Information Propagation Delay Research Articles

Modeling dynamic spatio-temporal correlations and transitions with time window partitioning for traffic flow prediction

Predicting traffic flow represents a critical undertaking within the domain of Intelligent Transportation Systems (ITS), given its pivotal role in optimizing traffic management strategies. Nevertheless, this endeavor is fraught with challenges, stemming from the inherent complexity and dynamic nature of traffic systems. Existing methods still suffer from the following three main limitations: (i) modeling the spatio-temporal correlations in a static way, restricting the ability to learn dynamic correlations; (ii) only capturing short-term local temporal features while neglecting long-term temporal patterns; (iii) cannot learn the latent relationships between traffic nodes at different time steps. Therefore, we propose a novel method named InOutformer based on In-Time-Window self-attention and Out-Time-Window self-attention to predict traffic flow. This method can effectively capture both short-term local temporal features and model long-term global temporal patterns, while also capturing dynamic spatial correlations between nodes. Specifically, we first propose a novel time window partitioning mechanism to replace the conventional sliding time window approach, in order to capture dynamic temporal features. Second, two specially designed temporal self-attention modules are used to learn short-term local temporal features and model long-term global temporal patterns, respectively. Then, a 2D-attention method is devised to capture the spatial correlations of nodes at different time steps. Moreover, by exploiting transition flow data, the detrimental effects due to spatial information propagation delays are effectively mitigated. Extensive experiments on four real-world traffic datasets demonstrate that the proposed model InOutformer outperforms the baselines, including several state-of-the-art methods.

Reliability Assessment of Vehicle-to-Vehicle Communication Networks through Headway Distribution and Information Propagation Delay

Several developed vehicle spaces and time headway distribution models in traffic flow theory have been widely used in the literature, reflecting the primary uncertainty in drivers’ car-following movements and explaining the traffic flow stochastic features. Moreover, effective vehicle-to-vehicle (V2V) communication is a key to decentralizing traffic information systems. Accurate vehicle headway distribution estimation will ensure reliable communication and benefit passengers’ safety and comfort. Consider several proposals for headway distribution in the literature; this paper studies the effect of space-headway distribution on information propagation delay in assessing the reliability of the V2V communication networks. We utilize the properties of reliability measurement for headway data by introducing the quasi-maximum likelihood estimator (QMLE) to measure the effects that different headway models have on estimating the parameters of headway distribution in a V2V communication network. The statistical analysis is then applied to the real Next-Generation Simulation (NGSIM) data. It validates the proposed methodology and formulations by measuring the effects of model selection on headway data and information propagation delay on the reliability of the V2V network. The results show that the effect of headway distribution when the vehicle’s transmission range is smaller than the road segmentation is not negligible, especially when cars are very distant. Based on our results, we recommend new metrics based on Kullback–Leibler divergence for model selection of headway data, thereby enhancing the reliability of the V2V network.

Research on Hopping Routing of Periodic Multiorbit LEO Satellites

In recent years, the low Earth orbit microsatellite network technology has experienced rapid development due to its advantages of low latency, low cost, and short development cycles. However, building an efficient and reliable satellite network routing system faces many challenges due to the characteristics of satellite networks, such as fast‐changing topology, large variations in link latency, higher probabilities of node and link failures, and limited resources. Routing algorithms have a significant impact on intersatellite communication and have become a research hotspot. The current mainstream algorithms focus on reducing information propagation delays between satellites to enable faster transmission. However, many satellite networks, such as meteorological observation satellite networks, are not sensitive to propagation delays but emphasize reducing hardware costs, especially for the receiving and transmitting signal systems of satellites. This means minimizing the single‐step signal transmission distance of satellites. This article proposes a routing algorithm based on time slot planning and the shortest path step length. Experimental simulation results demonstrate that this algorithm significantly reduces the step length of signal transmission and lowers hardware costs.

An empirical comparison of the security and performance characteristics of topology formation algorithms for Bitcoin networks

There is an increasing demand for digital crypto-currencies to be more secure and robust to meet the following business requirements: (1) low transaction fees and (2) the privacy of users. Nowadays, Bitcoin is gaining traction and wide adoption. Many well-known businesses have begun accepting bitcoins as a means of making financial payments. However, the susceptibility of Bitcoin networks to information propagation delay, increases the vulnerability to attack of the Bitcoin network, and decreases its throughput performance. This paper introduces and critically analyses new network clustering methods, named Locality Based Clustering (LBC), Ping Time Based Approach (PTBC), Super Node Based Clustering (SNBA), and Master Node Based Clustering (MNBC). The proposed methods aim to decrease the chances of performing a successful double spending attack by reducing the information propagation delay of Bitcoin. These methods embody proximity-aware extensions to the standard Bitcoin protocol, where proximity is measured geographically and in terms of latency. We validate our proposed methods through a set of simulation experiments and the findings show how the proposed methods run and their impact in optimising the transaction propagation delay. Furthermore, these new methods are evaluated from the perspective of the Bitcoin network’s resistance to partitioning attacks. Numerical results, which are established via extensive simulation experiments, demonstrate how the extensions run and also their impact in optimising the transaction propagation delay. We draw on these findings to suggest promising future research directions for the optimisation of transaction propagation delays.

Security and performance evaluation of master node protocol based reputation blockchain in the bitcoin network

Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbours without any knowledge about the underlying physical topology can cause a delay overhead in information propagation which makes the system vulnerable to double spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces a proximity-aware extension to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, which is based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In the MNBC protocol, physical internet connectivity increases as well as the number of hops between nodes decreases through assigning nodes to be responsible for maintaining clusters based on physical Internet proximity. Furthermore, a reputation-based blockchain protocol is integrated with MNBC protocol in order to securely assign a master node for every cluster. We validate our proposed methods through a set of simulation experiments and the findings show how the proposed methods run and their impact in optimising the transaction propagation delay.

DSRC-based rear-end collision warning system – An error-component safety distance model and field test

Dedicated short-range communication (DSRC) technology can provide drivers with information about other vehicles that are beyond the normal range of vision and enables the development of driving support systems such as the rear-end collision warning system (ReCWS). However, technology constraints such as communication delays and GPS error affect the accuracy of a DSRC-based ReCWS. This paper proposes a ReCWS design that explicitly represents functional specifications of DSRC technology, including transmission delay specifications that describe the information transmission process and an error-component safety distance specification used to represent the effect of GPS error and the information propagation delay. We propose three collision warning strategies each with different deceleration requirements. The system is assembled with off-the-shelf DSRC and mobile technology that can be readily installed into test vehicles. To test the effectiveness of the proposed ReCWS, we ran a variety of controlled scenarios on a test track. The results show a high degree of warning accuracy. These field test results also provide calibrated system parameter values for future studies and designs of DSRC-based ReCWSs.

Information Transmission between Financial Markets in Chicago and New York

AbstractHigh‐frequency trading has led to widespread efforts to reduce information propagation delays between physically distant exchanges. Using relativistically correct millisecond‐resolution tick data, we document a three millisecond decrease in one‐way communication time between the Chicago and New York areas that occurred from April 27, 2010 to August 17, 2012. We attribute the first segment of this decline to the introduction of a latency‐optimized fiber optic connection in late 2010. A second phase of latency decrease can be attributed to line‐of‐sight microwave networks, operating primarily in the 6–11 GHz region of the spectrum, licensed during 2011 and 2012. Using publicly available information, we estimate these networks' latencies, costs, and bandwidths.

Probability Distribution of End-to-End Delay in a Highway VANET

Vehicular ad-hoc networks (VANETs) are wireless ad-hoc networks formed by vehicles in motion on a road or highway. The performance of VANETs has been analyzed in several studies. However, these studies determined the expected value of the information propagation speed and the end-to-end delay in highway VANETs. In this letter, we find the probability distribution of the end-to-end information propagation delay of a message in a store-carry-forward highway VANET, and show that these results agree closely with those from computer simulations. Using the derived probability distribution, we calculate the probability that the end-to-end delay is less than a given threshold.

Swarming, schooling, milling: phase diagram of a data-driven fish school model

We determine the basic phase diagram of the fish school model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limited to groups of moderate size (in the order of 100 individuals), focused not only on the transition to schooling induced by increasing the swimming speed, but also on the conditions under which a school can exhibit milling dynamics and the corresponding behavioural transitions. We show the existence of a transition region between milling and schooling, in which the school exhibits multistability and intermittence between schooling and milling for the same combination of individual parameters. We also show that milling does not occur for arbitrarily large groups, mainly due to a distance dependence interaction of the model and information propagation delays in the school, which cause conflicting reactions for large groups. We finally discuss the biological significance of our findings, especially the dependence of behavioural transitions on social interactions, which were reported by Gautrais et al to be adaptive in the experimental conditions.

Information Transmission between Financial Markets in Chicago and New York

High frequency trading has led to widespread eft orts to reduce information propagation delays between physically distant exchanges. Using relativistically correct millisecond-resolution tick data, we document a 3-millisecond decrease in one-way communication time between the Chicago and New York areas that occurred from April 27th, 2010 to August 17th, 2012. We attribute the first segment of this decline to the introduction of a latency-optimized fi ber optic connection in late 2010. A second phase of latency decrease can be attributed to line-of-sight microwave networks, operating primarily in the 6-11 GHz region of the spectrum, licensed during 2011 and 2012. Using publicly available information, we estimate these networks' latencies and bandwidths. We estimate the total infrastructure and 5-year operations costs associated with these latency improvements to exceed $500 million.

Astrolabe

Scalable management and self-organizational capabilities are emerging as central requirements for a generation of large-scale, highly dynamic, distributed applications. We have developed an entirely new distributed information management system called Astrolabe. Astrolabe collects large-scale system state, permitting rapid updates and providing on-the-fly attribute aggregation. This latter capability permits an application to locate a resource, and also offers a scalable way to track system state as it evolves over time. The combination of features makes it possible to solve a wide variety of management and self-configuration problems. This paper describes the design of the system with a focus upon its scalability. After describing the Astrolabe service, we present examples of the use of Astrolabe for locating resources, publish-subscribe, and distributed synchronization in large systems. Astrolabe is implemented using a peer-to-peer protocol, and uses a restricted form of mobile code based on the SQL query language for aggregation. This protocol gives rise to a novel consistency model. Astrolabe addresses several security considerations using a built-in PKI. The scalability of the system is evaluated using both simulation and experiments; these confirm that Astrolabe could scale to thousands and perhaps millions of nodes, with information propagation delays in the tens of seconds.