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Your step-by-step guide — add heterogenous radio
Using airSlate SignNow’s eSignature any business can speed up signature workflows and eSign in real-time, delivering a better experience to customers and employees. add heterogenous radio in a few simple steps. Our mobile-first apps make working on the go possible, even while offline! Sign documents from anywhere in the world and close deals faster.
Follow the step-by-step guide to add heterogenous radio:
- Log in to your airSlate SignNow account.
- Locate your document in your folders or upload a new one.
- Open the document and make edits using the Tools menu.
- Drag & drop fillable fields, add text and sign it.
- Add multiple signers using their emails and set the signing order.
- Specify which recipients will get an executed copy.
- Use Advanced Options to limit access to the record and set an expiration date.
- Click Save and Close when completed.
In addition, there are more advanced features available to add heterogenous radio. Add users to your shared workspace, view teams, and track collaboration. Millions of users across the US and Europe agree that a solution that brings everything together in a single holistic enviroment, is what organizations need to keep workflows performing easily. The airSlate SignNow REST API allows you to embed eSignatures into your app, website, CRM or cloud. Try out airSlate SignNow and enjoy faster, easier and overall more efficient eSignature workflows!
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Add heterogenous radio
hi my name is Michael Lange and I'm a second year PhD student in professor moon Chang's edge live at Princeton University today I will talk about radio access technology selection in heterogeneous wireless networks 3G Wi-Fi 4G and LTE these are all common terms for wireless radio access technologies called rats that everyone has heard of when buying a new mobile device or smartphone however most people tend to think of these networks as isolated and unrelated however nothing could be farther from the truth in the modern world many of these rats coexist for example one can switch a phone from Wi-Fi to 3G just by the press of a button causing a phone to disconnect from the Wi-Fi network and connect to the 3G the set of coexisting rats is called a heterogeneous network these networks can be composed of a large number of different rats such as Wi-Fi 3G 4G distributed antenna systems and femtocells just to name a few with all these different networks coexisting in the same place it is easy to ask the question how should my smartphone or mobile device choose the best access network to connect to at any given time the hetnet project at edge lab here at Princeton University aim stands for this pressing question we have designed a fully distributed algorithm that allows each user to change rats in such a way that the entire system is guided to a final state where no own user can change rats and get a better throughput a state of affairs we term freedo optimal the algorithm we designed is fully distributed that is the decisions are made by users without influenced by any central network provider where we view the rat selection process from a user centric approach in this non cooperative game users the ones who make the decision decisions to select the appropriate network without requiring any communication or coordination among the different rats in this game users only strive to get the best possible data rates regardless of what other people get the two major obstacles we encountered are the multi rate property of pet nets that is that different users may get different rates on the same rat and that each users decisions will affect the data rate of others as an example if several people all switch to Wi-Fi this will reduce the data rates of those users already on the Wi-Fi network before the other users switch the major results that we have obtained so far include but are not limited to the following we have generalized rats into two main classes of throughput formulas improve convergence for each of these classes of rats as well as for a mixture of these rats we have also found bounce on the Pareto efficiency gain on the final states of the network after the algorithm finishes for a more thorough discussion of our algorithm and results please refer to our paper cited at the end of the presentation our current work on this project consists of obtaining answers to the following three questions first how can we better adapt the algorithm to noise second what are the bounds on the time it takes for the algorithm to converge and finally how can we take advantage of some minimal Network assistance in order to converge in a better fashion for more details on this project or the algorithm we have developed please refer to our paper titled rat selection games in het Nets or contact us at mw7 or e refr at princeton dot edu thank you
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