Self-Organizing Networked Systems


Self-Organizing Networked Systems

A worldwide megatrend with considerable impact on our society is the increasing connectivity of people and computers. Information and communication technologies (ICT) are basically everywhere.

The deep integration of ICT into many aspects of our life and the necessity to adapt these systems steadily to the evolving needs of society has however lead to a system complexity difficult to handle. In fact, the increasing complexity in terms of technology but also with respect to social, economic, legal, and other nontechnical aspects might become a stumbling block for the further development of ICT systems.

This calls for new approaches for the design and operation of networked systems. Approaches exploiting the concept of self-organization as known from nature — involving self-configuration, self-optimization, self-healing, and other self-* properties — hold the promise of a paradigm shift for the design and the evolution of ICT systems and may help to master complexity challenges.  

The phenomenon of self-organization occurs in many areas of our life. In nature, for example, fish organize themselves to swim in well-structured shoals, ants find shortest routes to food sources, and fireflies emit light flashes in perfect synchrony to attract mating partners.  Other examples of self-organized behavior can be observed in economy, psychology, and brain theory, to mention a few disciplines.

All these phenomena share the fact that the participating entities establish a structure or function without requiring central coordination. Instead, entities interact directly with each other and continuously react to changes in their environment. Such systems are often flexible, adaptive, and scalable.  Although individual entities are often unreliable, the overall system experiences a high level of resilience.

While many processes around us are self-organized, most systems in ICT do not exploit this potential in depth so far. They often require significant manual con-figuration and central entities for deployment and operation.

A prime example for a complex ICT system is a mobile telecommunication network. Such a network is traditionally organized in a very centralized manner. Recent development efforts in mobile communications, however, consider several aspects of self-organization — in particular self-configuration and self-optimization — in order to ease and speed-up planning and operation of next generation mobile networks. 

Motivated by this trend, research activities at Lakeside Labs focus on solutions for self-organization in networked systems with application domains that promise to have high impact on society.

The research portfolio of Lakeside Labs can be structured into five areas: Fundamental research on self-organization in networked systems constitutes the theoretical-methodical core of our activities. Four emerging technologies are virtually located around this core and represent the more applied research areas of Lakeside Labs:

- the Internet of Things,
- Autonomous Flying Robots,
- Multimedia-Communities, and
- Smart Grids.

All areas have thematic overlaps, which fosters synergies. All outer areas originally stem from ICT and robotics but have great potential for multidisciplinary work.