Towards a Scalable and Adaptive Learning Approach for Network Intrusion DetectionRead the full article
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Scalable THz Network-On-Chip Architecture for Multichip Systems
While THz wireless network-on-chip (WiNoC) introduces considerably high bandwidth, due to the high path loss, it cannot be used for communication between far apart nodes, especially in a multichip architecture. In this paper, we introduce a cellular and scalable architecture to reuse the frequencies of the chips. Moreover, we use a novel structure called parallel-plate waveguide (PPW) that is suitable for interchip communication. The low-loss property of this waveguide lets us increase the number of chips. Each chip has a wireless node as a gateway for communicating with other chips. To shorten the length of intra- and interchip THz links, the optimum configuration is determined by leveraging the multiobjective simulating annealing (SA) algorithm. Finally, we compare the performance of the proposed THz multichip NoC with a conventional millimeter-wave one. Our simulation results indicate that when the system scales up from four to sixteen chips, the throughput of our design is decreased about , while for millimeter-wave NoC, this reduction is about . Furthermore, the average latency growth of our system is only compared with about increase for the millimeter-wave NoC.
FSB-DReViSeR: Flow Splitting-Based Dynamic Replacement of Virtual Service Resources for Mobile Users in Virtual Heterogeneous Networks
Virtual networks are sets of virtual devices that are interconnected through a physical network to provide services to end users. These services are usually heterogeneous (VOIP, VoD, streaming, etc.), exploit various amounts of resources (bandwidth, computing power, servers, etc.), and have topologies different from those of the substrate network. These variations in requirements are traditionally known as the architectural flexibility of virtual networks. Each virtual service is provided through a server called a virtual service resource. When a virtual service resource can no longer provide a good quality of service to end users due to the traffic variation generated by their mobility, two approaches are commonly implemented: provisioning the virtual network with resources or replacing the virtual service resource by migrating the service to another node that offers the most suitable amount of resource to satisfy the quality of service (QoS). In this paper, we propose a flow splitting-based dynamic virtual service resource replacement approach that allows for virtual service replacement across multiple virtual paths. Our approach is based on a graph topology that differs from those in the literature, which are based on tree topologies. The simulations performed in this study show that our approach significantly reduces the virtual service resource replacement time compared to other approaches.
A Use of Fuzzy TOPSIS to Improve the Network Selection in Wireless Multiaccess Environments
Constantly faster, mobile terminals are developing, as well as wireless networks, to satisfy the growth of “Always Best Connected” demand. Users nowadays want to access the best available wireless network, either from 3GPP or IEEE group technologies, wherever they are, without losing their sessions. Consequently, mobile terminals must seamlessly transfer the communications to another access technology (vertical handover) if needed, as they often move into heterogeneous wireless environments. This work aims to optimize the network selection step in the vertical handover process. Multiattribute Decision-Making methods naturally fit this context. Nevertheless, they make wrong handover decisions sometimes, due to imprecise data collected from the metrics. This manuscript presents the use of a hybrid method, combining the fuzzy technique for order preference by similarity to the ideal situation and fuzzy analytic network process, in the network selection, to improve the quality of service and avoid, as much as possible, unnecessary handovers. The results demonstrate that this combination is the best, compared to the other methods of the same type in the network selection context.
Mobile Cloud Computing: Taxonomy and Challenges
Mobile cloud computing (MCC) holds a new dawn of computing, where the cloud users are attracted to multiple services through the Internet. MCC has a qualitative, flexible, and cost-effective delivery platform for providing services to mobile cloud users with the aid of the Internet. Due to the advantage of the delivery platform, several studies have been conducted on how to address different issues in MCC. The issues include energy efficiency in MCC, secured MCC, user-satisfied applications and Quality of Service-aware MCC (QoS). In this context, this paper qualitatively reviews different proposed MCC solutions. Therefore, taxonomy for MCC is presented considering major themes of research including energy-aware, security, applications, and QoS-aware developments. Each of these themes is critically investigated with comparative assessments considering recent advancements. Analysis of metrics and implementation environments used for evaluating the performance of existing techniques are presented. Finally, some open research issues and future challenges are identified based on the critical and qualitative assessment of literature for researchers in this field.
Scale Features of a Network Echo Mechanism: Case Study for the Different Internet Paths
We have investigated dynamics of the Internet performance through the assessment of scaling features of a network ICMP echo mechanism or pinging. Time series of round-trip times (RTT) from the host computer to 5 destination hosts and back, recorded during three consecutive days and nights, have been used. To assess correlation and scaling features of network echo mechanism, we used method of detrended fluctuation analysis (DFA) for RTT data sets. It was shown that for different, 10 minute long periods of day and night observations, RTT data sets mostly fluctuate within a narrow range, though sometimes we observe strong sharp spikes. RTT variations mostly reveal persistent behavior. DFA fluctuation curves often are characterized by crossovers indication stronger or lesser changes in the dynamics of network performance. Distribution function of DFA scaling exponents of considered RTT time series mostly was asymmetric with long tail on the right hand side. Dynamical changes occurring in the scaling features of Internet network as assessed by RTT fluctuations do not depend on the location of the host and destination nodes. Larger delays in round-trip time responses make the scaling behavior of the RTT series complicated and strongly influence their long range correlation features.
A Node-Regulated Deflection Routing Framework for Contention Minimization
Optical Burst Switching (OBS) paradigm coupled with Dense Wavelength Division Multiplexing (DWDM) has become a practical candidate solution for the next-generation optical backbone networks. In its practical deployment only the edge nodes are provisioned with buffering capabilities, whereas all interior (core) nodes remain buffer-less. In that way the implementation becomes quite simple as well as cost effective as there will be no need for optical buffers in the interior. However, the buffer-less nature of the interior nodes makes such networks prone to data burst contention occurrences that lead to a degradation in overall network performance as a result of sporadic heavy burst losses. Such drawbacks can be partly countered by appropriately dimensioning available network resources and reactively by way of deflecting excess as well as contending data bursts to available least-cost alternate paths. However, the deflected data bursts (traffic) must not cause network performance degradations in the deflection routes. Because minimizing contention occurrences is key to provisioning a consistent Quality of Service (QoS), we therefore in this paper propose and analyze a framework (scheme) that seeks to intelligently deflect traffic in the core network such that QoS degradations caused by contention occurrences are minimized. This is by way of regulated deflection routing (rDr) in which neural network agents are utilized in reinforcing the deflection route choices at core nodes. The framework primarily relies on both reactive and proactive regulated deflection routing approaches in order to prevent or resolve data burst contentions. Simulation results show that the scheme does effectively improve overall network performance when compared with existing contention resolution approaches. Notably, the scheme minimizes burst losses, end-to-end delays, frequency of contention occurrences, and burst deflections.