Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Overall Objectives

General objectives

Recent evolutions in distributed computing significantly increased the degree of uncertainty inherent to any distributed system and led to a scale shift that traditional approaches can no longer accommodate. The key to scalability in this context lies into fully decentralized and self-organizing solutions. The objective of the ASAP project team is to provide a set of abstractions and algorithms to build serverless, large-scale, distributed applications involving a large set of volatile, geographically distant, potentially mobile and/or resource-limited computing entities.

The ASAP Project-Team is engaged in research along three main themes: Distributed computing models and abstractions , Peer-to-peer distributed systems and applications and Data management in wireless autonomic networks . These research activities encompass both basic research, seeking conceptual advances, and applied research, to validate the proposed concepts against real applications.

A challenging new setting

Distributed computing was born in the late seventies when people started taking into account the intrinsic characteristics of physically distributed systems. The field then emerged as a specialized research area distinct from networks, operating systems and parallelism. Its birth certificate is usually considered as the publication in 1978 of Lamport's most celebrated paper “Time, clocks and the ordering of events in a distributed system[101] (that paper was awarded the Dijkstra Prize in 2000). Since then, several high-level journals and (mainly ACM and IEEE) conferences are devoted to distributed computing. This distributed system area has continuously been evolving, following the progresses in all the abovementioned areas such as networks, computing architecture, operating systems. We believe that the changes that occurred in the past decade involve a paradigm shift that can be much more than a “simple generalization” of previous works. Several conferences such as NSDI and IEEE P2P were created in the past 5 years, acknowledging this evolution. The NSDI conference is an attempt to reassemble the networking and system communities while the IEEE P2P conference was created to be a forum specialized in peer-to-peer systems. At the same time, the EuroSys conference has been created as an initiative of the European Chapter of the ACM SIGOPS to gather the system community in Europe.

The past decade has been dominated by a major shift in scalability requirements of distributed systems and applications mainly due to the exponential growth of network technologies (Internet, wireless technology, sensor devices, etc.). Where distributed systems used to be composed of up to a hundred of machines, they now involve thousand to millions of computing entities scattered all over the world and dealing with a huge amount of data. In addition, participating entities are highly dynamic, volatile or mobile. Conventional distributed algorithms designed in the context of local area networks do not scale to such extreme configurations. Therefore, they have to be revisited to fit into this new challenging setting. Precisely, scalability is one of the main focus of the ASAP project-team. Our ambitious goal is to provide the algorithmic foundations of large-scale dynamic distributed systems, ranging from abstractions to real deployment.

More specifically, distributed computing as such is characterized by how a set of distributed entities, whether they are called processes, agents, sensors, peers, processors or nodes, having only a partial knowledge of many parameters involved in the system, communicate and collaborate to solve a specific problem. While parallelism and real-time deal respectively with efficiency and on-time computing, distributed computing can be characterized by the word uncertainty . Uncertainty used to be created by the effect of asynchrony and failures in traditional distributed systems, it is now the result of many other factors, such as process mobility, low computing capacity, network dynamicity, scale, etc. This creates a new deal that makes distributed computing more diverse and more challenging.

Mastering uncertainty in distributed computing

The peer-to-peer communication paradigm emerged in the early 2000s and is now one of the prevalent models to cope with the requirements of large-scale dynamic distributed systems. In order to successfully manage the increasing level of uncertainty, distributed systems should now rely on the following properties:

Fully decentralized model:

A fully decentralized system does not rely on any central entity to control the system. Participating entities may act both as clients and servers. The number of potential servers thus increases linearly with the size of the system, avoiding the performance bottleneck imposed by the presence of servers in traditional distributed systems. Such systems are therefore naturally protected from failures since there is no single point of failure and many services are naturally replicated.

Self-organizing capabilities:

Participating entities are by essence highly dynamic as they might be disconnected, mobile or faulty. The system should be able to handle such dynamic behaviors and get automatically reorganized to face entities arrival and departure.

Local system knowledge:

Individual entities behavior is based on a restricted knowledge of the system and yet the system should converge toward global properties.

The objective of the ASAP project-team is to cope efficiently with the intrinsic uncertainty of distributed systems and provide the foundations for a new family of distributed systems for which scalability and dynamicity are first class concerns, and to provide the basis for the design and the implementation of distributed algorithms suited to this new challenging setting. More specifically, our objectives are to work on the following complementary axes:


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