Congestion-related Information Research Articles

Deep Reinforcement Learning for Dynamic Twin Automated Stacking Cranes Scheduling Problem

Effective dynamic scheduling of twin Automated Stacking Cranes (ASCs) is essential for improving the efficiency of automated storage yards. While Deep Reinforcement Learning (DRL) has shown promise in a variety of scheduling problems, the dynamic twin ASCs scheduling problem is challenging owing to its unique attributes, including the dynamic arrival of containers, sequence-dependent setup and potential ASC interference. A novel DRL method is proposed in this paper to minimize the ASC run time and traffic congestion in the yard. Considering the information interference from ineligible containers, dynamic masked self-attention (DMA) is designed to capture the location-related relationship between containers. Additionally, we propose local information complementary attention (LICA) to supplement congestion-related information for decision making. The embeddings grasped by the LICA-DMA neural architecture can effectively represent the system state. Extensive experiments show that the agent can learn high-quality scheduling policies. Compared with rule-based heuristics, the learned policies have significantly better performance with reasonable time costs. The policies also exhibit impressive generalization ability in unseen scenarios with various scales or distributions.

MPCP

In the recent years, end-to-end feedback-based variants of TCP as well as VCP have emerged as practical alternatives of congestion control by requiring the use of only one or two ECN bits in the IP header. However, all such schemes suffer from a relatively low speed of convergence and exhibit a biased fairness behavior in moderate bandwidth high delay networks due to utilizing an insufficient amount of congestion feedback. In this paper, we propose a novel distributed ECN-based congestion control protocol to which we refer as Multi Packet Congestion Control Protocol (MPCP). In contrast to other alternatives, MPCP is able to relay a more precise congestion feedback yet preserve the utilization of the two ECN bits. MPCP distributes (extracts) congestion related information into (from) a series of n packets, thus allowing for a 2n-bit quantization of congestion measures with each packet carrying two of 2n bits in its ECN bits. We describe the design, implementation, and performance evaluation of MPCP through both simulations and experimental studies.

Automatic Music Synchronization Using Partial Score Representation Based on IEEE 1599

In this paper, a novel multimedia transmission server is designed using rule based expert system technology. It is superior on current media transmission servers because it is more powerful on streaming, flexible on control, and reliable on maintenance. In the proposed expert server, working parameters and management methods are separated from the decision-making procedure and stored in an xml database called knowledge base. The server fires different transmission strategies inside the knowledge base by runtime inference. Thus it can easily adjust transmission parameters under various environments and adopt new developed methods without significantly changing the main body of server codes. In this paper, we not only analyzed the time complexity of inference procedure and the real time characteristics of the server, but also tested the server performance on local area networks. Results showed that the expert system can deliver smooth streams with around 50% deduced throughput oscillations when compared with a single rate control method. The saved 50% bandwidth could be used for supporting more users. When congestion happened, the expert system reacts intelligently and conducts cooperative steps to relocate its resources. At the same time, the congestion related information is recorded and referred for future congestion avoidance. Attractively, these enhanced performances are achieved by taking less than 10% of the CPU time for the execution of the expert server control program.

One More Bit is Enough

Achieving efficient and fair bandwidth allocation while minimizing packet loss and bottleneck queue in high bandwidth-delay product networks has long been a daunting challenge. Existing end-to-end congestion control (e.g., TCP) and traditional congestion notification schemes (e.g., TCP+AQM/ECN) have significant limitations in achieving this goal. While the XCP protocol addresses this challenge, it requires multiple bits to encode the congestion-related information exchanged between routers and end-hosts. Unfortunately, there is no space in the IP header for these bits, and solving this problem involves a non-trivial and time-consuming standardization process. In this paper, we design and implement a simple, low-complexity protocol, called variable-structure congestion control protocol (VCP), that leverages only the existing two ECN bits for network congestion feedback, and yet achieves comparable performance to XCP, i.e., high utilization, negligible packet loss rate, low persistent queue length, and reasonable fairness. On the downside, VCP converges significantly slower to a fair allocation than XCP. We evaluate the performance of VCP using extensive ns2 simulations over a wide range of network scenarios and find that it significantly outperforms many recently-proposed TCP variants, such as HSTCP, FAST, CUBIC, etc. To gain insight into the behavior of VCP, we analyze a simplified fluid model and prove its global stability for the case of a single bottleneck shared by synchronous flows with identical round-trip times.

One more bit is enough

Achieving efficient and fair bandwidth allocation while minimizing packet loss in high bandwidth-delay product networks has long been a daunting challenge. Existing end-to-end congestion control ( eg TCP) and traditional congestion notification schemes ( eg TCP+AQM/ECN) have significant limitations in achieving this goal. While the recently proposed XCP protocol addresses this challenge, XCP requires multiple bits to encode the congestion-related information exchanged between routers and end-hosts. Unfortunately, there is no space in the IP header for these bits, and solving this problem involves a non-trivial and time-consuming standardization process.In this paper, we design and implement a simple, low-complexity protocol, called Variable-structure congestion Control Protocol (VCP), that leverages only the existing two ECN bits for network congestion feedback, and yet achieves comparable performance to XCP, ie high utilization, low persistent queue length, negligible packet loss rate, and reasonable fairness. On the downside, VCP converges significantly slower to a fair allocation than XCP. We evaluate the performance of VCP using extensive ns2 simulations over a wide range of network scenarios. To gain insight into the behavior of VCP, we analyze a simple fluid model, and prove a global stability result for the case of a single bottleneck link shared by flows with identical round-trip times.

Information effects on commuters' behavior under varying network patronage

The present paper presents one aspect of a more comprehensive study which estimated the possible effects of information presented to commuting drivers on their choice behavior, and thus on the whole network performance. This research shows that the contribution of congestion-related information decreases as the number of drivers using the information increases, the effect of information on behavioral decisions is examined here in relation to network performance.

Congestion-related information and road network performance

The need for a more efficient use of existing transport infrastructure has increased the interest of researchers in the potential of road transport informatics to relieve traffic congestion. Accordingly, this paper examines and compares the impact of road transport information on the performance of the road network in two different countries, Israel and Sweden. The international comparison aims to identify differences in both travelers' needs and responses to congestion-related information. A micro-simulation methodology is adopted in order to perform a sensitivity analysis with respect to the impacts of travelers' responses on the performance of the traffic system. The impacts of information are determined by comparing the results of with- and without-information models. Both are micro-simulation models based on behavioral data collected in Tel Aviv and Gothenburg.