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.

Cooperative short-range communication schemes provide powerful tools to solve interference and resource shortage problems in wireless access networks. With such schemes, a mobile node with excellent cellular connectivity can momentarily accept to relay traffic for its neighbors experiencing poor radio conditions and use Device-to-Device

The 'big data' scene has brought new improvement opportunities to most products and services, including education. Web-based learning has become very widespread over the last decade, which in conjunction with the MOOC phenomenon, it has enabled the collection of large and rich data samples regarding the interaction of students with these educational online environments. 

Everyone is familiar with the problem of online scheduling, even if they are not aware of it; from the way we prioritize our everyday decisions to the way a delivery service must decide on the route to follow in order to cover the ongoing requests. In computer science this is a problem of even greater importance.

Mobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable.

Cellular service providers have been struggling with users’ demand since the emergence of mobile Internet. As a result, each generation of cellular network prevailed over its predecessors mainly in terms of connection speed.

This thesis tackles the optimization of energy efficiency in data centers in terms of network and server utilization.

In this thesis, signal propagation variations that are experience over the frequency resources of IEEE 802.11 Wireless Local Area Networks (WLANs) are studied.

The rapid growth of wireless mobile devices has led to saturation and congestion of wireless channels – a well-known fact. In the recent years, this issue is further exacerbated by the ever- increasing demand for traffic intensed multimedia content applications, which include but are not limited to social media, news and video streaming applications.