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Distributed Mininet implementations have been extensively used in order to overcome Mininet's scalability issues. Even though they have achieved a high level of success, they still have problems and can face bottlenecks due to the insufficient placement techniques. This paper proposes a new placement algorithm for distributed Mininet emulations with optimisation for Fat-Tree topologies. The proposed...
Recent rapid scale out of high performance computing systems has rapidly and continuously increased the scale and complexity of the interconnects. As a result, current static and over-provisioned interconnects are becoming cost-ineffective. Against this background, we have been working on the integration of network programmability into the interconnect control, based on the idea that dynamically controlling...
This paper provides insight into the effects of cross-border infrastructure and logical interconnections in Africa on both intra-country and cross-border latency on end-to-end Internet paths, by comparing Internet performance measurements between different countries. We collected ICMP pings between countries using Speedchecker and applied a community detection algorithm to group countries based on...
3D gated clock tree synthesis (CTS) mainly consists of three steps: 1) abstract clock topology generation; 2) layer embedding for minimal TSV allocation and 3) clock tree routing with gate and buffer insertion. In this paper, a self-tuning spectral clustering based nearest-neighbor selection (SSC-NNS) algorithm with parallel structure is proposed to achieve high time efficiency in clock tree topology...
In topology representations such as maps, carbon nanotubes, and cellular networks, neighboring cells are assigned different exclusive colors to represent different characteristics. In the previous research, based on the fourcolor theorem, an algorithm that can allocate exclusive channels among neighbors using only four channels in a polygonal cluster sensor network is proposed. The performance of...
Topological data analysis is a noble method to analyze high-dimensional qualitative data using a set of properties from topology. In this paper, we explore the feasibility of topological data analysis for mining social media data by investigating the problem of image popularity. We randomly crawl images from Instagram, convert their captions to 300 dimensional numerical vectors using Word2vec, calculate...
Photovoltaic is one of the electrical energy generating devices that potential for the future. In a large photovoltaic system, Photovoltaic Farm (PV Farm), there some issues that makes the operation less optimal. One of the problems is the shadow covering on the part of the area of PV Farm named Partially Shaded Condition. In topologies with single converter, partially shaded condition make the characteristic...
Instantiating a distributed application that involves extensive inter-node communication onto a network is a challenging task. In this work, we focus on the special case of mapping a network emulation experiment onto a cluster comprising several (possibly heterogeneous) physical machines. We automatically profile the available physical machine resources, and use this information, together with the...
In this paper, we concentrate on multi-target fusion and tracking problems in wireless sensor network (WSN) based on distributed clustering consensus filter. In particular, for the sake of the network lifetime and the tracking accuracy in multi-target cases, a distributed target-based clustering algorithm is proposed, which consists of the cluster member selection, the cluster head competition and...
Unsupervised feature selection has shown significant potential in distance-based clustering tasks. This paper proposes a novel triplet induced method. Firstly, a triplet-based loss function is introduced to enforce the selected feature groups to preserve ordinal locality of original data, which contributes to distance-based clustering tasks. Secondly, we simplify the orthogonal basis clustering by...
Large scale monitoring systems require reliable and efficient in-network information extraction mechanisms able to effectively track events at the field level. The study of consensus algorithms for distributed data processing has gained a lot of interest in the last decade. Average consensus algorithms used for decentralized sensor fusion in wireless sensor networks, iteratively compute the global...
Graph clustering is one of the most important research topics in graph mining and network analysis. With the abundance of data in many real-world applications, the graph nodes and edges could be annotated with multiple sets of attributes that could be derived from heterogeneous data sources. Considering these attributes during the graph clustering could help in generating graph clusters with balanced...
Software Defined Networking (SDN) technologies provide applications opportunities to manipulate underlying network flows and topologies via network controllers during runtime. In cloud environments, networked virtual machines can be enhanced by SDN by providing applications with controllable infrastructures to meet system-level quality requirements; however, customizing a suitable network topology...
This paper studies the multi-equilibria consensus problem for discrete-time multi-agent networks with fixed communication topologies. The agents are assumed to use the traditional distributed averaging based consensus algorithm that relies on neighbor information exchange. Given the graph of the network, two new notions of primary and secondary layer subgraphs are introduced, which are subsequently...
The topology of a Mobile Ad hoc Network (MANET) has substantial influence on its performance in that the transmission range and battery power of the nodes are not uniform in nature. The topology is susceptible to node and link failures which lead to network partitioning. Topology reconfiguration aims to recover from the failure and maintain the connectivity. Existing topology reconfiguration algorithms...
Now a days usage of Wireless Sensor Networks (WSNs) is increasing, because of its wide application. Unlike common networks the WSNs have the capability of reconfiguration, whenever any defect occurs in the network. However, while routing in these network the loss of data is occurring due to its security lack. Hence many researchers have presented their research for providing secure routing in WSNs...
Layout pattern classification, which groups similar layout clips into clusters, underlies a variety of design for manufacturability (DFM) applications such as hotspot library generation, hierarchical data storage, and yield optimization speedup. The key challenges of layout pattern classification are clip representation and clip clustering, while the mutually conflicting concerns are efficiency and...
Spontaneous progress in the field of wireless sensor networks (WSN) have led to development of various protocols for reliable communication and increasing longevity of the network. While designing the protocols for WSNs, designers come across the issues like limited energy per node, limited bandwidth for communication, security, minimum communication and computational cost. This paper focuses on energy...
Dimension reduction is one of the most important issues in machine learning and computational intelligence. Typical data sets are point clouds in a high dimensional space with a hidden structure to be found in low dimensional submanifolds. Finding this intrinsic manifold structure is very important in the understanding of the data and for reducing computational complexity. In this paper, we propose...
A Self-Enforcing Network (SEN), which is a self-organized neural network, is introduced to cluster medical data. In addition, a cue validity factor is defined, which affects the clustering of the data. The results show that a user can influence the clustering of data by SEN, thus allowing the analysis of the data depending on economical, medical or nursing interests. The described prototype includes...
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