Research in Collaborative Networking

We have three key research focus areas:

Edge and cloud computing
Information-centric networking
Opportunistic networking

Edge computing is a new emerging trend which extends traditional, centralized cloud computing to- wards the edges of the network and closer to the users and sources of data.

Edge computing obviates the need to transport all of the data to a centralized cloud processing data center and instead enables processing of data closer to where it originates and where it is needed. The benefits of edge computing compared to traditional cloud computing are multiple: less data traffic in the wide area networks; shorter latencies between data generation, processing, and consumption; possible increase in privacy due to data not being hoarded at a single location. There will certainly remain tasks for which traditional clouds are the best match, but for many others, edge computing and similar technologies will offer superior performance.

Information-centric networking (ICN) is a means of accessing information in the network by a loca- tion-independent name. Various ICN architectures have been proposed and currently systems like CCN and NDN enjoy the most popularity in research. By decoupling content names from their locations, information can be freely moved around in network and ideally also be discovered from the locations where it currently resides. Applying ICN in highly distributed environments like edge computing will require efficient content discovery means. ICN is an appealing concept and provides a set of solutions for moving and processing data in a distributed environment.

Opportunistic networking focuses on a type of mobile ad hoc networks where mobile devices communicate directly with each other without relying on any supporting network infrastructure. The natural mobility of the devices provides both challenges and advantages in information discovery, dissemination, and communication in these systems. Our focus has been on designing systems for location-based opportunistic information systems, e.g., floating content, and how such systems can be made to work in practice.

As driving applications for our research we consider environments like Internet of Things (IoT) where millions of (small) devices come together to provide new applications and services. IoT is a challenging environment due to the constrained resources available to many of the devices in the system, and the dynamic information and processing flows inherent to IoT applications. Another key application area in our research are energy-efficient systems; in particular systems that attempt to leverage renewable energy resources in their operation.