2,295 research outputs found
Classification of networks-on-chip in the context of analysis of promising self-organizing routing algorithms
This paper contains a detailed analysis of the current state of the
network-on-chip (NoC) research field, based on which the authors propose the
new NoC classification that is more complete in comparison with previous ones.
The state of the domain associated with wireless NoC is investigated, as the
transition to these NoCs reduces latency. There is an assumption that routing
algorithms from classical network theory may demonstrate high performance. So,
in this article, the possibility of the usage of self-organizing algorithms in
a wireless NoC is also provided. This approach has a lot of advantages
described in the paper. The results of the research can be useful for
developers and NoC manufacturers as specific recommendations, algorithms,
programs, and models for the organization of the production and technological
process.Comment: 10 p., 5 fig. Oral presentation on APSSE 2021 conferenc
Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks
In this paper, a family of ant colony algorithms called DAACA for data
aggregation has been presented which contains three phases: the initialization,
packet transmission and operations on pheromones. After initialization, each
node estimates the remaining energy and the amount of pheromones to compute the
probabilities used for dynamically selecting the next hop. After certain rounds
of transmissions, the pheromones adjustment is performed periodically, which
combines the advantages of both global and local pheromones adjustment for
evaporating or depositing pheromones. Four different pheromones adjustment
strategies are designed to achieve the global optimal network lifetime, namely
Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data
aggregation algorithms, DAACA shows higher superiority on average degree of
nodes, energy efficiency, prolonging the network lifetime, computation
complexity and success ratio of one hop transmission. At last we analyze the
characteristic of DAACA in the aspects of robustness, fault tolerance and
scalability.Comment: To appear in Journal of Computer and System Science
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Adding the reliability on tree based topology construction algorithms for wireless sensor networks
Topology control is a technique used in wireless sensor networks to maximize energy efficiency and network lifetime. In previous literature, many tree based techniques have been proposed to save energy and increase the network lifetime. In tree based algorithms, the most promising solution is the formation of a network backbone, which serves on behalf of rest of the nodes in the network and therefore leading towards Connected Dominating Set (CDS) formulation. However, one imminent problem with all tree based solution is a compromise on network reliability. Therefore, to address reliability issues in tree based solutions, in this paper, we propose Poly3 which maintains cliques of size three in order to achieve network reliability on top of the CDS algorithm. This makes the network more robust to link removal. Our empirical and mathematical analysis reveals that Poly3 provides better reliability than algorithms of the same kind
Orion Routing Protocol for Delay-Tolerant Networks
In this paper, we address the problem of efficient routing in delay tolerant
network. We propose a new routing protocol dubbed as ORION. In ORION, only a
single copy of a data packet is kept in the network and transmitted, contact by
contact, towards the destination. The aim of the ORION routing protocol is
twofold: on one hand, it enhances the delivery ratio in networks where an
end-to-end path does not necessarily exist, and on the other hand, it minimizes
the routing delay and the network overhead to achieve better performance. In
ORION, nodes are aware of their neighborhood by the mean of actual and
statistical estimation of new contacts. ORION makes use of autoregressive
moving average (ARMA) stochastic processes for best contact prediction and
geographical coordinates for optimal greedy data packet forwarding. Simulation
results have demonstrated that ORION outperforms other existing DTN routing
protocols such as PRoPHET in terms of end-to-end delay, packet delivery ratio,
hop count and first packet arrival
Structure and topology of transcriptional regulatory networks and their applications in bio-inspired networking
Biological networks carry out vital functions necessary for sustenance despite environmental adversities. Transcriptional Regulatory Network (TRN) is one such biological network that is formed due to the interaction between proteins, called Transcription Factors (TFs), and segments of DNA, called genes. TRNs are known to exhibit functional robustness in the face of perturbation or mutation: a property that is proven to be a result of its underlying network topology. In this thesis, we first propose a three-tier topological characterization of TRN to analyze the interplay between the significant graph-theoretic properties of TRNs such as scale-free out-degree distribution, low graph density, small world property and the abundance of subgraphs called motifs. Specifically, we pinpoint the role of a certain three-node motif, called Feed Forward Loop (FFL) motif in topological robustness as well as information spread in TRNs.
With the understanding of the TRN topology, we explore its potential use in design of fault-tolerant communication topologies. To this end, we first propose an edge rewiring mechanism that remedies the vulnerability of TRNs to the failure of well-connected nodes, called hubs, while preserving its other significant graph-theoretic properties. We apply the rewired TRN topologies in the design of wireless sensor networks that are less vulnerable to targeted node failure. Similarly, we apply the TRN topology to address the issues of robustness and energy-efficiency in the following networking paradigms: robust yet energy-efficient delay tolerant network for post disaster scenarios, energy-efficient data-collection framework for smart city applications and a data transfer framework deployed over a fog computing platform for collaborative sensing --Abstract, page iii
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