Space Debris mitigation is of utmost importance for GEO satellites. An overview of the main activities being carried out at EUMETSAT in the frame of space debris mitigation recommendations, and in particular in the areas of collision risk mitigation and End-Of-Life practices, is presented in the paper AIAA 2010-1959..
One of the selected SpaceOps2012 Conference "best papers" (AIAA-2012-1295493) describes a commercial collaboration for collision avoidance by establishing a Space Data Center (SDC). The paper describes the SDC architectureand operations, exposing unique capabilities and lessons learned since its inception in 2009.
Another "best topic paper" of the SpaceOps2012 Conference considers space debris mitigation requirements for LEO missions (AIAA-2012-1257086). The method developed by ESA alows the analysis of global compliance with the request to limit the orbital lifetime of a spacecraft to a period no longer than 25 years after the end of the mission by using publicly availble orbit data.
The SpaceOps2014 Conference addressed the growing concern about space debris which could become a runaway environment ("Kessler Syndrome"). To prevent this secnario Los Alamos National Laboratories established the goal to develop an integrated system of amospheric drag moedling, orbit propagation and conjunction analysis with detailed uncertainty qualification to address the space debris and collision avoidance problem. Components and capabilities of this "IMPACT" framework is presented in paper AIAA 2014-1771.

Deep Space Operations
The SpaceOps0214 Conference addressed various deep space operations aspects. Innovative "best topic" papers were:
AIAA 2014-1716: Presenting the incorporation of human health and human factors insights into possible vehicle designs for trans-lunar space.
AIAA 2014-1625: This paper presents the development of a two stage Mars Ascent Vehicle (MAV) using in-situ propellant production. The examined schemes utilize CO2 and water as starting blockes to produce LOX and a propane blend. The infrastructure to fuel and launch the MAV is also explored.
AIAA 2014-1634: This paper is exploring the possibilities to use JPL's Advanced Multimission Operation System (AMMOS) Ground Data System (GDS) for the support of future deep space CubeSat missions.

Delay and Disruption Tolerant Network (DTN)
A communications network accepting delays in the transmission and reception processes.
Delay tolerant networks are needed to cope with the traveling times of electrical signals through long distances in space, i.e. reaction times to occurrences on board a spacecraft could be in the order of hours. Because of the increasing delay-times for long distance human spaceflight the methods of establishing more delay tolerant networks is being considered (AIAA paper 2006-5526) . Disruption tolerant networks need to cope with breaks in the communication chains, modeled after the Internet. DTN automates the store and forward process within an available network of communication satellites and ground stations to transfer data from spacecraft to the intended receiver ( preliminary results: see test in Nov. 2008, Richard Doyle, NASA Jet Propulsion Laboratory). For application testing see also the recent Communicator article Internet in Space Testing.
In 2010 a paper (2010-2206) was presented dealing with four major developmental areas (system architecture, data definition/usage, application architecture, and tool implementation) critical to the maturation of this ability. Within each developmental area implementation recommendations are presented and current threads of research. Ultimately, it was concluded that closed-loop network management of DTNs is not viable and architectures that promote status telemetry over control loops, autonomous decision making over static configuration, and locality over global administration must be engineered for these networks.
The SpaceOps2012 Conference "best topic paper": "The Delay-Tolerant Networking Engineering Network", AIAA-2012-1290363) describes the DTN Engineering Network (DEN) testbed comprised of physical and virtual machines and flight-like hardware located at different NASA-centers and supporting universities. Its design, construction test excecution, and anticipated evlution is outlined.

DSN Schedule Automation
The DSN Scheduling Engine (DSE) is described in paper AIAA 2010-2265, It has been developed to increase the level of automated scheduling support available to users of NASA’s Deep Space Network (DSN). Another "best topic paper" of the SpaceOps2012 conference deals with the automation of the DSN scheduling process wrt mid- und longrange schedule describing the Seervice Scheduling Software (SSS, or S3): AIAA-2012-1296235.