Mobile Computing Activity - Overview

Modeling and analysis of wireless access markets

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New paradigms in wireless access and spectrum markets are being formed. This is accelerated even further by the advances in the dynamic spectrum access. The cognitive radio network (CRN) technology empowers devices with new degrees of flexibility, enabling new network architectures, access methods, and services, enriching the roles of service providers, and opening new opportunities for businesses cases. Unlike the traditional cellular-based markets, these spectrum markets have larger sizes, are more heterogeneous, and can offer an improved set of services. As wireless access and use increase, users are differentiated even more by their usage and data-rate requirement profile. The main objective of this research is the development of a /modular multi-level modeling framework and simulation platform/, that enables the business-driven comparative analysis of various spectrum and access markets and services. The analysis will consider a diverse set of customer populations and QoE-based performance metrics from the perspective of providers, customers, and regulators.

Support of intelligent and robust wireless networks

We envision highly flexible environments of heterogeneous wireless networks of devices with different capabilities that have access to multiple channels or network interfaces and roam over different networks. In general, such environments are extremely complex and the interaction of different layers and technologies creates many situations that cannot be foreseen during the design and testing stages of technology development. This is especially true for wireless networks, which are used for many different purposes, and which are based on a shared medium that is inherently more vulnerable than its wired counterpart. It is therefore critical to perform comprehensive empirical studies in a wide range of production environments to uncover deficiencies and identify possible optimizations and extensions. The availability of high-quality measurement and modeling studies would make it possible to develop wireless networks that are more robust, easier to manage and scale, and able to utilize scarce resources more efficiently. Our ultimate technological goal is to develop intelligent and robust wireless network, which can be defined as network of devices that in a self-organizing manner, monitor the environment, analyze its performance, and adapt based on their resources and what was learnt to increase their quality of service. The two essential components of this technology are (a) efficient, accurate and scalable measurement and analysis techniques, and (b) adaptation mechanisms that can optimize the performance and robustness of the entire system under real workloads. The underlying philosophy in our research efforts is to tightly integrate these two components by performing extensive real-life wireless measurements, analysis, and modeling, and designing well-founded adaptation mechanisms. We will demonstrate the main principles of our approach in the design of capacity planning, load balancing, device adaptation, and location-sensing algorithms.

Our research work uses real measurement data collected from large-scale wireless networks. A significant part of the measured data is available to the research community via the joint UNC/FORTH repository of traces and models for wireless networks.

Mobile peer to peer computing

To enhance the data availability, the group proposed a novel mechanism that enables wireless devices to share resources. The focus is on three facets of cooperation, namely information sharing, network connection sharing and message forwarding. Peers communicate via a wireless LAN and may have (intermittent) connection to the Internet e.g., via a Bluetooth , modem or 802.11 AP. In the information sharing facet, peers query, discover and disseminate information. When the network connection sharing is enabled, the system allows a host to act as an application-based gateway and share its connection to the Internet. The group designed, prototyped and evaluated an architecture and set of protocols, that enables this resource sharing in a self-organizing fashion without the need of an infrastructure.

Location Sensing

Positioning is a critical component of the mobile and pervasive, computing. The Mobile Computing Activity at FORTH designed and evaluated the Cooperative Location-Sensing (CLS) system that adaptively positions wireless-enabled devices using the existing communication infrastructure (WiFi access points) without the need of specialized hardware or training. CLS employs the peer-to-peer paradigm enabling hosts to cooperate and share positioning information. It also allows the easy incorporation of external information (e.g., maps and spatial information, mobility patterns) to improve its accuracy.

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