Future millimeter-wave networks will support very high densities of devices and access points. This vastly increases the overhead required for...

Online advertising has evolved into a key component of the Internet we know today. It is a very complex ecosystem...

Fast advance in the design of 5G cellular networks has motivated a lot of research that addresses challenges given by...

In the last years indoor localization and applications that use positioning information have attracted a lot of attention from the...

Visible Light Communication(VLC) has emerged in the last years as a new way to communicate. Using the existing lighting infrastructure,...

By leveraging on novel concepts of virtualization and programmability, future 5G Net- works are expected to be reliable, high-performing and...

As the Internet is becoming a fundamental aspect of the society serving as a de facto platform for social and...

The current Internet includes a large number of distributed services. In order to guarantee the QoS of the communication in these services, a client has to select a close-by server with enough available resources. In order to achieve this objective, in this Thesis, we propose a simple and practical solution for Dynamic and Location Aware Server Discovery based on a Distributed Hash Table (DHT). Specifically, we decide to use a Chord DHT system (although any other DHT scheme can be used). In more detail, the solution works as follows. The servers offering a given service form a Chord-like DHT. In addition, they register their location (topological and/or geographical) information in the DHT. Each client using the service is connected to at least one server from the DHT. Eventually, a given client realizes that it is connected to a server providing a bad QoS, then, it queries the DHT in order to find an appropriate server (i.e. a close-by server with enough available resources). We define 11 design criteria, and compare our solution to the State of the Art based on them. We show that our solution is the most complete one. Furthermore, we validate the performance of our solution in two different scenarios: NAT Traversal Server Discovery and Home Agent Discovery in Mobile IP scenarios. The former serves to validate our solution in a highly dynamic environment whereas the latter demonstrates the appropriateness of our solution in more classical environments where the servers are typically hosts.

We consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon’s Mechanical Turk. We model the computations as an Internet-based task computing system under the master-worker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task. 

The operators of the Autonomous Systems (ASes) composing the Internet must deal with a constant traffic growth, while striving to reduce the overall cost-per-bit and keep an acceptable quality of service.