The accuracy of short-term traffic volume prediction in urban areas depends on the traffic volume characteristics and how prediction models address these characteristics. In this paper, we propose a space-time multivariate Negative Binomial (NB) regression for short-term traffic volume prediction in urban areas. The NB regression spatially correlates multiple overdispersed traffic volumes on multiple roads. We add the temporal correlation of volumes by allowing each volume to correlate with its values at previous time segments. Data consisting of traffic volumes collected in Taipei city are used to verify the model. The root mean square error is used to compare the proposed model with the Holt-Winters (HW) and Multivariate Structural Time series (MST) models. The results show that the proposed model is more accurate than the HW and MST models in all traffic conditions. The proposed model also determines causal interactions among spatial variables which assists in identifying roads affecting the prediction accuracy. Upstream roads are always significant, distant roads are always insignificant and downstream roads are significant during rush hours only.
Routing in the Internetthat empower its users to route Internet telephony sessions in a variety of interesting ways. In this paper, we will take an in-depth look at five different ways in which SIP serves as a routing protocol at the application layer.The body of this paper is organized as follows. First, we provide an overview of SIP-what it is and how it enables Internet telephony. We then cover the basics of routing and formulate a case for the emergence of application layer routing protocols such as SMTP and SIP. Next, we present some examples bolstering our claim of using SIP as a routing protocol. Finally, we provide some brief comments on the five routing methods outlined in this paper.
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