George Parisis

Designing and realizing an information-centric internet

Information-centric networking has been attracting increasing attention within the networking community. Technological solutions as well as entire architectures have been proposed with subtle but seemingly important differences. In this article, we define a set of design tenets for an information-centric architecture together with a demonstration of its feasibility. For the latter, we present an early prototype of an artifact that is directly based on our design framework. This prototype is available under open source, deployed in a European-wide testbed, and can be used for Planetlab-scale experiments. Early indications of its performance show promising results for our future work.

Pursuing a Software Defined Information-centric Network

The areas of Software-Defined Networking (SDN) and Information-Centric Networking (ICN) have gained increasing attention in the wider research community, while gaining credibility through corporate interest and investment. With the promise of SDN to simplify the deployment of alternative network architectures, the question arises how SDN and ICN could concretely be combined, deployed and tested. In this paper, we address this very question within a particular architectural context for ICN. We outline a possible realization in a novel design for ICN solutions and point to possible test bed deployments for future testing.

Storage replication in information-centric networking

Shifting the communication paradigm of the internetworking layer from endpoints to information has been the focus for a variety of research efforts. Optimized dissemination of information within transient communication relationships of endpoints is the main promise of such efforts. Efficient replication of information is key to delivering on this promise. In this paper, we address this promise by proposing a storage placement and replica assignment algorithm for an information-centric networking architecture. For this, we present a node architecture that is based on a coherent set of architectural invariants that are utilized in the storage solution. By directly utilizing the information structures provided at the new internetworking layer, we enable the differentiation of classes of information based on their popularity with the attempt to minimize the overall network traffic. We show that such an algorithm can be easily implemented in an information-centric network environment and we evaluate our implementation through experimentation in a testbed and simulations, showing the feasibility but also the potential of such solutions.

DHTbd: A Reliable Block-Based Storage System for High Performance Clusters

Large, reliable and efficient storage systems are becoming increasingly important in enterprise environments. Our research in storage system design is oriented towards the exploitation of commodity hardware for building a high performance, resilient and scalable storage system. We present the design and implementation of DHTbd, a general purpose decentralized storage system where storage nodes support a distributed hash table based interface and clients are implemented as in-kernel device drivers. DHTbd, unlike most storage systems proposed to date, is implemented at the block device level of the I/O stack, a simple yet efficient design. The experimental evaluation of the proposed system demonstrates its very good I/O performance, its ability to scale to large clusters, as well as its robustness, even when massive failures occur.

Towards an approximate graph entropy measure for identifying incidents in network event data

A key objective of monitoring networks is to identify potential service threatening outages from events within the network before service is interrupted. Identifying causal events, Root Cause Analysis (RCA), is an active area of research, but current approaches are vulnerable to scaling issues with high event rates. Elimination of noisy events that are not causal is key to ensuring the scalability of RCA. In this paper, we introduce vertex-level measures inspired by Graph Entropy and propose their suitability as a categorization metric to identify nodes that are a priori of more interest as a source of events. We consider a class of measures based on Structural, Chromatic and Von Neumann Entropy. These measures require NP-Hard calculations over the whole graph, an approach which obviously does not scale for large dynamic graphs that characterise modern networks. In this work we identify and justify a local measure of vertex graph entropy, which behaves in a similar fashion to global measures of entropy when summed across the whole graph. We show that such measures are correlated with nodes that generate incidents across a network from a real data set.

Digital fountains in information-centric networking

In this paper, we revisit digital fountains as an information theoretic approach for disseminating information. We embed this approach, however, into the architectural context of information centric networking (ICN). We discuss how our information-centric network architecture enables efficient information dissemination through fountain coding and we present the basic network operations for disseminating information from publishers to subscribers.

Vertex Entropy As a Critical Node Measure in Network Monitoring

Understanding which node failures in a network have more impact is an important problem. Current understanding, motivated by the scale free models of network growth, places emphasis on the degree of the node. This is not a satisfactory measure; the number of connections a node has does not capture how redundantly it is connected into the whole network. Conversely, the structural entropy of a graph captures the resilience of a network well, but is expensive to compute, and, being a global measure, does not attribute any specific value to a given node. This lack of locality prevents the use of global measures as a way of identifying critical nodes. In this paper, we introduce local vertex measures of entropy which do not suffer from such drawbacks. In our theoretical analysis, we establish the possibility that our local vertex measures approximate global entropy, with the advantage of locality and ease of computation. We establish properties that vertex entropy must have in order to be useful for identifying critical nodes. We have access to a proprietary event, topology, and incident dataset from a large commercial network. Using this dataset, we demonstrate a strong correlation between vertex entropy and incident generation over events.

GSAF: Efficient and flexible geocasting for opportunistic networks

With the proliferation of smartphones and their advanced connectivity capabilities, opportunistic networks have gained a lot of traction during the past years; they are suitable for increasing network capacity and sharing ephemeral, localised content. They can also offload traffic from cellular networks to device-to-device ones, when cellular networks are heavily stressed. Opportunistic networks can play a crucial role in communication scenarios where the network infrastructure is inaccessible due to natural disasters, large-scale terrorist attacks or government censorship. Geocasting, where messages are destined to specific locations (casts) instead of explicitly identified devices, has a large potential in real world opportunistic networks, however it has attracted little attention in the context of opportunistic networking. In this paper we propose Geocasting Spray And Flood (GSAF), a simple but efficient and flexible geocasting protocol for opportunistic, delay-tolerant networks. GSAF follows a simple but elegant and flexible approach where messages take random walks towards the destination cast. Messages that follow directions away from the cast are extinct when the device buffer gets full, freeing space for new messages to be delivered. In GSAF, casts do not have to be pre-defined; instead users can route messages to arbitrarily defined casts. Our extensive evaluation shows that GSAF is efficient, in terms of message delivery ratio and latency as well as network overhead.

Enhancing multi-source content delivery in content-centric networks with fountain coding

Fountain coding has been considered as especially suitable for lossy environments, such as wireless networks, as it provides redundancy while reducing coordination overheads between sender(s) and receiver(s). As such it presents beneficial properties for multi-source and/or multicast communication. In this paper we investigate enhancing the efficiency of multi-source content delivery in the context of Content-Centric Networking (CCN) with the usage of fountain codes. In particular, we examine whether the combination of fountain coding with the in-network caching capabilities of CCN can further improve performance. We also present an enhancement of CCNs Interest forwarding mechanism that aims at minimizing duplicate transmissions that may occur in a multi-source transmission scenario, where all available content providers and caches with matching (cached) content transmit data packets simultaneously. Our simulations indicate that the use of fountain coding in CCN is a valid approach that further increases network performance compared to traditional schemes.

Short vs. Long Flows: A Battle That Both Can Win

In this paper, we introduce MMPTCP, a novel transport protocol which aims at unifying the way data is transported in data centres. MMPTCP runs in two phases; initially, it randomly scatters packets in the network under a single congestion window exploiting all available paths. This is beneficial to latency-sensitive flows. During the second phase, MMPTCP runs in Multi-Path TCP (MPTCP) mode, which has been shown to be very efficient for long flows. Initial evaluation shows that our approach significantly improves short flow completion times while providing high throughput for long flows and high overall network utilisation.