodic task consists of an infinite number of requests, each of which has a prescribed deadline. Each node is a monoprocessor machine and we assume that the existence of enough processing power for all periodic tasks is verified at system initialization time. We develop an algorithm which determines on-line, whether or not an occurring sporadic task can be guaranteed to meet its timing requirements. Guarantee means that all the tasks, sporadic and periodic, supported by the node can be feasibly scheduled by the preemptive Earliest Deadline scheduling strategy. We show that this algorithm is optimal, e.g., guarantees a task whenever it is possible and hence provides an efficient acceptance test which runs in linear time.