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Abstract-Optical data center network architectures are be- coming attractive because of their low energy consumption, large bandwidth, and low cabling complexity. In [1], an AWGR-based passive optical data center architecture (PODCA) is presented. Compared with other optical data center architectures, e.g., DOS [2], Proteus [3], and Petabit [4], PODCA can save up to 90% on power consumption and 88%...
Identification of protein complexes is very important to investigate the characteristics of biological processes. Most of existing protein complex clustering algorithms were often run only on a static protein-protein interaction (PPI) network. The dynamic characteristics of interactions were ignored. In order to solve the problem, a new clustering algorithm (TP-WDPIN) was proposed which is based on...
Cloud Computing (CC) is becoming increasingly pertinent and popular. A natural consequence of this is that many modern-day data centers experience very high internal traffic within the data centers themselves. The VMs with high mutual traffic often end up being far apart in the data center network, forcing them to communicate over unnecessarily long distances. The consequent traffic bottlenecks negatively...
We propose a topology-aware heuristic that significantly reduces the message latency for search trees of tree parallel Monte-Carlo Tree Search. There exist many communication-aware and topology-aware mappings. However, those mappings are not applicable to the hash driven parallel search techniques. This is because in hash driven parallel search each graph/tree node is randomly distributed based on...
Money Laundering (ML) is the process of cleaning “dirty” money, thereby making the source of funds no longer identifiable. Detecting money laundering activities is a challenging task due to huge volumes of financial transactions being made in a global market on a daily basis. This paper proposes a novel approach for detecting money laundering transactions among large volumes of financial data in an...
Network-on-chip (NoC) emerged as a promising alternative to the bus and point-to-point communication architectures. Recently 3D NoC become a hot topic. While complex 3D NoCs will generate a large amount of data to deal with, NoCs suffer from intermittent congestions and link overflows, especially when the network bandwidth is limited by the area and energy budget. In this paper, we explore a technique...
Vehicular Ad Hoc Networks (VANETs) are the most emerging ad hoc networks, that enabling wireless communications among nearby vehicles (V2V) as well as between vehicles and nearby fixed equipment (V2R). In recent years, VANETs have drawn greater attention of researchers as well as academician due to their significant attractive features such as dynamic connectivity, self-organizing and no centralized...
Botnets are one of the most serious threats in the Internet, and thus the effective detection of the botnet becomes more and more important. In this paper, inspired by IP tracing technology, we propose a novel botnet detection method that can analyze the data packets, based on graph structure clustering. This method analyzes the comprehensive information of packages content and timestamp flow. Such...
Network-on-Chip (NoC) is a promising solution for System-on-Chip (SoC) challenges. In this work, we present a Decompose and Cluster generation Refinement (DCR) algorithm to find minimum power consumption simultaneously. A two-stage method is proposed for decompose and cluster generation step to generate solutions with lower power. Refinement step explores optimal positions and adjusts clusters for...
In most of the systems, data collection is one of the major tasks to be carried out. The way of data collection can be automatic or manual. Adversity is the main cause that in many systems, manual intervention is not possible. So, opting for automated way isn't such bad idea. Depending upon the way of communication, wired or wireless, data can be collected through either wired or wireless networks...
In internet of vehicles (IOV), on-board Ad hoc network between vehicles is established randomly and freely based on dedicated short range communication technology, enabling the vehicles beyond visual range of drivers and signal transmission range of on-board communication equipment to establish communication connection for transmission and sharing of information and data through single-hop and multi-hop...
Community structure detection in complex networks is important since it can help better understand the network topology and how the network works. Compared with unsupervised method, semi supervised method may perform better. Previous works add and remove edges based on the prior information. But this method doesn't make full use of the prior information. It only used party of information to change...
Spontaneous network are called sometimes as accidental network formed by nodes which have mobility nature allocated in close proximity which connect to each other share resources and services. The creation of network with security concern is a point of issue in wireless network. The work aims to create network in secure manner. The updations of the nodes and further communication in the network to...
Support vector machines (SVM), originally introduced as powerful binary classifiers, can also be used for multi-class recognition with the help of creative meta-learning strategies such as commonly used one-vs-rest, one-vs-one and majority voting. In this paper, we explore the potential of creating informed nested dichotomies based on clustering pseudo-labels and probability estimates generated a...
In recent years, it has become more and more popular to recommend friends on the location-based social network (LBSN), which is combined with the user's behavior in the real world. LBSN has three attributes including temporal, spatial and social correlation. However, the combination situation of the three cannot be solved in previous algorithms. For instance, the problem of recommending friends with...
Clustering is an important technique widely used in many areas such as machine learning, pattern recognition, data analysis etc. Data stream clustering is a branch of clustering that draws much attention in recent years, where data objects are processed as an ordered sequence. In this paper, we propose an unsupervised learning neural network named Density Based Self Organizing Incremental Neural Network(DenSOINN)...
High performance computing (HPC) means the aggregation of computational power to increase the ability of processing large problems in science, engineering, and business. HPC on the cloud allows performing on demand HPC tasks by high performance clusters in a cloud environment. The connection structure of the nodes in HPC clusters should provide fast internode communication. It is important that scalability...
To evaluate the reliability of WSN whose topology is clustering structure, we model the WSN as a Weighted Voting System (WVS) with unreliable links, and propose an algorithm. The algorithm is based on universal generating function technique, and two composition operators are defined to composite u-functions of member nodes, links and cluster heads. Test results shows that the proposed algorithm can...
Taking into account the shortcomings of existing topology control algorithms for wireless sensor networks, a low energy uneven clustering (LEUC) topology control algorithm is proposed in this paper. The algorithm adopts three-stage election mechanism of cluster heads. First, selecting the candidate cluster heads is based on the threshold parameter. Second, the competition of temporary cluster heads...
A Hierarchical Weighted Voting System (HWVS) model is established to describe the process of data transmission on the wireless sensor network (WSN) whose topology is cluster. A new definitions about reliability of HWVS is presented. Based on universal generating function technique, an algorithm is suggested for evaluating the reliability of HWVS. The proof that suggested algorithm is applicable to...
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