49 research outputs found
Relay-assisted Multiple Access with Full-duplex Multi-Packet Reception
The effect of full-duplex cooperative relaying in a random access multiuser
network is investigated here. First, we model the self-interference incurred
due to full-duplex operation, assuming multi-packet reception capabilities for
both the relay and the destination node. Traffic at the source nodes is
considered saturated and the cooperative relay, which does not have packets of
its own, stores a source packet that it receives successfully in its queue when
the transmission to the destination has failed. We obtain analytical
expressions for key performance metrics at the relay, such as arrival and
service rates, stability conditions, and average queue length, as functions of
the transmission probabilities, the self interference coefficient, and the
links' outage probabilities. Furthermore, we study the impact of the relay node
and the self-interference coefficient on the per-user and aggregate throughput,
and the average delay per packet. We show that perfect self-interference
cancelation plays a crucial role when the SINR threshold is small, since it may
result to worse performance in throughput and delay comparing with the
half-duplex case. This is because perfect self-interference cancelation can
cause an unstable queue at the relay under some conditions.Comment: Accepted for publication in the IEEE Transactions on Wireless
Communication
Resilient networking in wireless sensor networks
This report deals with security in wireless sensor networks (WSNs),
especially in network layer. Multiple secure routing protocols have been
proposed in the literature. However, they often use the cryptography to secure
routing functionalities. The cryptography alone is not enough to defend against
multiple attacks due to the node compromise. Therefore, we need more
algorithmic solutions. In this report, we focus on the behavior of routing
protocols to determine which properties make them more resilient to attacks.
Our aim is to find some answers to the following questions. Are there any
existing protocols, not designed initially for security, but which already
contain some inherently resilient properties against attacks under which some
portion of the network nodes is compromised? If yes, which specific behaviors
are making these protocols more resilient? We propose in this report an
overview of security strategies for WSNs in general, including existing attacks
and defensive measures. In this report we focus at the network layer in
particular, and an analysis of the behavior of four particular routing
protocols is provided to determine their inherent resiliency to insider
attacks. The protocols considered are: Dynamic Source Routing (DSR),
Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing
(RWR)
Effect of Energy Harvesting on Stable Throughput in Cooperative Relay Systems
In this paper, the impact of energy constraints on a two-hop network with a
source, a relay and a destination under random medium access is studied. A
collision channel with erasures is considered, and the source and the relay
nodes have energy harvesting capabilities and an unlimited battery to store the
harvested energy. Additionally, the source and the relay node have external
traffic arrivals and the relay forwards a fraction of the source node's traffic
to the destination; the cooperation is performed at the network level. An inner
and an outer bound of the stability region for a given transmission probability
vector are obtained. Then, the closure of the inner and the outer bound is
obtained separately and they turn out to be identical. This work is not only a
step in connecting information theory and networking, by studying the maximum
stable throughput region metric but also it taps the relatively unexplored and
important domain of energy harvesting and assesses the effect of that on this
important measure.Comment: 20 pages, 4 figure
Network-Level Cooperation in Energy Harvesting Wireless Networks
International audienceWe consider a two-hop communication network consisted of a source node, a relay and a destination node in which the source and the relay node have external traffic arrivals. The relay forwards a fraction of the source node's traffic to the destination and the cooperation is performed at the network level. In addition, both source and relay nodes have energy harvesting capabilities and an unlimited battery to store the harvested energy. We study the impact of the energy constraints on the stability region. Specifically, we provide inner and outer bounds on the stability region of the two-hop network with energy harvesting source and relay
Hierarchical conditional dependency graphs as a unifying design representation in the CODESIS high-level synthesis system
International audienceIn high-level hardware synthesis (HLS), there is a gap in the quality of the synthesized results between data-flow and control-flow dominated behavioral descriptions. Heuristics destined for the former usually perform poorly on the latter. To close this gap, the CODESIS interactive HLS tool relies on a unifying intermediate design representation and adapted heuristics that are able to accommodate both types of designs, as well as designs of a mixed data-flow and control-flow nature. Preliminary experimental results in mutual exclusiveness detection and in efficiently scheduling conditional behaviors, are encouraging and prompt for more extensive experimentation
Coded ResNeXt: a network for designing disentangled information paths
To avoid treating neural networks as highly complex black boxes, the deep
learning research community has tried to build interpretable models allowing
humans to understand the decisions taken by the model. Unfortunately, the focus
is mostly on manipulating only the very high-level features associated with the
last layers. In this work, we look at neural network architectures for
classification in a more general way and introduce an algorithm which defines
before the training the paths of the network through which the per-class
information flows. We show that using our algorithm we can extract a lighter
single-purpose binary classifier for a particular class by removing the
parameters that do not participate in the predefined information path of that
class, which is approximately 60% of the total parameters. Notably, leveraging
coding theory to design the information paths enables us to use intermediate
network layers for making early predictions without having to evaluate the full
network. We demonstrate that a slightly modified ResNeXt model, trained with
our algorithm, can achieve higher classification accuracy on CIFAR-10/100 and
ImageNet than the original ResNeXt, while having all the aforementioned
properties