20,197 research outputs found
On the Impact of Network Topology on Wireless Sensor Networks Performances - Illustration with Geographic Routing
Poster in the Tenth ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2013)Wireless Sensor Networks (WSN) are composed of constrained devices and deployed in unattended and hostile environments. Most papers presenting solutions for WSN evaluate their work over random topologies to highlight some of their "good" performances. They rarely study these behaviors over more than one topology. Yet, the topology used can greatly impact the routing performances. This is what we demonstrate in this paper. We present a study of the impact of network topology on algorithms performance in Wireless Sensor Networks and illustrate it with geographic routing. Geographic routing is a family of routing algorithms using nodes coordinates to route data packet from source to destination. We measure the impact of different network topologies from realistic ones to regular and unrealistic ones through extensive simulations. Studied algorithms are common geographic greedy algorithms with different heuristics from the literature. We show that different topologies can lead to a difference of up to 25% on delivery ratio and average route length and more than 100% on overall cost of transmissions
Polarized routing for large interconnection networks
Supercomputers and datacenters comprise hundreds of thousands of servers. Different network topologies have been proposed to attain such a high scalability, from flattened Butterfly and Dragonfly to the most disruptive Jellyfish, which is based on a random graph. The routing problem on such networks remains a challenge that can be tackled either as a topology-aware solution or with an agnostic approach. The case of random networks is a very special one since no a priori topological clues can be exploited. In this article, we introduce the polarized routing algorithm, an adaptive nonminimal hop-by-hop mechanism that can be used in most of topologies, including Jellyfish. Polarized routing follows two design criteria: a source-destination symmetry in the routes and avoiding backtracking. Experimental evaluation proves that polarized routing not only outperforms other routings in random graphs but also attains the best performance provided by ad hoc solutions for specific outstanding low-diameter interconnection networks.This work has been supported by the Spanish Ministry of Science and Innovation under contracts PID2019-105660RB-C22 and FJCI-2017-31643. Simulations were performed in the Altamira supercomputer, a node of the Spanish Super-computing Network
Network Information Flow in Small World Networks
Recent results from statistical physics show that large classes of complex
networks, both man-made and of natural origin, are characterized by high
clustering properties yet strikingly short path lengths between pairs of nodes.
This class of networks are said to have a small-world topology. In the context
of communication networks, navigable small-world topologies, i.e. those which
admit efficient distributed routing algorithms, are deemed particularly
effective, for example in resource discovery tasks and peer-to-peer
applications. Breaking with the traditional approach to small-world topologies
that privileges graph parameters pertaining to connectivity, and intrigued by
the fundamental limits of communication in networks that exploit this type of
topology, we investigate the capacity of these networks from the perspective of
network information flow. Our contribution includes upper and lower bounds for
the capacity of standard and navigable small-world models, and the somewhat
surprising result that, with high probability, random rewiring does not alter
the capacity of a small-world network.Comment: 23 pages, 8 fitures, submitted to the IEEE Transactions on
Information Theory, November 200
Measuring and Understanding Throughput of Network Topologies
High throughput is of particular interest in data center and HPC networks.
Although myriad network topologies have been proposed, a broad head-to-head
comparison across topologies and across traffic patterns is absent, and the
right way to compare worst-case throughput performance is a subtle problem.
In this paper, we develop a framework to benchmark the throughput of network
topologies, using a two-pronged approach. First, we study performance on a
variety of synthetic and experimentally-measured traffic matrices (TMs).
Second, we show how to measure worst-case throughput by generating a
near-worst-case TM for any given topology. We apply the framework to study the
performance of these TMs in a wide range of network topologies, revealing
insights into the performance of topologies with scaling, robustness of
performance across TMs, and the effect of scattered workload placement. Our
evaluation code is freely available
Nature-Inspired Interconnects for Self-Assembled Large-Scale Network-on-Chip Designs
Future nano-scale electronics built up from an Avogadro number of components
needs efficient, highly scalable, and robust means of communication in order to
be competitive with traditional silicon approaches. In recent years, the
Networks-on-Chip (NoC) paradigm emerged as a promising solution to interconnect
challenges in silicon-based electronics. Current NoC architectures are either
highly regular or fully customized, both of which represent implausible
assumptions for emerging bottom-up self-assembled molecular electronics that
are generally assumed to have a high degree of irregularity and imperfection.
Here, we pragmatically and experimentally investigate important design
trade-offs and properties of an irregular, abstract, yet physically plausible
3D small-world interconnect fabric that is inspired by modern network-on-chip
paradigms. We vary the framework's key parameters, such as the connectivity,
the number of switch nodes, the distribution of long- versus short-range
connections, and measure the network's relevant communication characteristics.
We further explore the robustness against link failures and the ability and
efficiency to solve a simple toy problem, the synchronization task. The results
confirm that (1) computation in irregular assemblies is a promising and
disruptive computing paradigm for self-assembled nano-scale electronics and (2)
that 3D small-world interconnect fabrics with a power-law decaying distribution
of shortcut lengths are physically plausible and have major advantages over
local 2D and 3D regular topologies
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