The (unhelpful) ultra-short version is that Dijkstra's algorithm is used for policy-based SOTA and A* is used for path-based SOTA. ![]() So you have an optimal subproblem structure to exploit. So you can't make that assumption to simplify the problem initially.īy contrast, in the policy-based scenario, you always assume that your future actions are optimal, You won't necessarily be on the most optimal path anymore, Why? Intuitively, it's because after you travel a bit, This is-counterintuitively!-a much tougher problem than finding the policy.Įven though the solution looks simpler (it's just a path rather than a policy), You can just print out a map for this on paper, the old-fashioned way. It is the SOTA problem in the case where you statically decide on the entire path before you depart. Is just the maximum probability of reaching it from each road at the next intersection. This is a dynamic-programming problem, because the probability of reaching your destination on time This is what you'd prefer to do, because it can potentially give better results depending on whether you get lucky/unlucky with traffic. You'd probably need a navigation device for this, since there are too many possibilities in the "policy" to print on paper. It is the case of the SOTA problem where you decide which road to take based on how much time you have left. Path-based Routing What is the policy-based SOTA problem? That means your time budget can affect your route. To avoid suddenly getting stuck in the middle of, say, a highway, due to traffic. a highway), otherwise you might have no chance of reaching your destination on time.īut if you have a lot of time, you might take a safer path (like side roads) that no one uses, If you don't have a lot of time, you might need to take a riskier path That would only be the case if traffic was perfectly predictable. But so what? 30 minutes or 60 minutes-isn't there a single best path? What it (probably) gives you is the path with the least expected (average) time to your destination. It only lets you specify a departure or arrival time, but not both. It doesn't let you specify a time budget. Or you might need to get from your house to the airport in less than 1 hour. It's the reliable routing problem: How do you travel from point A to point B in T time under traffic?įor example, you might have a meeting in San Jose at 3pm, and one to reach in San Francisco at 4pm. Theory (in plain English) What is the Stochastic On-Time Arrival problem (SOTA)? Tractable Pathfinding for the Stochastic On-Time Arrival Problem (also in the corresponding arXiv preprint) This option may be useful when large downloads are affecting the network speed.SOTA-Py is a Python-based solver for the policy- and path-based "SOTA" problems, Additional information includes:ĭisplays the number of current web requestsĬlick Terminate if you want to close any active connection. Users - A list of users with total Web Requests and Bandwidth consumption per user.Ī graph displays the current bandwidth consumption in KB/sec.Data can be viewed by Domain or by Site using the provided controls. Websites - A list of websites with respective total Web Requestsand Bandwidth consumption per site.Categories - Select to view a list of categories with total Web Requests and Bandwidth consumption for each category. ![]() For more information refer to Terminating active connections. ![]() Active connections can be terminated to free up bandwidth. Provides information related to current active connections. ![]() To access the Real-Time Traffic dashboard: For more information refer to Configuring Anonymization.Īctive connections in Real-Time dashboard If Anonymization is enabled, personal data (such as User Names and IPs) will be masked.
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